82% of enterprise leaders say AI will fail without process visibility
Celonis, a global leader in Process Intelligence, a key enabler of Enterprise AI, today released new research that reveals a critical gap between enterprises’ agentic AI ambitions and their operational readiness.
Results from the 2026 Process Optimization Report (which surveyed over 1,600 global business leaders) show that most businesses are aggressively pursuing an AI-driven future – 85% of organisations want to be an “agentic enterprise” in three years. However, a large majority (76%) admit that their current processes are holding them back.
To act autonomously and effectively, AI agents need optimized, 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. And 82% of decision-makers believe AI will fail to deliver return on investment (ROI) if it doesn’t understand how the business runs.
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.
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, 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.”
To explore findings further and learn how organisations are building AI-ready operations, read the full 2026 Process Optimization Report. An executive summary and specific data sheets for leaders in IT, Supply Chain, and Finance and Shared Services are also available.
Research methodology
The research was conducted by Insight Avenue, an independent, third-party, specialist B2B and technology research consultancy. 1,649 interviews, with around 320 in each of five regions, and around 400 in each of four departments, were conducted during June and July 2025. Business leaders were interviewed from organizations with revenue of $500m+ across a range of sectors. The sample used in this report is made up as follows:
- Department: Supply Chain 25% Finance / Shared Services 25% Process / Operations 25% IT / Digital 25%
- Seniority: Board / C-level 6% VP level 11% Head of department / Director 33% Senior manager 50%
- Revenue: $500m – $2bn 15% $2bn – $10bn 80% More than $10bn 5%
- Industry Sector: Manufacturing 18% Banking 15% Automotive 13% Tech / Software 11% Retail 9% Energy / Oil and gas 8% CPG / FMCG 5% Healthcare 4% Logistics 4% Insurance 4% Pharma / Life sciences 3% Public sector 3% Utilities 2% Telco 2%
- Region: APAC (Australia, Japan, South Korea) 20% DACH (Austria, Germany, Switzerland) 20% Europe (France, Spain, UK) 20% India 20% US 20%
- Country: Australia 9% Austria 2% France 6% Germany 12% India 20% Japan 6% South Korea 6% Spain 4% Switzerland 5% UK 10% US 20%