What’s Next for AI? Key Trends to Watch in 2026

There’s no doubt that artificial Intelligence stole the spotlight in 2025, with one of the fastest paces of innovation we’ve seen in tech. Organizations moved from AI hype to measurable impact. It was also a year of big AI leaps: partnerships, breakthroughs, and even key initiatives, such as Mexico launching the largest public AI school in Latin America.

With AI reducing the distance between imagination and execution, and boosting productivity across industries, it’s no longer just a tech story, but an enterprise story. That is why we have shared monthly thoughts on AI in IT automation, cybersecurity, open source, and more. Now is the time to gather these learnings and information and look ahead at how AI will fold into enterprise technology. 

Let’s review the AI trends that are going to matter in 2026, according to IBM experts:

Agents

2026 will be the year of operating AI agents at scale. 

Enterprises will run dozens or even hundreds of agents in production, built by multiple teams across various platforms and executing in diverse environments. As this happens, the focus will shift heavily toward observability, evaluation, and optimization of agentic workflows, along with strong policy enforcement to manage and govern increasingly autonomous agent behavior. 

Infrastructure

The era of generic infrastructure for AI will come to an end in 2026.

With more organizations integrating AI inference into their daily work, details such as latency, cost, and reliability will become more critical. Therefore, the future lies in specialized and co-created AI infrastructure: hardware and software designed together for specific use cases. The future of AI is not just about smarter algorithms, but also about smarter infrastructures. Those who build them will define the next decade of AI-driven business.

Security

"Shadow: agents will accelerate the exposure of data faster than it can be detected.

As more autonomous AI agents operate in businesses, they access sensitive data with minimal human oversight. These agents can replicate and evolve without leaving clear records for auditing, they do not fit into traditional security frameworks, and they operate at a speed that exceeds conventional monitoring. This creates a new exposure problem: companies will know that their data was exposed, but they won't know which agents moved it, where it went, or why. Systems that can track data access by agents and interactions between machines will be essential.

ROI

By 2026, AI will help companies to differentiate themselves and stand out from competition.

After years of experimentation, the test for companies is how to get AI to deliver measurable results. The competitive advantage will belong to those who treat AI as a strategic discipline woven into every part of the company, those who combine technological excellence with human knowledge, going beyond passive adoption toward active innovation. Those who will set the pace for what's to come are those who train their teams, put AI creation in the hands of their people, and enable them to combine data-driven intelligence with judgment, empathy, and imagination.

Ecosystem

By 2026, companies will standardize how they orchestrate AI agents.

Companies will move from incorporating AI functions into existing tools to building ecosystems where agents interact across multiple platforms, deepening alliances between AI model providers, cloud infrastructure companies, and enterprise software providers. Alignment around open and interoperable standards will lay the foundation for agentic AI to truly scale in enterprises.

In 2026, AI will continue to evolve, but as we move closer, one thing is clear: AI isn’t slowing down, and neither should we. Progress happens fastest when people and technology work together. So, here’s to a year of building smarter, working better, and imagining bigger. The next chapter of AI is already unfolding, and we all have a part in writing it.