A new survey from Celonis highlights a disconnect between corporate AI goals and operational readiness, with 85% aiming for an agentic enterprise but facing process and skills barriers, emphasising the need for better process understanding.
Celonis’ latest survey of senior business leaders portrays a pronounced mismatch between corporate ambitions for autonomous, agent-driven AI and the operational foundations firms say they lack to make it work.
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he announcement, 85% of organisations want to become an “agentic enterprise” within three years, yet 76% of respondents acknowledged that existing processes are preventing progress. The research, the company said, found that 82% of decision-makers believe AI will not deliver a return on investment unless it gains a meaningful understanding of how the business actually operates. The study also reported widespread interest in multi‑agent systems, with 90% of organisations already using or exploring them to automate complex decision-making.
Respondents pointed to skills and contextual understanding as the principal barriers: internal expertise was cited by 47% and difficulty getting AI to grasp business context by 45%. More than half of process and operations leaders, 58%, reported that functional silos persist across their organisations, limiting the end‑to‑end visibility that proponents argue is required for effective enterprise AI. The announcement added that 89% of leaders see AI as their chief competitive opportunity.
The company said these findings were drawn from 1,649 interviews conducted in June and July 2025 with business leaders at firms with revenues of $500m or more across regions including the US, India, DACH and Europe. The sample spanned supply chain, finance and shared services, process and operations, and IT functions.
Celonis framed Process Intelligence as the missing link that can provide the operational context AI agents need. “For AI to truly work for the enterprise, it needs more than just data, it needs operational context,” Carsten Thoma, President and Board Director at Celonis, said in the statement. He added that Process Intelligence can give AI “a shared understanding of how a business actually runs and how to improve it,” enabling continuous measurable value, the company said.
Other material supplied by the firm’s related summaries reinforces several of these themes while emphasising different angles. A prior edition of the Process Optimization Report highlighted that a large majority of leaders planned near‑term AI deployment to enhance processes and that many regard process understanding as critical to AI success. Separate executive summaries focused on specific functions reported equally strong enthusiasm: finance leaders were said to view AI as their principal source of competitive advantage, and supply chain leaders were reported to be especially intent on becoming agentic within the three‑year horizon. An IT summary noted that while IT teams often have advanced AI skills, the wider organisation is not always keeping pace.
The company’s broader reporting also underlined how widespread concern about process shortfalls has become. One summary stated that nearly three quarters of leaders feared process weaknesses would hamper AI over the next two years and that virtually all senior leaders saw process optimisation as essential to meeting business goals.
The research places operational readiness at the centre of the debate over enterprise AI: firms signalling ambitious, multi‑agent road maps also admit that a lack of coherent process data, organisational alignment and in‑house expertise could blunt returns. The company argued that addressing those gaps requires cross‑functional visibility and tools that map work flows and context so that autonomous agents can make informed, business‑relevant decisions.
The announcement and its companion materials stop short of independent validation of the causal link between Process Intelligence adoption and improved AI ROI, and the company’s framing presents Process Intelligence as the primary remedy. The survey results nonetheless add to a growing chorus of industry literature that flags process quality and organisational integration as critical determinants of whether advanced AI initiatives translate into measurable business outcomes.
Source: Noah Wire Services
