What 2026 will bring for AI

It's our annual post-AI House Davos trends list, and why we’re calling 2026 “The Year of AI ROI.”

We just returned from an action-packed week of discussion with AI leaders across industry, investing, and research at AI House Davos.

We couldn’t help but notice that the AI narrative has shifted a bit in Davos since we first co-founded AI House three years ago. In our first year, AI was a shiny and mysterious “new” object. Last year, it was about trying to separate the hype from the reality. This year, we’ve begun calling it the “year of AI ROI”. We heard a lot of variations of, “What can AI do for my business?” A real push for tangible, bottom line results.

That’s just one of our themes for the year. Below are 9 more. Ultimately, Merantix Capital is an investor. Our portfolio = our predictions. Nevertheless, here are a few educated guesses of what we think will shape AI in 2026.

For this post, I asked for some help from my colleague Thomas Wollmann, the CTO of Merantix Momentum, our AI solutions business.

1. Sovereignty and the European AI stack get real

The debate around European AI sovereignty is finally getting some momentum. One big topic in Davos was European Commission president Ursula von der Leyen officially endorsing the EU Inc initiative, an initiative we signed at its 2024 launch, which would institute the same capital regime across Europe and make it much easier for startups to register here, raise capital, and incentivize talent.

This should be the bare minimum, but it’s a real step in the right direction.

Meanwhile, by the end of 2026, we expect multiple European foundation models to be essentially good enough for most enterprise use cases, and for there to be a greater emphasis on European sovereign cloud providers. In that regard, we expect the narrative focus to shift away from whether Europe can (or should) build its own models, and more towards how the ecosystem actually works together, with a greater emphasis on infrastructure, deployment, public-private partnerships, and distribution.

2. Beyond (Transformer) LLMs

Three years after ChatGPT took the world by storm, we think 2026 will finally be the year where the conversation catches up with the research world and pushes past LLMs, particularly transformer LLMs.

LLMs are powerful interfaces, but their cost and weak grounding in the physical world are pushing researchers and companies to chip away and replace parts of the stack. LLMs will not go away, but state space models and flow models will play a bigger role, moving beyond transformer architecture.

And when it comes to the layperson’s understanding of AI, more people will see AI deeply implemented into their workplaces and personal lives in other modalities, shifting how they understand and talk about what AI really is

3. The Year of AI ROI

As we saw in the marketing installations along the Davos promenade, businesses are pushing to convey how AI can help the bottom line in real terms.

Enterprises are done asking if they should use AI. Now they want to know what it returns. We expect this year that more companies will be able to quantify this, measuring AI’s impact on the P&L. Earnings reports won’t just mention AI, they will quantify productivity as AI implementation becomes a board-level priority. Companies that cannot demonstrate AI ROI will stall.

4. Cybersecurity has a wake up call moment.

If 2025 was the year of “vibe coding,” 2026 is shaping up to be the year of security breaches. As AI-generated code and autonomous agents go mainstream, attackers are gaining leverage. We expect to see more scenarios where one skilled hacker (armed with AI) takes on an entire security team. Will 2026 produce “the big one?” A major AI-enabled cyberattack that forces enterprises and governments to completely rethink their assumptions around software trust, security, and resilience? We think so.

Every threat is an opportunity, which is why we back entrepreneurs with deep domain expertise in cybersecurity working to address these challenges head on.

5. AI’s job impact becomes impossible to ignore

For years, people have talked about the labor impact of AI in theory. So far, it’s been largely marginal or role-specific. Last year you started to see more storylines about how junior or entry-level white-collar work has been hollowed out, especially in knowledge work like software, consulting, or marketing.

This year, we think things will become significantly more noticeable. New junior roles in knowledge work will disappear as AI juices productivity gains in functions like customer support, sales, and content. For high-growth startups, this will mean scaling revenue without proportional hiring. For traditional businesses, it will mean layoffs or headcount freezing.

As a result, the importance of upskilling and reskilling and the future of education will become a more clear topic of discussion, as both new and existing workers in the job force look for alternative roles.

6. World models

If “beyond LLMs” is one theme, the natural follow up question is: What next?

Much of the talk at AI House, including a session with Yann LeCun, centered on embodied AI and world models. World models learn how objects move and how actions lead to consequences, making them foundational for general-purpose robotics. At the same time, world models can also power digital twins for factories, supply chains, cities, and financial systems, enabling decision making through simulation.

The next big leap will not come from words, but from machines that can imagine, simulate, and reason about the world before acting in it.

7. Death of search and and an e-commerce revolution

Consumers are increasingly asking, deciding, and buying through AI.

This may spell the slow death of the open web. But it also unlocks entirely new business models: LLM-native search, agentic commerce, and AI-first marketplaces that are not optimized for clicks.

2026 will be an inflection point. As consumer habits tip toward AI-driven shopping, the economics of the internet and who captures the value will get rewritten.

8. Constraints will drive the next wave of innovation

Constraints breed creativity. The era of “just add more GPUs” will have to end at some point.

We expect that constraints, whether they are geopolitical or financial, will turn compute into an even bigger battlefield in AI with more than just one dominant chip vendor winning via brute-force scaling.

Meanwhile a wave of innovation is expected to hit the hardware side this year. New, specialized chips will challenge the incumbents. On the software side, advances in inference optimization (compression) and efficient model design will push what’s possible with limited compute.

Doing more with less will be the name of the game, which will reshape the power dynamics and dependencies within the AI stack

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9. AI for Science breaks through

AI is a powerful scientific assistant. That’s really just the beginning. Rather than just helping analyze or generate, AI systems are starting to decide themselves what experiments to run next, creating hypotheses, simulating outcomes, and iterating autonomously. The upside here is huge: AI systems that produce new knowledge and self-improve to accelerate progress.

This will have major implications in materials science, physics, mathematics, and beyond. We anticipate at least one major scientific breakthrough this year where AI is not a footnote or an assistant, but the primary driver. This will get significant press attention, accolades, and help people understand AI’s potential in the scientific realm.

10. And the Oscar goes to AI…

AI-generated content is having an interesting moment. On the one hand, our feeds are full of “AI slop” meant to farm engagement (like videos of Friedrich Merz doing a TikTok dance). Still, some AI content is indistinguishable from human output.

Oftentimes the dam breaks in the commercial realm. Coca-Cola released holiday ads created with the help of AI, which earned the soda maker some public criticism, but was more cost efficient.

We think 2026 is the year society will start to accept that (some) AI content can be high-quality. AI interviews will appear in major newspapers. AI-assisted research will distinguish itself in conferences. AI art will break through. An AI-generated film will receive awards.

This has happened with the advent of nearly every new technology. Radio scoffed at television. Print laughed at the internet. Once the quality bar is met, the acceptance of AI generation in the entertainment realm will unlock new formats and personalization.

Looking Ahead

Once again we couldn’t be more excited to see what this year brings in AI. What are we missing? And if you’re building something that helps solve the world’s most pressing issues with AI, let us know.