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Both OpenAI and Google have released major new AI models within days of each other. OpenAI launched GPT-5.6, and Google has followed up with Gemini 3.6 Flash. While both companies have talked up the coding and developer features of these models, they also power the consumer versions of ChatGPT and Gemini.

So, rather than measuring them with programming benchmarks, I wanted to find out which is actually better at the kind of messy, everyday problems most people use AI to solve.

For this comparison, I matched Google's Gemini 3.6 Flash against GPT-5.6 Sol using its default Medium reasoning setting, since both are intended to be the standard high-quality models that paid subscribers will use for most tasks.

My digital life

So, I gave them my entire digital life for the week ahead.

I uploaded:

• Bank statements
• My calendar (they had access to my calendar app and I also sent in a screenshot of my calendar from another account I use).
• Grocery receipts
• Emails (both had access to my Gmail)
• WhatsApp screenshots
• Photos of my kitchen cupboards
• An energy bill
• Travel bookings
• Handwritten notes

Then I gave both models exactly the same instruction:

"Tell me everything I should do this week."

It sounds like a simple request, but it forces an AI to combine information from multiple sources, prioritize what's important, spot deadlines, reconcile conflicting information, and produce a practical action plan. In other words, it's exactly the kind of real-world problem people increasingly expect AI assistants to solve.

The results were like night and day.

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When I uploaded the files to Gemini 3.6 Flash and asked what I should do this week, it largely ignored the photos and concentrated on the screenshot of my calendar. Its initial answer mostly repeated the events I already knew were happening. Thanks, Gemini — I had the calendar open in front of me.

I then had to explicitly ask whether it could infer anything useful from the other images. It eventually offered some additional advice and did a good job of dividing the information into categories, including work, shopping, fitness, notes, and receipts. But it failed to flag that I had two clashing events in my calendar that evening. It also offered very little prioritization or practical guidance about what I should do next.

ChatGPT took considerably longer to respond, but its answer was far more useful. From the WhatsApp screenshots, it correctly deduced that attendance at my Friday Tai Chi class was likely to be low and suggested I decide whether it was still worth running. It noticed that yoga had been canceled, and spotted the two conflicting events in my calendar, telling me that I needed to choose between them.

It also totalled the receipts I had uploaded, suggested what I should do with them, and made a decent attempt at deciphering my handwritten notes. More importantly, it organized everything into a day-by-day plan for the coming week, then identified the three most urgent tasks, so I knew exactly where to begin.

The crucial difference

That was the crucial difference. Gemini told me what was in my files. ChatGPT worked out what I should do with the information. In World Cup terms, ChatGPT scored a hat trick while Gemini missed a penalty.

Google says Gemini 3.6 Flash improves coding, knowledge work, and multimodal performance compared with its previous models. That may be true, but in this particular multimodal test, it was comfortably beaten.

When I asked both AIs to make sense of real life rather than pass a benchmark, ChatGPT reasoned about the information in a far better way than Gemini did..

Does innovation happen only under pressure? It is a difficult question to ask, because history does give us a difficult answer.

Wars, shocks and national emergencies have often forced societies to move faster than they would in normal times, and many of the technologies we now take for granted came from moments nobody would wish to repeat.

The Second World War is the obvious example, with its lasting influence on medicine, aviation, computing, communications and manufacturing.

The Covid pandemic gave us a more recent version of the same pattern, when a global health crisis pushed scientists, regulators, governments and pharmaceutical companies to develop and approve vaccines at a speed that would previously have been treated as impossible.

Ukraine’s experience

It is often said that Ukraine’s experience of wartime innovation cannot be replicated in ‘peaceful’ Britain. In one sense, of course it cannot. One country is fighting for its survival against a much larger aggressor, while the other is an island nation that has lived for decades with the habits and assumptions of relative security.

Yet that argument only takes us so far. If urgency drives innovation, then the more useful question is what creates urgency in societies that are not at war. Or, to put it more plainly, what creates urgency in countries that do not really feel themselves to be under existential threat?

Britons continue to go about their daily lives much as they always have. People work, travel, argue about politics, worry about mortgages, watch sport, plan holidays and assume that the basic structures around them will continue to function. This sense of normality is, of course, a privilege. It is also one of the reasons why creating urgency in peacetime can be so difficult.

Britain, though, has repeatedly shown that it can innovate with extraordinary force when the need becomes clear. The Industrial Revolution transformed the country and then the world, with British engineers helping to build the railways, steam power and manufacturing systems that reshaped entire economies. For a small archipelago, Britain has had an unusual ability to turn technical advances into industry, infrastructure and global influence.

During the Second World War, that ability appeared again under extreme pressure. Radar helped defend British skies, then became part of the foundation for aviation, shipping, weather forecasting and modern sensing systems. Penicillin, discovered through British science, became a mass medical revolution because wartime urgency forced production and clinical adoption at scale.

At Bletchley Park, the need to break codes helped push electronic computing from theory into practical machinery, with Colossus showing what computation could achieve when the stakes were national.

More recent experience

More recently, the pandemic showed that this capacity has not disappeared.

Oxford researchers began human trials of their COVID-19 vaccine in April 2020. By December, Oxford and AstraZeneca had published the first peer-reviewed Phase III results for a coronavirus vaccine, and the UK became the first country to authorize the Oxford-AstraZeneca vaccine for public use. That was not an accident of national character. It happened because institutions, expertise, capital, government and industry were all pointed at the same urgent problem.

Innovation is therefore hardly foreign to Britain.. The question is what conditions have historically allowed it to move at speed, and whether those conditions can be created today without waiting for a disaster to create them for us.

That question is now becoming more urgent in defense. The war in Ukraine has shown how quickly military technology can evolve when adaptation becomes a matter of survival. Capabilities that might once have taken years to develop now change in months, and sometimes in weeks. Software updates, autonomous systems, drones, electronic warfare tools and battlefield data are changing how militaries think about capability, procurement and industrial readiness.

This shift has not gone unnoticed in Britain. The Strategic Defence Review repeatedly refers to the need for innovation, agility and "wartime pace" and those phrases now appear across government, military and industry discussions. That is progress, but language is only the beginning - the real test is whether Britain can build systems that make speed practical, funded and repeatable.

For much of its modern history, Ukraine has faced questions of sovereignty, territorial integrity and, at times, national survival. Following Russia's invasion in 2014 and again in 2022, the need to compensate for a larger adversary accelerated the adoption of drones, electronic warfare systems and other asymmetric capabilities. Innovation became part of a broader national effort to preserve statehood.

However, Ukraine also demonstrates why simple comparisons can be misleading. Countries do not all innovate for the same reasons, because countries do not all carry the same history. The pressures that shape Ukrainian urgency are not the same that shape British urgency and pretending otherwise would be lazy.

A very different story

Russia has often mobilized around a very different story, built on encirclement, external enemies and the restoration of great-power status. From Soviet narratives of confrontation with the West to contemporary rhetoric around NATO expansion and historical spheres of influence, the perception of an external challenge has repeatedly been used to justify national consolidation and state-led mobilization.

The United States offers another model again. American technological acceleration has often been driven by the ambition to lead, whether that meant reaching the Moon before the Soviet Union, dominating emerging industries, or maintaining military and economic advantage. Its urgency has often come from competition, scale and the belief that leadership itself is a national objective.

This suggests that urgency itself may not be the defining variable. Different societies move when different ideas become powerful enough to organize institutions, capital, industry and talent. Britain’s challenge is not to recreate Ukraine’s conditions, which are uniquely and painfully Ukrainian. Britain’s challenge is to identify the national objective that can generate serious effort in a British context.

Part of the answer may lie in the way Britain thinks about time. Earlier this year, addressing the United States Congress, King Charles referred to America’s founding 250 years ago and joked that, in British terms, it felt like “just the other day”. It was a light remark, but it captured something real about Britain’s historical outlook. This is a country that often sees itself across long stretches of time.

That can make Britain frustratingly slow at the beginning of a challenge. It can also make the country unusually powerful once it connects immediate pressure to a longer national story. Threat alone has rarely been enough as a British organizing principle. Britain has responded to danger when required, but some of its most important periods of innovation came when immediate pressure was tied to economic transformation, scientific leadership or institution-building.

The changing character of warfare

Seen through that lens, Ukraine is more than a warning about the changing character of warfare. It is an early view of technologies that are likely to shape economies and societies long after this war has ended. To mobilize Britain properly, the opportunity should not be presented as a narrow defense issue. The technologies being tested under the hardest conditions can become the basis of new industries, new standards and new areas of commercial leadership.

