2025 was the year of AI acceptance and experimentation led by hype cycles and increased expectations. In 2026, we will see the AI landscape settle into a new phase of transformation as business leaders consider tougher questions around ROI delivery, ecosystem control, and autonomy. Leaders will no longer simply deploy AI, they will design for it. And we’ll see some recurring themes related to that deep integration of AI across enterprises and industries in the new year – from commoditization, to ROI, to agentic AI, to autonomous intelligence.
The Foundation Model Market Will See Commoditization
In 2026, foundation models will continue their march toward commoditization as the market matures. There will be a focus shift from the release of the latest generative model to who is using these models most effectively. The gap between the top players will shrink, and differentiation will increasingly come from application, integration, and infrastructure.
There will also be greater emphasis on scaling infrastructure and building distribution channels. OpenAI, as an independent, will continue to diversify, turning assets into hard tangibles such as data center bricks and chips. Open-source players like DeepSeek and Qwen will gain further momentum, offering credible alternatives in global markets, particularly in regions seeking technological independence from U.S.-based providers.
Tech giants like Google, on the other hand, will use their advantage across their vertical stacks, using everything from bare metal to massive interaction channels to outmaneuver competitors, and aim to counter commoditization by moving into the application layers. Already in the first weeks of January, Google announced deep AI integration into Gmail, partnered with retailers such as Walmart, Shopify and Etsy to change the way we shop within Gemini, and announced a partnership with Apple for Gemini to power Apple Intelligence.
AI ROI Will Be Under the Microscope
2026 will be the year enterprises get serious about value. The backlash that began in late 2025, centered on a perceived lack of ROI from GenAI pilots, will intensify before it stabilizes. Many organizations will come to terms with the hard truth: value from AI isn’t instant. It comes from long, methodical transformation.
The most successful AI programs in 2026 will be the ones delivering transformative results where technology is woven into processes to improve service outcomes and operational efficiency. This does not involve just piloting lab projects, but rather 12–18-month programs for full-scale rollout and adoption.
While quick wins will still exist, executives will demand clearer paths to scale, sustainability, and accountability. Vendors will be forced to connect their tech to measurable business outcomes or otherwise find themselves falling by the wayside.
Agentic AI Will Begin to Prove Its Worth, Carefully
The money and action in 2026 will appear in the application layer, where AI is applied and value is either created or lost. This is where AI gets embedded into the often-unglamorous reality of business strategy, enterprise architecture, and workflows. Enter: the ‘advent’ of agentic AI. These are systems designed to take action, complete tasks, and operate semi-independently. But after early overpromises, 2026 will be the year of controlled ambition in agent design.
Despite rapid development, in state-of-the-art agentic benchmarks, most agent systems still fail at least half their tasks. This won’t change overnight. Instead, it becomes crucial to focus on the right half of the tasks: some are simply too hard, and others are better solved by non-agentic AI or business processes.
The most successful agent deployments in 2026 will need to be robust, predictable, and reliable. They will operate within clearly scoped workflows, using defined data, and collaborating with humans. Transparency and explainability will become critical, as AI moves from labs into regulated industries and sensitive systems. Companies will invest in automated evaluation benchmarks to add more science into agent development.
Also, as AI assisted coding has grown substantially in 2025, such design time use of agentic AI will also make its way into low code, freeing up budget and resource for innovation by transforming legacy into modern AI-driven apps.
The Push Toward Autonomous Intelligence Will Begin Cautiously
Agentic systems are just the beginning. In 2026, we will see the first serious efforts to move from reactive AI to systems with true autonomy where AI can learn continuously, act with purpose, and respond to dynamic environments.
Agentic systems must actively acquire the right data, perform goal and intrinsic motivation-based reasoning, form long-term memories, and continuously learn from feedback to adapt to dynamic conditions. These systems will interact with humans and other agents, coordinate tasks, negotiate conflicts, and adapt in real-time.
But do not expect “artificial general intelligence” in 2026, nor is it required to make good and responsible use of AI. Instead, expect to see controlled experiments in narrow domains like supply chain, operations, and customer service, where autonomy can be governed, controlled, and monitored.
Bottom Line: 2026 Will Be the Year AI Grows Up
AI in 2026 will move beyond shiny demos to make meaningful progress. The market will mature, and the hype will settle as serious players focus on infrastructure, value delivery, and responsible autonomy. Commoditization will reshape the model landscape, and the pressure to see true ROI will clarify what matters. And agentic systems will begin their long evolution toward something smarter, more useful and more autonomous than what came before.
