2026 tipped as turning point for enterprise agentic AI

Technology executives expect 2026 to mark a shift from small-scale artificial intelligence pilots to broader deployment of "agentic" systems, as enterprises seek measurable returns from recent investments.

Senior leaders from language AI firm DeepL and process automation company Camunda predict that next year will see agent-based systems move from experimentation into mainstream business workflows, with a focus on orchestration, governance and outcome-focused metrics.

Enterprise focus

Sebastian Enderlein, Chief Technology Officer at DeepL, said many organisations are now past early-stage proofs of concept and are preparing to deploy AI systems at scale.

"I believe 2026 will be the year AI stops experimenting and starts executing, at a scale we haven't yet seen. After a cycle of pilots and proofs of concept, businesses are now ready to scale and they're betting big on agentic AI to do it," said Enderlein.

Enderlein said that while consumer-facing AI tools for video and image generation will continue to attract attention, he expects the more consequential changes to happen inside companies.

"For consumers, the "wow effect" of AI will continue to grow - especially in video and image generation - as tools become more fluent, expressive, and embedded in daily life. But beyond the spectacle, the real transformation will happen inside organizations. These systems are starting to reliably handle repetitive, knowledge-based tasks at scale, freeing many up to focus on higher-impact, creative problem-solving," said Enderlein.

He also expects commercial models to change as corporate buyers demand clearer links to productivity and business outcomes.

"At the same time, the business side of AI will mature. Vendors will stabilize, monetization models will evolve from usage-based to outcome-driven, and productivity - not novelty - will become the new benchmark," said Enderlein.

Rise of agents

DeepL's Chief Scientist, Stefan Miedzianowski, said he expects agent-based AI systems to progress along the technology adoption curve within large organisations.

"2026 will undoubtedly be the year of the agent. 2025 was the year where public awareness caught up with the science showing what agents can do, but enterprise adoption at scale will happen in the new year. We will be moving from the innovators on the technology adoption curve to the early majority," said Miedzianowski.

Miedzianowski said his discussions with customers indicate that businesses are planning to embed virtual "coworkers" more deeply into operations and decision-making processes, while changing how technology choices are made within enterprises.

"As we look ahead to 2026, the role of agentic AI in business is expected to become even more pronounced. We see from conversations with our customers that their organizations will increasingly rely on virtual coworkers to streamline operations and enhance decision-making processes. Perhaps more importantly, we will also see a shift in how AI solutions are selected by organizations. There will be a more collaborative approach, with each team selecting the tools that are most suited to their requirements, requesting IT support once they've been able to test the solution," said Miedzianowski.

He expects that as more organisations demonstrate benefits, adoption will spread across sectors and functions.

"This widespread integration will lead to more efficient workflows, enabling teams to focus on strategic initiatives rather than routine tasks and free their time to focus on complex topics. As early adopters continue to demonstrate the value of these technologies, we anticipate a ripple effect, encouraging broader acceptance across industries. Ultimately, agentic AI will play a crucial role in driving innovation and improving overall business outcomes in the coming years," said Miedzianowski.

Multi-agent control

Daniel Meyer, Chief Technology Officer at Camunda, said many organisations are now dealing with multiple AI agents and tools that need to be coordinated if they are to deliver consistent value.

He expects "multi-agent orchestration" to become a priority as enterprises look to combine different systems while maintaining governance and accountability frameworks.

According to Meyer, the focus is shifting from the power of any single agent to how different agents can work together, delegate tasks and react in real time, without losing operational visibility. He said this orchestration could help organisations improve both efficiency and customer experience.

Agentic automation

Jakob Freund, CEO and Co-Founder of Camunda, said many early agentic AI efforts have struggled to move beyond narrow pilots because of risk, governance and integration challenges. He expects "enterprise agentic automation" to be used to structure deployments in larger, more complex environments.

Freund said combining AI agents with defined policies, guardrails and human checkpoints can enable companies to automate more complex or exception-heavy activities while maintaining control over decisions and outputs.

He said this approach is designed to coordinate agents, human workers and existing systems across end-to-end processes. Role-based permissions and human oversight are expected to be key elements as organisations seek to balance autonomy and control, while responding to pressure to demonstrate return on AI spending.

Freund said that as enterprises adopt these controls and orchestration mechanisms, they aim to reduce risk and technical debt while pursuing measurable financial and operational outcomes.