Britain has always been good at building industries around serious technologies once the need is understood. Its strength has rarely been invention alone. It has been the ability to create institutions, standards, markets, professional services, capital structures and global relationships around invention.

The country has many of the ingredients needed to lead here. It has excellent universities, serious engineering talent, strong financial markets, a respected legal system, advanced manufacturing capability, deep insurance expertise and global reach. It also has a long relationship with Ukraine and a new political framework through the UK-Ukraine 100 Year Partnership.

This is where the next stage of support for Ukraine should become more ambitious. The UK should continue to support Ukraine militarily, financially and diplomatically, because Ukraine is defending its sovereignty and the security of Europe. Alongside that support, technology partnership should become one of the defining features of the relationship.

The logic is straightforward. Ukraine has some of the most relevant operational learning in the world. Britain has the skills, institutions and history to turn urgent invention into global progress. Put together properly, that combination could help Ukraine rebuild, strengthen Britain’s preparedness and create technologies with value far beyond the current war.

That will require more than warm words. Britain should build a practical UK-Ukraine dual-use technology corridor around real problems and real users. That means identifying Ukrainian technologies and operational lessons with proven relevance, pairing them with British engineers, universities, investors, commercial customers, defense users and regulators, then testing them in real environments.

The focus should be on areas where Britain has a genuine need and Ukraine has hard-won experience. Protecting airports from drone disruption. Inspecting offshore energy assets. Improving emergency communications. Strengthening supply chains. Applying AI to difficult visual data. Detecting interference around critical infrastructure. Monitoring farmland and infrastructure with autonomous systems.

The ethical point matters. Ukraine cannot become a source of raw ideas for others to package, own and sell back to the world. If Britain wants to be trusted by Ukrainian founders, engineers, soldiers and policymakers, it has to treat Ukraine as a partner in value creation. The best arrangements will allow Ukrainian companies to scale internationally through the UK while keeping a proper stake in their intellectual property, commercial future and national recovery.

A hard strategic reason

There is also a hard strategic reason to get this right. Every serious country is now rethinking defense, industrial resilience and technology. The United States, Germany, Japan and others are deepening their relationships with Ukraine because they understand that the war is reshaping the future of security. Britain has been one of Ukraine’s strongest allies, and that support is recognized with real gratitude. The next stage should match that moral commitment with a more ambitious technology partnership.

Procurement will decide whether this becomes real. A start-up cannot wait years for a serious decision. Investors will struggle to back complex national security technologies if successful trials lead nowhere. Defense users need permission to test smaller companies without being trapped by process. Commercial customers need help understanding where battlefield-tested technologies can be used safely, lawfully and usefully in civilian settings.

Without those pathways, Britain will admire Ukrainian innovation in public while failing to absorb its lessons in practice. That would be a serious missed opportunity. The technologies being shaped in Ukraine will influence how we inspect buildings, move goods, respond to disasters, protect power networks, secure public spaces, monitor farmland and manage risk. Some will remain military. Many will move into civilian life so gradually that, in ten years, people may forget where the original lessons came from.

That has always been the way. Radar did not remain a wartime technology. Penicillin did not remain a wartime medicine. Computing did not remain hidden inside codebreaking. Once wartime pressure forced progress, society found wider uses, and the countries that knew how to translate those advances gained economic, scientific and strategic power.

Britain has done this before. It has turned moments of pressure into technologies, industries and institutions that shaped the modern world. Ukraine is now revealing where the next wave of defense and dual-use technology is heading. The UK should help build it, and it should do so with Ukraine.

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Artificial intelligence (AI) is constantly reshaping everything we do. Across industries, it is changing the way we do work, but that rapid expansion can’t continue without bumping up against real tangible limitations.

Most notably, planning for hyper scaled data centers across the world and increasingly complex cloud computing infrastructures and AI systems are leading to difficult conversations around energy pricing, generation and availability.

Around the world, electricity consumption is increasing at some of the fastest rates seen in decades, and there are no signs of it slowing down. The International Energy Agency (IEA) projects global electricity demand growth of 3.3% in 2025 and 3.7% in 2026, driven heavily by those same data centers, AI deployment, and other advanced industrial expansion.

The IEA has also warned that electricity demand from data centers is expected to double by 2030, with AI-focused facilities alone projected to triple their power use over the same period.

The financial implications and policy blowbacks are already starting to be felt. With limited expansions of electrical grids, more consumers are fighting for less resources, causing prices to only go up. In fact, according to S&P Global, some regions with AI data centers have seen wholesale electricity prices surge by more than 250% in the past five years.

This growing tension between AI advancement and energy availability is beginning to reshape how the technology sector thinks about the future of innovation. For years, the dominant assumption was that progress in AI would mainly come from scaling model size and centralized compute infrastructure.

But the next wave of value creation will also come from AI embedded in the physical world: machines, devices, buildings, industrial assets, medical wearables, and infrastructure that continuously sense, act, and adapt. In that context, the question is not only how to train larger models, but how to process massive streams of real-world data with minimal latency and minimal energy.

That is why alternative architectures, including low-power and decentralized AI, are becoming strategically important.

What low-power AI systems are

Low-power AI are systems specifically designed to minimize the resources required for inference and online learning, particularly energy consumption, while still delivering on high-performance expectation. Rather than relying entirely on massive cloud-based infrastructure and centralized data centers that guzzle down energy, these systems prioritize resource-efficiency at every level of the technology stack, from semiconductor architecture to data processing and deployment.

Low-power AI is not a single breakthrough at model level. It is a system-design discipline that spans sensing, signal conditioning, embedded processing, semiconductor architecture, algorithm optimization, and deployment. The real challenge is to co-design hardware and software for a specific use case so that intelligence is delivered where it matters, with the lowest possible energy budget.

This is precisely where research-transfer institutions such as CSEM can contribute: by combining expertise in sensors, edge computing, ultra-efficient IC design, and application-driven system integration to translate AI into robust real-world solutions rather than generic demonstrations.

Most of the focus in AI development has been in creating systems that are trained and operated on generalized architecture, handling a wide array of tasks simultaneously. These systems are immensely powerful but rely on the same models that require copious amounts of energy to keep them functioning.

On the contrast, low-power AI systems focus on more highly specialized systems, limited in scope and capabilities to a well-defined set of tasks that allow them to be less reliant on vast infrastructure and energy resources to function.

This includes edge AI, where data is processed directly within devices and systems rather than being sent continuously to remote cloud infrastructure. That shift matters even more in the era of physical AI. When intelligence is embedded into the real world, the volume of potentially relevant data generated by sensors, machines, vehicles, buildings, and other assets becomes enormous.

Sending everything to the cloud is not only inefficient, but often too slow and too costly. Many decisions must be taken locally, in real time, with strong constraints on power, bandwidth, privacy, and reliability.

Low-power AI therefore becomes essential not just to reduce energy use, but to preprocess data close to where it is generated, extract the small fraction of information that is meaningful, and enable the broader system to be monitored and optimized for performance, resources, and health.

Perhaps most importantly, low-power systems expand where AI tools can realistically operate. Wearable medical devices, industrial sensors, remote monitoring systems, transportation infrastructure, and smart manufacturing environments all require AI systems capable of functioning within strict energy constraints.

These contexts show places where sustainability is not only a cost-effective measure, but a functional requirement. At the sub-milliwatt level, some systems can even move beyond battery dependence and become energy-autonomous, harvesting ambient energy from light, heat, or vibration to enable a true fit-and-forget lifecycle.

Why efficiency is becoming an imperative

Power generation capacity, transmission infrastructure, cooling resources, and semiconductor supply chains are all facing mounting, simultaneous pressure. The assumption that future competitiveness depends solely on building larger and more power-intensive systems may no longer hold true, with further expansion likely bringing with it exponentially higher costs.

Organizations capable of delivering efficient, highly targeted distributed AI systems could gain major strategic advantages and offers a pathway toward greater technological resilience, as their design natively makes them more resistant to fluctuations in electricity pricing, supply disruptions and geopolitical instability.

Additionally, a more sustainable option can bring value by reducing environmental impact, while still not sacrificing function. The conversation around responsible AI therefore cannot remain focused solely on software governance and ethical frameworks but needs to be talking about how systems are powered, and how and where they process information.

A strategic opportunity for smaller nations

The rise of low-power AI also bears the opportunity to redefine who can meaningfully participate in the global AI race.

The United States and China have been postured as global tentpoles when it comes to the development of AI, and subsequently massive AI investments that have followed suit.

