Why enterprises are still struggling to get real ROI from AI

Despite billions being poured into Artificial Intelligence (AI) globally, most enterprises are still stuck at the experimentation stage. AI pilots are everywhere, from copilots drafting emails to chatbots automating customer support, but meaningful operational transformation remains elusive.

That, according to leadership at Celonis, is because enterprises are missing a critical layer: process intelligence.

“AI has not delivered fully on its promise at the operational level because AI does not understand how a business really works,” said Malhar Kamdar, Chief Growth Officer at Celonis, during an interaction with Business Today. “The business context it needs to operate is scattered across systems, departments and people. Those operational blind spots are preventing AI from becoming truly enterprise-scale.”

The Germany-headquartered company, known for pioneering process mining, is betting that the next phase of enterprise AI will be less about standalone AI tools and more about building operational visibility across organisations. Its latest push revolves around what it calls a “context model”, a real-time digital twin of enterprise operations that can help AI systems understand workflows, bottlenecks and dependencies across departments and software systems.

The challenge, Celonis executives argue, is that enterprises rushed into GenAI adoption without first fixing fragmented workflows and legacy operational structures.

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“Today, 95% of companies are doing something with AI, but most of it remains at the productivity layer — writing emails, summarising documents, making small tasks easier,” Kamdar said. “But truly transforming supply chains, finance operations or enterprise workflows requires AI to understand operational context.”

That gap between AI enthusiasm and business outcomes is increasingly becoming a boardroom concern. Across industries, CIOs are under pressure to justify AI spending amid limited measurable returns. Dilipkumar Khandelwal, who previously served as CIO at Deutsche Bank before joining Celonis as Chief Customer Officer, believes enterprises are now moving from “AI experimentation” to “return on AI.”

“There are a lot of enterprises investing in AI, but the biggest question remains: can you quantify the value creation?” he said. “Process intelligence provides an X-ray of how a business runs. Once you can identify inefficiencies, automate workflows and deploy AI agents with the right context, ROI becomes measurable.”

Celonis claims its global customers have generated over $25 billion in value creation through process intelligence deployments, with more than $10 billion already quantified by customers themselves.

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The company sees India emerging as a major enterprise AI market, driven by the country’s large GCC ecosystem, digitally native startups and younger workforce. Celonis now treats India as a separate strategic market alongside North America and Europe and has nearly doubled its India headcount over the past year.

Kamdar believes India may also have an advantage over mature Western markets.

“India has the opportunity to leapfrog directly into AI-driven operations,” he said. “In many Western enterprises, legacy systems create inertia. Indian companies are showing a much faster willingness to adopt AI-led transformation.”

Yet even in India, enterprises are discovering that AI alone cannot solve broken processes.

“The future enterprise will be AI-driven and composable,” Kamdar added. “But AI cannot operate in isolation. It has to work with existing systems, workflows and human decision-making. AI is a force multiplier for humans, not a replacement.”