Most companies are rushing to adopt Artificial Intelligence (AI), but 85% of enterprises aim for “agentic AI” within three years while 76% acknowledge their current operations can’t support it. A new Celonis report reveals a critical gap: while the ambition for AI-driven transformation is high, the foundational work of modernizing workflows and building operational resilience remains largely unfinished. This isn’t just a technical challenge; it’s a fundamental mismatch between aspiration and infrastructure.
The AI ROI Problem: Context is King
To function effectively, AI agents require optimized processes and clear operational context. Without that, AI is essentially guessing, and 82% of decision-makers believe AI will fail to deliver return on investment (ROI) if it doesn’t understand how the business actually runs. The focus has shifted from whether AI works to why it isn’t working as expected. The root cause is structural: siloed teams, disconnected systems, and AI that performs well in demos but falters in real-world deployment.
Only 19% of organizations use multi-agent systems today, highlighting the operational readiness problem. Companies have long tolerated messy, inefficient processes because growth masked the underlying issues. AI changes that calculus; sub-optimal processes now actively block AI strategy.
The Missing Link: Operational Visibility
AI needs business context to maximize ROI. This includes understanding how key performance indicators (KPIs) are defined, internal policies, organizational structure, and decision-making authority. This knowledge is often trapped in departmental silos with incompatible systems. Introducing AI into this environment is like dropping someone into a years-long conversation without any background.
Process intelligence provides the connective layer — a shared operational language that grounds AI decisions in reality. It’s not just about tools; it’s about creating a common understanding across the organization.
Change Management: The Real Hurdle
The AI adoption challenge isn’t primarily technical; it’s a change-management and operating-model problem. While only 6% of leaders cite resistance to change, the real blockers are siloed teams (54% ) and lack of interdepartmental coordination (44% ). 93% of process and operations leaders agree that optimization requires as much cultural shift as technological investment.
Bolting AI onto broken processes won’t work. True modernization means redesigning how teams, systems, and decisions connect. AI only delivers when this foundational work is done first.
Strategic Advantage: Connecting Processes to Outcomes
Process optimization becomes a strategic advantage when directly linked to executive-level concerns. 63% of leaders use it to proactively manage risks, while 58% report faster decision-making. In a volatile environment, agility is crucial, as evidenced by 66% of the supply chain industry already viewing process optimization as a business-wide imperative.
Closing the Gap: Visibility First
To succeed with agentic AI, organizations must be honest about their current state and close the readiness gap. The biggest risk is layering AI onto fragmented processes and expecting results. The shift must be from static tools to real-time process intelligence, providing live visibility into operations. Without it, AI agents will be misdeployed, unable to integrate with existing systems, and ROI will remain elusive.
The leaders who will thrive aren’t necessarily those with the most advanced AI; they’re those who have invested in a clear, accurate picture of their operations. Master your processes, provide AI the necessary context, and then you can deploy it effectively.