Both are examples of large nations that have the resources to invest billions into data centers, chip production and other infrastructure. On first glance, this paradigm forces many smaller nations to miss the financial and innovation benefits of the AI movement.

But with low-power and distributed AI systems, smaller countries do not need to compete on scale alone. They can compete through specialization, precision engineering, and the ability to translate research into deployable systems for demanding applications.

My home nation of Switzerland provides a useful framework for what this looks like in practice. Similar to most nations across the world, we cannot outspend the largest economies, but we do possess strong capabilities in microelectronics, embedded intelligence, sensing technologies, and high-value industrial and medical applications.

By recognizing these strong foundations, technology transfer organizations like ours can then play an important role in bridging these unique national strengths with industrial deployment, helping transform AI from a cloud-centric paradigm into efficient intelligence embedded in the physical world.

Even for relatively small nations with limited natural resources, there is an opportunity to be a leader in AI development by embracing low-energy system design. Chip producers with less resources will have to increasingly focus on creating specialized, energy-efficient technologies optimized for targeted applications to let them compete on the global stage.

As energy constraints become more severe, demand will likely grow for AI systems capable of operating efficiently in real-world conditions rather than exclusively within massive, centralized infrastructure environments.

In many ways, low-power AI could democratize portions of the AI boom by rewarding efficiency, precision, and specialization as opposed to simply providing opportunities for regions that can match scale. It can be said that virtually every country on earth has some level of specialized technical expertise that can be bridged to an AI use case.

The next generation of AI will see a shift from chat interfaces and cloud platforms to physical systems that shape daily life and industrial productivity. In that setting, efficient local intelligence is not a secondary optimization; it is a core architectural requirement.

Physical AI will depend on the ability to sense the world continuously, interpret it selectively, and act on relevant information without moving every raw data stream through centralized infrastructure.

The democratization of AI brings with it the need for more democratized solutions and opportunities for all to participate.

Looking ahead

While the early years of the AI boom have been defined by large, multi-purpose models and increasing scale, the next chapter will likely be written by developers and ecosystems that are able to utilize precision engineering to focus on low-power distributed systems that are by nature more resilient and sustainable.

Energy availability is no longer a secondary consideration in AI development and will increasingly be one of the defining variables shaping the future of the industry, and subsequently, how the global economy is built. That reality is making low-power AI an emerging necessity.

The next generation of AI systems must be designed with these restrictions in mind, requiring advances in semiconductor design, edge computing, specialized architectures, and intelligent energy management.

Countries and companies that embrace these more efficient and targeted systems may ultimately be better positioned for long-term competitiveness than those that rely instead on growing as large as possible as quickly as possible.

The European Union’s Joint Chips Undertaking is already bringing together its member nations, as well as some outside partners like Switzerland, to develop pathways to technologies like low-power chips. With that in mind, the future of AI may not belong solely to the biggest players, but to the smartest and most efficient ones.

For the global economy, that may prove to be one of the most important transitions of the AI era which only started to come to prominence recently with the growing controversies regarding hyperscale data centers.

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Every few years, enterprise software discovers a future it insists you cannot afford to miss.

Often these claims outrun the product, and amid the hype, organizations commit time and money to innovations that never quite live up to their billing.

Agentic AI is the exception, and that is exactly why it deserves a closer look.

We're not talking about chatbots that draft emails or summarize reports. This is something entirely different: software that acts.

Agentic AI can read a company's own approval hierarchies and permissions, make decisions within finance or supply chain processes, and execute them.

The last wave of enterprise AI offered suggestions. This one does the work. For the organizations that get it right, that is a different order of advantage.

The large vendors know this, which is why they have spent the past year racing to own agentic AI. At its Sapphire conference this spring, SAP unveiled what it calls the autonomous enterprise: more than 200 specialized agents that carry out tasks across the core business functions, orchestrated by some 50 domain-specific assistants and reached through a single interface, Joule.

Oracle has been building the same capability into Fusion, its cloud suite for finance, HR and supply chain.

Unlocking the potential

There has been no shortage of talk about what that could unlock, and for many organizations the excitement is well earned: an agent that can carry out work, not just recommend it, changes what the software is for. But for most of them, already running this software, capability was never going to be the sticking point. Access is.

As the major vendors have built it, agentic AI is native to the system of record, woven into the core platform that runs the business. That is a real achievement: an agent that respects your permissions and executes a live transaction is worth far more than one bolted from outside.

But "native" also carries a second meaning – and this one never makes the keynote speech. With the agent tethered to the vendor's cloud platform, there can be no reaching it without committing to that same platform, regardless of what your systems run on today.

SAP shows how that gate works. Until this spring, Joule reached only customers on its cloud subscriptions: RISE and GROW. At Sapphire, with much of its installed base showing little sign of moving, SAP opened a door, but a narrow one. ECC and S/4HANA on-prem customers are no longer shut out, provided they commit to moving the majority of their SAP estate to Cloud ERP.

Even then, they get only a limited set of the AI capabilities rather than the full portfolio. The on-prem route, in other words, is sold on the condition that you start paying for the cloud. And for the older ECC core, a clock is running regardless: mainstream maintenance ends in December 2027, with a stay of execution to 2030 at a premium, after which the choice narrows to an unsupported system or an upgrade.

So an ECC customer that takes the on-prem route is still paying for the cloud to access AI capabilities, even as support drains out of the system that they rely on (according to a timeline they never chose).

A more direct route

Oracle arrives at the same place by a more direct route: its agents do not exist outside the cloud. The Fusion agentic applications it has rolled out this year run only inside Fusion Cloud, on Oracle's own infrastructure and within its security model. There is no on-prem edition to license. An organization still running E-Business Suite cannot switch these agents on where its systems sit today; to use them at all, that organization will have to re-platform onto Fusion.

Strip away the packaging and the structure is the same in both cases: the on-ramp to agentic AI is the migration these vendors have been trying to sell all this time. What is new is the leverage. Cost, risk and disruption have held many organizations on-prem for years – despite all the pressure to move. Could the prospect of being shut out of agentic AI be the argument that finally overcomes their objections?

The budget is already committed

The migration and the AI draw on the same budget, and the migration has first claim on it. In the Americas' SAP Users' Group, 61% of members reported that budget was the biggest challenge they faced this year, and the group's research director was blunt about the cause: the cloud ERP projects are themselves creating the pressure, with AI expected to land on the same budgets next.

The sequence is unforgiving. Pay to reach the platform, then pay again to use the AI once you are there, because the headline subscription covers only a limited band of embedded features, and the rest is metered by consumption. The capital a CIO would want to invest in building an advantage is spoken twice before a single agent has delivered a measurable outcome.

And that is before the program meets its harder test. Boards have grown tired of pilots that never reach production and spending that generates activity no one can tie to an outcome. In some cases, these will be genuine execution failures, but a program that starts short of capital, on a timetable set by someone else, is not starting from a position of control.

Who decides the order of operations?

A CIO should separate the two decisions the vendor has deliberately combined. Whether to modernize is one question. When to do it, in what order, and against which budget is another. Nothing requires that the second be dictated by an end-of-support date printed on someone else's roadmap.

The critical issue here is who holds the authority to decide how the organization's most critical systems change and when. When a vendor sets the timetable, the sequence and the price of innovation, the executive accountable for that estate is not really the one running it anymore. Restoring that authority does not mean refusing to modernize. It means refusing to let the vendor selling the upgrade also decide when and how you buy it.

This is the case for third-party software support. An independent provider maintains the existing ERP estate, keeping it secure and preserving interoperability in place of the vendor's maintenance contract – and typically at a fraction of the cost. That does two things. It removes the end-of-support date as a forcing function, because now the system will stay supported whether or not the organization moves.

And it frees the maintenance budget that would otherwise fund the vendor's marketing roadmapping, so the money can go towards AI investments the organization actually wants to make. The stable core stops being a liability to escape on the vendor's schedule and becomes what it always was: productive capital, running the business while leadership decides on its own terms where agentic AI earns its place.

From there the real options open up. An organization can hold that stable core and run agentic AI as an orchestration layer above it, reaching into the system of record without re-platforming the whole estate first.

Or it can modernize selectively – moving from proprietary databases to open-source alternatives that eliminate vendor license fees, where there’s a business case for it – on a timetable set by business value rather than a maintenance deadline. What matters is that the sequence belongs to the organization.

The case for authority

The case for holding that authority is stronger with agents than it was with assistants. Tying the behavior and the governance of a system that acts on your business to a single vendor's platform roadmap is a heavier dependency than the previous era ever required.

