Celonis research reveals AI ambitions facing significant operational barriers
New Celonis research released today reveals a critical gap between enterprises’ agentic AI ambitions and their operational readiness with 85% of organisations wanting to be an agentic enterprise in three years but 76% admitting that their current processes are holding them back.
Additionally, the vast majority of decision makers (82%) believe AI will fail to deliver return on investment (ROI) if it doesn’t understand how the business runs.
The findings are in Celonis’ annual 2026 Optimisation Report which surveyed 1,649 business leaders around the globe across four sectors – Supply Chain, Finance, Operations and IT.
Celonis, a global leader in Process Intelligence, a key enabler of Enterprise AI, said to act autonomously and effectively, AI agents need optimised, AI-ready processes and the process data and operational context that only comes from process intelligence. Without both, AI agents can’t understand how a business actually runs or know how to improve it.
Additional key findings from the report include:
- Ambition is high: 90% of organisations are already using or exploring multi-agent systems to automate complex decision-making.
- Expertise and context are top hurdles: The top 2 barriers to adoption: internal expertise (47%), difficulty of getting AI to understand business context (45%).
- Silos block effective AI deployment: 58% of process and operations leaders report that their departments still do not operate seamlessly together, preventing the end-to-end visibility required for effective Enterprise AI.
- Competitive urgency: 89% of leaders view AI as their single biggest opportunity to compete in the market.
Celonis says that to bridge the gap between ambition and reality, organisations must move beyond isolated automation. The findings suggest that for AI to navigate the complex reality of the business rather than just execute isolated, simple tasks it must be grounded in Process Intelligence. This provides the “common language” that allows AI agents to understand how work flows across departments and systems, identify friction points, and execute actions that drive genuine business outcomes.
“While business leaders are leaning boldly into an agentic AI future, the reality is that many are struggling to translate that ambition into tangible ROI right now,” said Carsten Thoma (pictured), President and Board Director at Celonis.
“For AI to truly work for the enterprise, it needs more than just data. It needs operational context. By using Process Intelligence to give AI a shared understanding of how a business actually runs and how to improve it, we’re finally turning that ambition into continuous, measurable value.”
The survey interviewed leaders from around the globe made up of 20% APAC, 20% DACH, 20% Europe, 20% India and 20% the US. 80% of companies had revenue between $2 billion and $10 billion. The leaders ran companies across nearly 20 sectors with manufacturing making up 18%, banking 15%, automotive 13% and tech/software 11%.