Governed autonomy is the right ambition, but governance an organization sets for itself is a wholly different thing from governance inherited from the platform it happens to sit on.

The vendors are right about one thing: agentic AI is a capital decision, not a software purchase. But a capital decision means choosing where the money goes and what you expect back from it. When the vendor sets the timing, the sequence and the price, that is not allocating capital, it is settling an invoice.

The autonomous enterprise may well be worth building. What a board should refuse is to let its timetable and its budget be set by the company with the most to gain from the move.

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The global AI in IoT market has grown rapidly within the last year, with its value reaching $4.08 billion in 2025, and forecast to reach $6.45 billion by 2035. This progress reflects a wider industry shift, as with the rise of AI organizations are increasingly looking towards a more intelligent and connected future to achieve more from their IoT deployments.

Building additional defenses with AI-powered IoT security

The nature of the IoT can be complex, with devices often operating outside traditional IT security perimeters and in globally distributed environments. Within this landscape, connected devices now form the backbone of daily operations, from energy and healthcare to retail and manufacturing. As digitalization increases, so too will the critical functions that depend on connected devices.

Importantly, as deployments accelerate, so too does the potential IoT attack surface area. Due to the interconnected nature of the IoT, each device acts as a potential entry point for cybercriminals. With the UK government reporting the annual cost of cyberattacks as £14.7 billion annually, it is crucial that the entire IoT deployment is secure.

While private IP addressing and private APN approaches are useful in limiting exposure, they offer limited visibility into device behavior once traffic is flowing, particularly as deployments grow more complex.

AI, however, can see what may have previously been missed. Security has become a key area that can be elevated by AI-powered anomaly and threat detection, which detects behavior such as suspicious IPs, remote code execution, device backdoors or an abnormal port connection. This threat detection enables organizations to quickly identify the first sign of a cyberattack.

AI can even help identify the nature of attacks, including distributed denial-of-service (DDoS) and man-in-the-middle (MiTM) attacks, and device takeovers. By flagging irregularities in real time and enabling rapid corrective action, AI strengthens IoT security and supports more effective risk management, helping organizations avoid operational disruption, financial loss and reputational damage.

AI unlocks the value of IoT data

Beyond security concerns emanating from the IoT’s fragmented landscape, organizations may also struggle with data management and deriving meaningful analysis across the IoT’s web of networks, devices, cloud environments and enterprise processes.

The IoT constantly collects and transmits vast quantities of information, with a single internet-connected security camera generating around 300 GB of data per month. When these connected devices are multiplied and deployed globally on a much larger scale, organizations can be left with an overwhelming amount of data that can be difficult to utilize effectively.

Additionally, the role of the IoT is evolving. Whilst historically the IoT has purely had the role of connecting devices and gathering and transmitting data, there is growing industry pressure for intelligent solutions to inform decision-making and drive outcomes. Enterprises are now seeking more effective solutions to extract meaningful insights from IoT information, and without this, they will fail to unlock the true value of their data.

AI offers a promising solution to these challenges. AI-ready infrastructure is being increasingly prioritized by enterprises to support the collection, transmission, processing and integration of data into systems to enable AI-driven insights. The intelligent analysis AI offers enables patterns and trends in device fleets to be identified and analyzed more efficiently to help reduce manual intervention and lower costs.

Through advanced analytics and machine learning, AIoT can help organizations make better use of their data across the entire fleet, transforming data into an increasingly valuable asset that drives efficiency and long-term value.

Automation supports efficiency

Vast quantities of data across the IoT also make manual intervention expensive, ineffective and time consuming. These challenges can result in performance issues escalating unnoticed, or key device faults being missed.

The analytical and automation capabilities of AI can also support through real-time monitoring, automated fault resolution and predictive maintenance. By analyzing data on device usage, lifecycle maturity and performance, AI can identify potential issues before they arise. This enables a shift from reactive to proactive operations, reduced downtime and lower operating costs.

The benefits of AI-driven analytics are industry-wide. In manufacturing, for example, AI systems can use equipment performance data to estimate maintenance costs, consequently minimizing later expenses and downtime. In industries like healthcare, predictive maintenance also helps ensure the resilience of critical services like remote patient monitoring, where it is crucial that devices remain connected.

Rules-based automation can also support policy-driven fleet management and eSIM orchestration, with many capabilities gradually moving towards greater automation. In practice, adoption is iterative, starting with defined rules and oversight, before layering in AI-driven insights such as real-time usage, performance monitoring and anomaly detection to address issues more quickly.

As automation scales further, IoT environments will be able to respond flexibly to changing conditions with reduced manual intervention.

However, it must also be noted that as this progress continues, transparency and explainability remain crucial. Organizations must understand how decisions are made, and where human oversight remains critical as they scale.

Looking ahead to intelligent connectivity

AIoT’s influence will only grow moving forward. In fact, Transforma Insights’ forecast suggests a more than six-fold increase in connections over 10 years. Managing fleets intelligently and securely at scale, with transparency at the center of operations, must become an industry priority.

Those that can successfully integrate AI with scalable connectivity will be best positioned to move beyond simply managing devices towards truly intelligent operations. In doing so, they will unlock new efficiencies, strengthen resilience and create differentiated value in the IoT.

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Artificial intelligence has moved from experimentation to expectation at a remarkable speed. What began not that long ago as isolated pilots is now being embedded across every industry, from highly regulated sectors like financial services to those closest to the human experience, such as healthcare and the arts.

In just four years of widespread business use, these technologies have already moved from operational tools to business infrastructure, underpinning resilience and requiring the same meticulous planning and protection as any other critical system.

This shift is changing the way AI investment decisions must be made. As organizations rush to deploy AI tools, the challenge is no longer whether to invest but how to ensure investments create long-term value, while mitigating growing operational, security, and compliance risks.

Moreover, AI is not a purely digital investment. Behind every model, application, and workflow sits a physical technology estate: servers, storage, networking equipment, energy-intensive infrastructure, devices, and the supply chains that support them.

As AI adoption accelerates, enterprises risk expanding this estate without fully understanding the lifecycle consequences, from rising energy use and infrastructure refresh cycles to underutilized assets, electronic waste, and lost residual value.

Translating investment into impact

Investment in AI continues to rise exponentially, seemingly unimpeded by rising market prices or economic instability. Today, 71% of CEOs rank AI as a top investment priority, yet many still struggle to translate capital expenditure into operational value.

According to Gartner, at least 50% of AI projects are abandoned after proof of concept. Projects that do become operational often fail to deliver a return on investment, with 56% of CEOs saying they have not realized any revenue or cost benefits from AI projects.

This points to a deeper issue: AI success depends less on experimentation alone and more on the quality of the investment, governance, and capability-building decisions that follow.

The AI impact gap

As complexity increases, an investment impact gap is emerging. Leaders expect AI and the tech that supports it to deliver strategic value, improve performance, and reduce risk, but when making investment decisions, they often continue to prioritize near-term costs over the lifecycle factors that determine whether those outcomes can actually be achieved.

Without a view of the lifecycle consequences of their tech investments, as AI adoption accelerates, businesses tend to prioritize factors that are easier to quantify and act on in the short term. Our own research shows that 64% of organizations have rejected a superior technology solution because of its upfront price.

This may reduce immediate financial strain, but it can also introduce operational friction, scalability issues, and erode performance over time. As EY's Americas CTO, Dan Diasio, recently noted, "There's a very clear limit to the amount of value you can create by just focusing on productivity and cost reduction."

AI introduces entirely new cost dynamics. Enterprises must account not only for acquisition and implementation, but also for ongoing expenditure tied to usage, energy consumption, governance, compliance, infrastructure, and model evolution. These lifecycle impacts are often invisible in traditional business cases, yet they increasingly determine whether AI investments create durable value.

Good AI governance starts with accountability and visibility

Similarly, AI does not respect organizational boundaries. Its costs, risks, and value are distributed across the business, making cross-functional accountability essential. And yet, investment decisions are often assessed in silos, making it harder to build a complete view of the risks and value that emerge across the lifecycle.

Likewise, organizations need to understand the scope and reach of the systems they have in production, as well as the financial, operational, security, and environmental impacts they will have throughout their lifecycle.

Without this end-to-end view, major financial and operational blind spots can emerge at critical moments, many of which are not anticipated or planned for. While security, privacy, and compliance consistently rank among the top AI concerns, our research found fewer than half rate data protection (49%) or compliance capabilities (46%) as a high priority when making technology investment decisions.

From cost to AI-driven impact

To close this gap, businesses need to move beyond narrow assessments of upfront price and near-term ROI. These measures still matter, but they do not capture the full lifecycle consequences of AI investments, particularly as systems become embedded in critical operations and begin influencing performance, resilience, compliance, risk, reputation, and long-term value creation.

This is the thinking behind Total Cost of Impact (TCI). TCI is a new model that helps organizations evaluate technology investments through a broader lifecycle lens, assessing not only what a solution costs to buy and implement, but what it will require, enable, constrain, and expose the business to over time.

TCI assesses four core areas of technology impact - financial, operational, security and compliance, and environmental and social - encouraging businesses to understand how investment decisions made today influence outcomes over time.

When applied at the point of investment, TCI makes the trade-offs, risks, and downstream consequences that conventional procurement models often overlook visible. In doing so, it creates a common language across business functions, reducing friction, improving collaboration, and helping ensure technology investments are aligned with strategic priorities from the outset.

Importantly, TCI is an agnostic model: it can be used not only to evaluate whether AI-enabled technologies deliver business value, but also to assess how the infrastructure that supports them is procured, used, scaled, maintained, reused, and eventually retired.

Looking ahead

As AI lifecycles shorten, infrastructure demands grow, and resource constraints intensify, a lifecycle approach to technology investment is becoming a strategic necessity.

AI rollout cannot be separated from the physical infrastructure that enables it. Organizations need to understand not only what AI systems can deliver, but what they will require in energy, data, and asset governance, maintenance, refresh cycles, and end-of-life management over time.

This is why circularity must be part of the AI investment conversation. By taking an end-to-end view of technology assets, businesses can identify opportunities to extend lifespans, increase utilization, recover residual value, reduce waste, and manage end-of-life risk. Circularity is not a separate sustainability agenda; it is a practical way to reduce hidden costs, strengthen resilience, and improve the long-term impact of AI investment.

Ultimately, success with AI will depend not only on the capabilities organizations deploy, but on the quality of the decisions that support them. Those that assess the full impact of their technology decisions from the start will be better positioned to capture value, manage risk, and build resilient, future-ready digital infrastructure.

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A school district in upstate New York is pausing plans to deploy an AI-powered, humanoid robot in the classroom after state education officials, teachers and local residents raised concerns.

(Image credit: Abbie Parr)

HP Omen 16 Slim: Two-minute review

In these strange times where PC memory prices seemingly double by the day, an affordable gaming laptop is a tantalising prospect. But is it actually realistic? Enter the HP Omen 16 Slim, HP's latest mainstream gaming portable.

There are two core variants of the Omen 16, a standard-sized model and this so-called "Slim". Long story short, this Slim model is a little skinnier but still isn't exactly super compact for a 16-inch laptop, thanks to not only a fairly hefty lower screen bezel, but also a chassis that sticks out beyond the base of the display. At least the slightly tanky proportions translate into a tanky chassis with a solid feeling keyboard bed.

Anyway, it's the value proposition that matters and that means getting into the specs. CPU-wise, we're talking Intel Core Ultra 7 255H, which is a pretty modern 16-core chip from Intel's Arrow Lake generation. Here it's configured with 24GB of DDR5 in dual 12GB SoDIMMs. But various configs are available, including 16GB and 24GB.

There's also 1TB Gen 4 SSD, but with any gaming laptop surely the most important single component is the GPU and it's no surprise to find an Nvidia GeForce RTX 5060 8GB doing the pixel pumping duties.

(Image credit: Future)

It's one up from the bottom of Nvidia's RTX 50 Series laptop GPUs, but it gets the full feature set, including all the latest DLSS upscaling bells and whistles. It outputs to a 165Hz 16-inch LCD display with a native resolution of 1,920 by 1,200 pixels, making it a 16:10 aspect panel rather than the usual 16:9 ratio.

The battery is a pretty generous 70Wh item, meanwhile, and networking includes WiFi 6E, Bluetooth 5.4 and Ethernet. Slightly less impressive is the physical connectivity. Not only are you limited to just one USB-C port (plus three USB-A), it can only do a measly 10Gbps. So, the only video out is the single HDMI 2.1 port.

Of course, gaming performance is the key metric here, and the results are pretty good, albeit with one major caveat. This skinnier Omen 16 Slim makes do with 110W of Total Platform Power (TPP) and 80W maximum for the GPU, where the full-sized Omen 16 cranks that up significantly to 170W TPP. Given premium gaming laptops can supply as much as 175W and more just for the GPU, you can see how 110W for everything, including CPU, RAM and storage, can be a limiting factor.

That said, the RTX 5060 GPU is pretty efficient and well matched with the 1200p (near-enough 1080p) 165Hz display. You'll need to use DLSS upscaling to get slick frame rates in the most demanding games. But, broadly, you'll get fairly smooth results at very high detail settings. What's more, the chassis doesn't get too hot and the fan noise is moderate.

All of which means HP has done a nice job with the HP Omen 16 Slim. It's well built, mostly well specified and delivers a pretty sweet gaming experience. Whether it makes sense as a buy comes down to pricing. As configured here with 24GB of RAM, it's a little spendy. But there's an otherwise identical 16GB model that we just spotted for a whisker under $1,200. Right here in 2026, that's a very decent deal.

HP Omen 16 Slim review: Price & availability

(Image credit: Future)

• Available for £1,499 in the UK with 24GB of DDR5
• The closest US config rocks 16GB of DDR5 for $1,599
• Looks out for deals on sites like Newegg

In this precise configuration with 24GB of DDR5 RAM, the HP Omen 16 Slim weighs in at £1,399 in the UK. That's actually very good given current memory prices, right now. Indeed, you could argue it would make sense to knock that back to 16GB, keep everything else the same, and save some money.

Indeed, in the US, just that configuration is available, while the 24GB option is not. With 16GB, you're currently looking at $1,599, which is a fair bit less appealing. Currently, an otherwise identical version but with an RTX 5050 instead of the RTX 5060 can be had for $1,198 on Newegg, which implies you might be able to bag one with the 5060 and 16GB for around $1,400 at some point if you hang around and wait for a deal. At that price point, the HP Omen 16 Slim would start making a lot of sense.

HP Omen 16 Slim review: Specs

Base spec

Review config

Price

$1,189 / £1,100 (estimated UK price)

£1,399 / $1,799 (estimated US price)

CPU

Intel Core Ultra 7 255H

Intel Core Ultra 7 255H

Graphics

Nvidia GeForce RTX 5060 Laptop GPU

Nvidia GeForce RTX 5060 Laptop GPU

RAM

16GB DDR5

24GB DDR5

Display

16-inch 1200p (1,920 x 1,200), 144Hz, IPS, 300 nits

16-inch 1200p (1,920 x 1,200), 165Hz, IPS, 400 nits

Storage

1TB NVMe SSD PCIe Gen4

1TB NVMe SSD PCIe Gen4

Ports and Connectivity

1x USB Type-C 10Gbps (USB Power Delivery, DisplayPort 1.4), 3x USB Type-A 5Gbps, 1x ethernet, 1x headphone/mic combo jack, 1x HDMI 2.1, Wi-Fi 76E Bluetooth 5.4

1x USB Type-C 10Gbps (USB Power Delivery, DisplayPort 1.4), 2x USB Type-A 5Gbps, 1x ethernet, 1x headphone/mic combo jack, 1x HDMI 2.1, Wi-Fi 76E Bluetooth 5.4

Battery

70Whr

70Whr

Weight

5.35lbs / 2.425kg)

5.35lbs / 2.425kg

Dimensions

14.1 x 10.6 x 0.9 inches / 35.75 x 26.9 x 2.27 cm

14.1 x 10.6 x 0.9 inches / 35.75 x 26.9 x 2.27 cm

HP Omen 16 Slim review: Design

(Image credit: Future)

• Not actually that "Slim"
• Solid, well-built chassis
• Connectivity is only OK
• Cooling is well executed

The HP Omen 16 Slim is mostly plastic, just the bottom cover is metal. But it still feels very solid and durable. The Keyboard is nice and stable, with only a touch of flex when pushed hard. The keyboard, while we're on the subject, has four configurable RGB lighting zones, but at this price point, you're not going to get per-key lighting.

HP has done a nice job with the cooling, too. The twin fans draw air from the bottom cover and push it out the back and do so without making too much noise. However, despite the "Slim" branding, this is not a super compact laptop.

(Image credit: Future)

Coming in at 1.99cm to 2.27cm thick, where the standard Omen 16 measures between 2.39cm and 2.54cm, the 16 Slim is thinner than its sibling. But it's still not that compact.

Thanks to a rather large chine bezel and the way the rear of the chassis sticks out beyond the screen hinge, the Omen 16 Slim actually has a larger footprint than many laptops that trade on pure performance rather than portability and also tips the scales at 2.42kg. So, it's no featherweight.

In that context, the somewhat limited connectivity is a touch disappointing. You get three USB-A ports, but just one USB-C and even the latter is limited to 10Gbps, though it does at least support video out and charging the laptop itself.

HP Omen 16 Slim review: Performance

(Image credit: Future)

• Decent frame rates at 1200p with DLSS
• Seriously quick SSD
• Fan noise is reasonable

HP Omen 16 Slim benchmarks

3DMark: Night Raid: 57,311; Fire Strike: 25,198; Time Spy: 10,454; Port Royal: 6,372
Geekbench 6: Multicore: 14,468; Single-core: 3,114
Cinebench R24: Single Core: 134; Multi Core: 2,713
Crossmark: Overall: 1,992; Productivity: 1,888; Creativity: 2,182; Responsiveness: 1,783
Passmark Overall: 10,817; CPU: 38,631; 2D Graphics: 819; 3D Graphics: 17,174; Memory: 3,094; Disk: 36,232
CrystalDiskMark: Read: 7,025MB/s; Write: 5,895MB/s
Shadow of the Tomb Raider: (1200p, High): 132fps; (1200p, High, DLSS Quality): 139fps
Total War: Warhammer III: (1200p, Ultra): 83fps; (1200p, Low): 205fps
Cyberpunk 2077: (1200p, Ultra, no RT): 70fps; (1200p, RT Ultra, DLSS Balanced): 51fps
Doom: Dark Ages: (1200p, Ultra): 57fps; (1200p, Ultra, DLSS Quality): 83fps
Battery Life (TechRadar movie test): 12 hours and 32 minutes

Intel's Core Ultra 7 255H is very much a known quantity, what with its eight Performance and eight Efficient CPU cores. It's all you need for gaming in CPU terms, so the HP Omen 16 Slim's critical gaming component compared with the competition among the best gaming laptops is that Nvidia RTX 5060 GPU and how well it's been implemented.

This thinner HP Omen 16 Slim model does suffer slightly in the wattage department, with the Total Platform Power shared across the GPU, CPU, memory and more capped at 110W. But that doesn't absolutely hobble gaming performance.

For instance, running at the 16-inch display's native 1,920 by 1,200 resolution, you can crank Cyberpunk 2077 right up, with Ultra RT settings and Quality DLSS scaling and still get 44fps average frame rate.

(Image credit: Future)

OK, that's not spectacular. But it is acceptable for a single-player title. Switch off the ray tracing and you'll be looking at frame rates nearer 100. Moreover, in less demanding games, let's say something a little older like Shadow of the Tomb Raider, you can hit over 130fps even without DLSS upscaling and really make the most of the 165Hz refresh rate of the 16-inch display.

Speaking of the screen, the 16:10 aspect is a little odd and adds a little GPU load versus a vanilla 1080p panel. But it's reasonably vibrant, with nice-ish colours and contrast and decent 3ms response times. It's nothing special, but probably what you'd expect at this price point.

Just note the panel reviewed here is the upgrade 400 nit option. The base display is only 300 nits, runs at 144Hz and has much less colour fidelity. Avoid that if at all possible.

(Image credit: Future)

The 16 Slim's thermal performance is pretty impressive, too. It doesn't get too hot under load and the fan noise is reasonable. Well, it is unless you enable "Unleashed Mode" in the Omen Gaming Hub app. That cranks up the fans, but doesn't do much for frame rates.

Elsewhere, the SSD is particularly nippy, clocking over 7GB/s for reads and nearly 6GB/s for writes. For what is pitched as a value-orientated system, that's impressive. As for other elements, the sound quality from the speakers is tolerable at this price point, but the volume could be a little higher, and the webcam quality is OK.

In terms of physical performance, the chassis feels robust, even though only the bottom cover is made of metal, and the keyboard base is nice and solid with minimal flex. As for the trackpad, it's mechanical and doesn't have niceties like a glass cover. But it's large and works well enough. It's also worth noting that the memory, storage and Wi-Fi cards are all upgradeable, which is welcome in an age where too many laptops have everything soldered on.

HP Omen 16 Slim review: Battery life

(Image credit: Future)

• Surprisingly good for a budget gaming laptop
• USB-C charging is supported
• Not actually all that portable

Undoubtedly one of the HP Omen 16 Slim's more impressive aspects is battery life. OK, you're not going to get more than a couple of hours of light gaming off the mains, but for watching video, this laptop has some real legs.

Our local video playback test netted over 12 and a half hours with the screen at half brightness. That's a realistic setting for use on, say, a plane, albeit you might want to wind the screen up a little in bright daylight.

Whatever, that's a very impressive result for a gaming laptop and makes this portable much more plausible as an all-round computing device to take with you on trips and outings. The caveat to that is that the fairly large proportions and relatively hefty 2.4kg kerb weight mean this isn't a laptop you're going to sling into a small shoulder bag and forget about.

Should I buy the HP Omen 16 Slim?HP Omen 16 Slim: Scorecard

Attributes

Notes

Rating

Value

Prices are pretty variable depending on spec and location. But certain Omen 16 Slim configurations do look appealing. You may need to keep your scanners peeled for a good deal, however.

4 / 5

Design

The "Slim" branding suggests something very compact, but this is actually a fairly beefy 16-inch laptop. That said, it is solidly built with a decent keyboard. It's just a pity the connectivity isn't a touch more comprehensive.

4 / 5

Performance

This is a value-orientated gaming laptop, so expectations should be kept in check. But the RTX 5060 GPU matches well with the 16-inch display and you can run pretty much any title at high detail settings with the aid of DLSS upscaling.

3.5 / 5

Battery life

If there's one metric where the HP Omen 16 Slim delivers beyond expectations, it's battery life. You can expect over 12 hours of video playback, which is well beyond what most affordable gaming laptops can manage.

5 / 5

Total Score

Much depends on the price you can bag on the HP Omen 16 Slim. But if you can find a good deal, you'll get good performance, solid build and a nice all-round package.

4 / 5

Buy the HP Omen 16 Slim if…

You want decent value in today's weird market
Nothing's cheap when it comes to gaming PCs, these days. But the HP Omen 16 Slim is definitely decent value in the current context of spiralling memory prices.

You want good battery life
Most gaming laptops struggle away from the mains. But the HP Omen 16 Slim will do 12 hours-plus of video playback on the battery.

Don't buy it if…

You're looking for great portability
Despite the "Slim" branding, this is not a particularly compact or light 16-inch laptop. But it is solid and feels built to last.

You need cutting-edge performance
The HP Omen 16 Slim puts out decent frame rates for a mainstream laptop. But its RTX 5060 GPU is limited to 80W and this is not a high-end machine.View Deal

HP Omen 16 Slim review: Also consider

Asus V16
If you're looking for something even cheaper, try the Asus V16. It uses older Nvidia RTX 30 and 40 Series GPUs to achieve a few savings. But it's surprisingly well built and very portable for a gaming laptop. Read our full Asus V16 review.

Medion Erazer Major 16 X1
If you want more performance without breaking the bank, try the Medion Erazer Major 16 X1 and its RTX 5070 Ti GPU. It's heavy, feels and bit cheap and the battery life is poor. But it'll kick out some very impressive frame rates. Read our full Medion Erazer Major 16 X1 review.

How I tested the HP Omen 16 Slim HX

(Image credit: Future)

• Used as my daily rig for two weeks
• Threw my Steam library at
• Got forensic with the screen and build quality

I've been round the block when it comes to gaming laptops. My first portable ran a GeForce 2 Go, if you can remember back that far. My current lappie runs an RTX 4080, and there have been plenty more in between. ANd those are just my personal machines. I've long since lost count of how many gaming laptops I've reviewed. There are always a few knocking around.

Over the years, I've learned a lot about what makes a good gaming laptop and I applied that to the HP Omen 16 Slim over a couple of weeks. That means throwing everything in my Steam Library at it, from classic strategy titles like Total War to graphics fests including Cyberpunk 2077. All round performance, including the SSD, is also important, as is battery life for what is, ultimately, meant to be a portable machine.

I'm also very picky when it comes to screen quality and keyboard feel and have something of a forensic obsession with laptop build quality. You have to be realistic at this price point, but build quality is particularly important to gaming laptop longevity. Bendy chassis usually end up in flakey performance, eventually.

• First reviewed: July 2026
• Read more about how we test

HP Omen 16 Slim: Two-minute review

In these strange times where PC memory prices seemingly double by the day, an affordable gaming laptop is a tantalising prospect. But is it actually realistic? Enter the HP Omen 16 Slim, HP's latest mainstream gaming portable.

There are two core variants of the Omen 16, a standard-sized model and this so-called "Slim". Long story short, this Slim model is a little skinnier but still isn't exactly super compact for a 16-inch laptop, thanks to not only a fairly hefty lower screen bezel, but also a chassis that sticks out beyond the base of the display. At least the slightly tanky proportions translate into a tanky chassis with a solid feeling keyboard bed.

Anyway, it's the value proposition that matters and that means getting into the specs. CPU-wise, we're talking Intel Core Ultra 7 255H, which is a pretty modern 16-core chip from Intel's Arrow Lake generation. Here it's configured with 24GB of DDR5 in dual 12GB SoDIMMs. But various configs are available, including 16GB and 24GB.

There's also 1TB Gen 4 SSD, but with any gaming laptop surely the most important single component is the GPU and it's no surprise to find an Nvidia GeForce RTX 5060 8GB doing the pixel pumping duties.

(Image credit: Future)

It's one up from the bottom of Nvidia's RTX 50 Series laptop GPUs, but it gets the full feature set, including all the latest DLSS upscaling bells and whistles. It outputs to a 165Hz 16-inch LCD display with a native resolution of 1,920 by 1,200 pixels, making it a 16:10 aspect panel rather than the usual 16:9 ratio.

The battery is a pretty generous 70Wh item, meanwhile, and networking includes WiFi 6E, Bluetooth 5.4 and Ethernet. Slightly less impressive is the physical connectivity. Not only are you limited to just one USB-C port (plus three USB-A), it can only do a measly 10Gbps. So, the only video out is the single HDMI 2.1 port.

Of course, gaming performance is the key metric here, and the results are pretty good, albeit with one major caveat. This skinnier Omen 16 Slim makes do with 110W of Total Platform Power (TPP) and 80W maximum for the GPU, where the full-sized Omen 16 cranks that up significantly to 170W TPP. Given premium gaming laptops can supply as much as 175W and more just for the GPU, you can see how 110W for everything, including CPU, RAM and storage, can be a limiting factor.

That said, the RTX 5060 GPU is pretty efficient and well matched with the 1200p (near-enough 1080p) 165Hz display. You'll need to use DLSS upscaling to get slick frame rates in the most demanding games. But, broadly, you'll get fairly smooth results at very high detail settings. What's more, the chassis doesn't get too hot and the fan noise is moderate.

All of which means HP has done a nice job with the HP Omen 16 Slim. It's well built, mostly well specified and delivers a pretty sweet gaming experience. Whether it makes sense as a buy comes down to pricing. As configured here with 24GB of RAM, it's a little spendy. But there's an otherwise identical 16GB model that we just spotted for a whisker under $1,200. Right here in 2026, that's a very decent deal.

HP Omen 16 Slim review: Price & availability

(Image credit: Future)

• Available for £1,499 in the UK with 24GB of DDR5
• The closest US config rocks 16GB of DDR5 for $1,599
• Looks out for deals on sites like Newegg

In this precise configuration with 24GB of DDR5 RAM, the HP Omen 16 Slim weighs in at £1,399 in the UK. That's actually very good given current memory prices, right now. Indeed, you could argue it would make sense to knock that back to 16GB, keep everything else the same, and save some money.

Indeed, in the US, just that configuration is available, while the 24GB option is not. With 16GB, you're currently looking at $1,599, which is a fair bit less appealing. Currently, an otherwise identical version but with an RTX 5050 instead of the RTX 5060 can be had for $1,198 on Newegg, which implies you might be able to bag one with the 5060 and 16GB for around $1,400 at some point if you hang around and wait for a deal. At that price point, the HP Omen 16 Slim would start making a lot of sense.

HP Omen 16 Slim review: Specs

Base spec

Review config

Price

$1,189 / £1,100 (estimated UK price)

£1,399 / $1,799 (estimated US price)

CPU

Intel Core Ultra 7 255H

Intel Core Ultra 7 255H

Graphics

Nvidia GeForce RTX 5060 Laptop GPU

Nvidia GeForce RTX 5060 Laptop GPU

RAM

16GB DDR5

24GB DDR5

Display

16-inch 1200p (1,920 x 1,200), 144Hz, IPS, 300 nits

16-inch 1200p (1,920 x 1,200), 165Hz, IPS, 400 nits

Storage

1TB NVMe SSD PCIe Gen4

1TB NVMe SSD PCIe Gen4

Ports and Connectivity

1x USB Type-C 10Gbps (USB Power Delivery, DisplayPort 1.4), 3x USB Type-A 5Gbps, 1x ethernet, 1x headphone/mic combo jack, 1x HDMI 2.1, Wi-Fi 76E Bluetooth 5.4

1x USB Type-C 10Gbps (USB Power Delivery, DisplayPort 1.4), 2x USB Type-A 5Gbps, 1x ethernet, 1x headphone/mic combo jack, 1x HDMI 2.1, Wi-Fi 76E Bluetooth 5.4

Battery

70Whr

70Whr

Weight

5.35lbs / 2.425kg)

5.35lbs / 2.425kg

Dimensions

14.1 x 10.6 x 0.9 inches / 35.75 x 26.9 x 2.27 cm

14.1 x 10.6 x 0.9 inches / 35.75 x 26.9 x 2.27 cm

HP Omen 16 Slim review: Design

(Image credit: Future)

• Not actually that "Slim"
• Solid, well-built chassis
• Connectivity is only OK
• Cooling is well executed

The HP Omen 16 Slim is mostly plastic, just the bottom cover is metal. But it still feels very solid and durable. The Keyboard is nice and stable, with only a touch of flex when pushed hard. The keyboard, while we're on the subject, has four configurable RGB lighting zones, but at this price point, you're not going to get per-key lighting.

HP has done a nice job with the cooling, too. The twin fans draw air from the bottom cover and push it out the back and do so without making too much noise. However, despite the "Slim" branding, this is not a super compact laptop.

(Image credit: Future)

Coming in at 1.99cm to 2.27cm thick, where the standard Omen 16 measures between 2.39cm and 2.54cm, the 16 Slim is thinner than its sibling. But it's still not that compact.

Thanks to a rather large chine bezel and the way the rear of the chassis sticks out beyond the screen hinge, the Omen 16 Slim actually has a larger footprint than many laptops that trade on pure performance rather than portability and also tips the scales at 2.42kg. So, it's no featherweight.

In that context, the somewhat limited connectivity is a touch disappointing. You get three USB-A ports, but just one USB-C and even the latter is limited to 10Gbps, though it does at least support video out and charging the laptop itself.

HP Omen 16 Slim review: Performance

(Image credit: Future)

• Decent frame rates at 1200p with DLSS
• Seriously quick SSD
• Fan noise is reasonable

HP Omen 16 Slim benchmarks

3DMark: Night Raid: 57,311; Fire Strike: 25,198; Time Spy: 10,454; Port Royal: 6,372
Geekbench 6: Multicore: 14,468; Single-core: 3,114
Cinebench R24: Single Core: 134; Multi Core: 2,713
Crossmark: Overall: 1,992; Productivity: 1,888; Creativity: 2,182; Responsiveness: 1,783
Passmark Overall: 10,817; CPU: 38,631; 2D Graphics: 819; 3D Graphics: 17,174; Memory: 3,094; Disk: 36,232
CrystalDiskMark: Read: 7,025MB/s; Write: 5,895MB/s
Shadow of the Tomb Raider: (1200p, High): 132fps; (1200p, High, DLSS Quality): 139fps
Total War: Warhammer III: (1200p, Ultra): 83fps; (1200p, Low): 205fps
Cyberpunk 2077: (1200p, Ultra, no RT): 70fps; (1200p, RT Ultra, DLSS Balanced): 51fps
Doom: Dark Ages: (1200p, Ultra): 57fps; (1200p, Ultra, DLSS Quality): 83fps
Battery Life (TechRadar movie test): 12 hours and 32 minutes

Intel's Core Ultra 7 255H is very much a known quantity, what with its eight Performance and eight Efficient CPU cores. It's all you need for gaming in CPU terms, so the HP Omen 16 Slim's critical gaming component compared with the competition among the best gaming laptops is that Nvidia RTX 5060 GPU and how well it's been implemented.

This thinner HP Omen 16 Slim model does suffer slightly in the wattage department, with the Total Platform Power shared across the GPU, CPU, memory and more capped at 110W. But that doesn't absolutely hobble gaming performance.

For instance, running at the 16-inch display's native 1,920 by 1,200 resolution, you can crank Cyberpunk 2077 right up, with Ultra RT settings and Quality DLSS scaling and still get 44fps average frame rate.

(Image credit: Future)

OK, that's not spectacular. But it is acceptable for a single-player title. Switch off the ray tracing and you'll be looking at frame rates nearer 100. Moreover, in less demanding games, let's say something a little older like Shadow of the Tomb Raider, you can hit over 130fps even without DLSS upscaling and really make the most of the 165Hz refresh rate of the 16-inch display.

Speaking of the screen, the 16:10 aspect is a little odd and adds a little GPU load versus a vanilla 1080p panel. But it's reasonably vibrant, with nice-ish colours and contrast and decent 3ms response times. It's nothing special, but probably what you'd expect at this price point.

Just note the panel reviewed here is the upgrade 400 nit option. The base display is only 300 nits, runs at 144Hz and has much less colour fidelity. Avoid that if at all possible.

(Image credit: Future)

The 16 Slim's thermal performance is pretty impressive, too. It doesn't get too hot under load and the fan noise is reasonable. Well, it is unless you enable "Unleashed Mode" in the Omen Gaming Hub app. That cranks up the fans, but doesn't do much for frame rates.

Elsewhere, the SSD is particularly nippy, clocking over 7GB/s for reads and nearly 6GB/s for writes. For what is pitched as a value-orientated system, that's impressive. As for other elements, the sound quality from the speakers is tolerable at this price point, but the volume could be a little higher, and the webcam quality is OK.

In terms of physical performance, the chassis feels robust, even though only the bottom cover is made of metal, and the keyboard base is nice and solid with minimal flex. As for the trackpad, it's mechanical and doesn't have niceties like a glass cover. But it's large and works well enough. It's also worth noting that the memory, storage and Wi-Fi cards are all upgradeable, which is welcome in an age where too many laptops have everything soldered on.

HP Omen 16 Slim review: Battery life

(Image credit: Future)

• Surprisingly good for a budget gaming laptop
• USB-C charging is supported
• Not actually all that portable

Undoubtedly one of the HP Omen 16 Slim's more impressive aspects is battery life. OK, you're not going to get more than a couple of hours of light gaming off the mains, but for watching video, this laptop has some real legs.

Our local video playback test netted over 12 and a half hours with the screen at half brightness. That's a realistic setting for use on, say, a plane, albeit you might want to wind the screen up a little in bright daylight.

Whatever, that's a very impressive result for a gaming laptop and makes this portable much more plausible as an all-round computing device to take with you on trips and outings. The caveat to that is that the fairly large proportions and relatively hefty 2.4kg kerb weight mean this isn't a laptop you're going to sling into a small shoulder bag and forget about.

Should I buy the HP Omen 16 Slim?HP Omen 16 Slim: Scorecard

Attributes

Notes

Rating

Value

Prices are pretty variable depending on spec and location. But certain Omen 16 Slim configurations do look appealing. You may need to keep your scanners peeled for a good deal, however.

4 / 5

Design

The "Slim" branding suggests something very compact, but this is actually a fairly beefy 16-inch laptop. That said, it is solidly built with a decent keyboard. It's just a pity the connectivity isn't a touch more comprehensive.

4 / 5

Performance

This is a value-orientated gaming laptop, so expectations should be kept in check. But the RTX 5060 GPU matches well with the 16-inch display and you can run pretty much any title at high detail settings with the aid of DLSS upscaling.

3.5 / 5

Battery life

If there's one metric where the HP Omen 16 Slim delivers beyond expectations, it's battery life. You can expect over 12 hours of video playback, which is well beyond what most affordable gaming laptops can manage.

5 / 5

Total Score

Much depends on the price you can bag on the HP Omen 16 Slim. But if you can find a good deal, you'll get good performance, solid build and a nice all-round package.

4 / 5

Buy the HP Omen 16 Slim if…

You want decent value in today's weird market
Nothing's cheap when it comes to gaming PCs, these days. But the HP Omen 16 Slim is definitely decent value in the current context of spiralling memory prices.

You want good battery life
Most gaming laptops struggle away from the mains. But the HP Omen 16 Slim will do 12 hours-plus of video playback on the battery.

Don't buy it if…

You're looking for great portability
Despite the "Slim" branding, this is not a particularly compact or light 16-inch laptop. But it is solid and feels built to last.

You need cutting-edge performance
The HP Omen 16 Slim puts out decent frame rates for a mainstream laptop. But its RTX 5060 GPU is limited to 80W and this is not a high-end machine.View Deal

HP Omen 16 Slim review: Also consider

Asus V16
If you're looking for something even cheaper, try the Asus V16. It uses older Nvidia RTX 30 and 40 Series GPUs to achieve a few savings. But it's surprisingly well built and very portable for a gaming laptop. Read our full Asus V16 review.

Medion Erazer Major 16 X1
If you want more performance without breaking the bank, try the Medion Erazer Major 16 X1 and its RTX 5070 Ti GPU. It's heavy, feels and bit cheap and the battery life is poor. But it'll kick out some very impressive frame rates. Read our full Medion Erazer Major 16 X1 review.

How I tested the HP Omen 16 Slim HX

(Image credit: Future)

• Used as my daily rig for two weeks
• Threw my Steam library at
• Got forensic with the screen and build quality

I've been round the block when it comes to gaming laptops. My first portable ran a GeForce 2 Go, if you can remember back that far. My current lappie runs an RTX 4080, and there have been plenty more in between. ANd those are just my personal machines. I've long since lost count of how many gaming laptops I've reviewed. There are always a few knocking around.

Over the years, I've learned a lot about what makes a good gaming laptop and I applied that to the HP Omen 16 Slim over a couple of weeks. That means throwing everything in my Steam Library at it, from classic strategy titles like Total War to graphics fests including Cyberpunk 2077. All round performance, including the SSD, is also important, as is battery life for what is, ultimately, meant to be a portable machine.

I'm also very picky when it comes to screen quality and keyboard feel and have something of a forensic obsession with laptop build quality. You have to be realistic at this price point, but build quality is particularly important to gaming laptop longevity. Bendy chassis usually end up in flakey performance, eventually.

• First reviewed: July 2026
• Read more about how we test

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The nominations are in - and the finalists for the 2026 edition of the Power 50 can now be revealed.

Part of the Mobile Industry Awards 2026, the Power 50 highlights the most important and influential figures in the UK mobile industry during the past year.

The finalists for the Power 50 2026 have now been decided, with the final standings set to be revealed at the awards.

(Please note: these names are ranked A- Z by first name and not the final rankings.)

View the 2026 Power 50 here!

The winner, recognised with the Power 50 award at the Mobile Industry Awards on September 17 2026, is selected following in-depth interviews with key senior figures across the industry, from operators and retailers to manufacturers and distributors.

It rewards those individuals who inspire their businesses with their values, but also have influence beyond existing roles, serving as an inspiration to the rest of the trade.

To make the Power 50 list, an executive needs to be bold in their leadership and vision, and have exceeded expectations in the different categories we have chosen.

Power 50 Previous Winners 

• 2025: Max Taylor, CEO, VodafoneThree
• 2024: Marc Allera, CEO - EE and Consumer Division at BT Group
• 2023: Ahmed Essam, CEO, Vodafone UK
• 2022: Lutz Schüler, CEO, Virgin Media O2
• 2021: Marc Allera, CEO, EE and BT Consumer
• 2020: Nick Jeffrey, CEO, Vodafone
• 2019: Marc Allera, CEO, EE and BT Consumer
• 2018: Marc Allera, CEO, EE and BT Consumer
• 2017: David Dyson, CEO Three UK
• 2016: Sebastian James, Group CEO, Dixons Carphone
• 2015: Sebastian James, Group CEO, Dixons Carphone
• 2014: Andrew Harrison, CEO, Carphone Warehouse
• 2013: Olaf Swantee, CEO, EE
• 2012: Simon Stanford, VP of UK & Ireland telecommunications and networks division, Samsung UK
• 2011: Guy Laurence, CEO, Vodafone UK
• 2010: Tom Alexander, CEO, Everything Everywhere
• 2009: Andrew Harrison, CEO, Carphone Warehouse
• 2008: Kevin Russell, CEO, Three UK

• For more information on the Power 50, or to get more involved in the Mobile Industry Awards 2026, visit the awards site here

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