AI will not repair poor work design. It will often make poor work faster.
This theme captures a strong warning from the European Executive Roundtable. Participants recognized the potential of AI, but they also emphasized that AI should not be applied to broken processes, unclear workflows, weak data or poorly defined roles.
One comment captured this sharply: “Don’t bolt on AI on broken work, you will just get faster chaos.” This is one of the strongest statements in the data set because it challenges the assumption that AI automatically improves work. Participant notes suggest that if FM leaders apply AI to badly designed processes, they may simply accelerate confusion, inefficiency, duplication or poor decision-making.
Many organizations are experimenting with AI through pilots. This is understandable. AI is evolving quickly, and experimentation can help teams understand what is possible. However, the Roundtable data suggests that experimentation alone is not enough.
The comment that “95% of the pilots failed” points to a wider concern. AI pilots can fail when they are not connected to real business problems, when ownership is unclear, when the data is poor, when workflows are not understood, or when there is no pathway from pilot to adoption.
In FM, this risk is especially important because the work is complex. FM spans buildings, assets, people, services, suppliers, workplace experience, sustainability, risk, compliance and operational continuity. AI cannot be applied effectively unless leaders understand how work is currently done, where friction exists, what decisions matter and where human judgment remains essential.
The data also suggests that prompting should be understood as more than a technical skill. A good prompt depends on knowing the context, the desired outcome, the relevant constraints and the business logic behind the task. In this sense, prompting is part of work design. It requires clarity about what the work is meant to achieve.
FM leaders should review the work before scaling the technology. This means identifying which processes are suitable for AI support, which need redesign, and which should not be automated or augmented without further consideration.
A practical starting point is to examine workflows through a simple work design lens.
FM leaders should also avoid treating AI implementation as a series of disconnected pilots. Pilots should be designed with clear ownership, learning goals, evaluation criteria and a route to scale if successful.
A purposeful AI pilot should answer five questions:
FM leaders should also make AI capability role specific. The way a facilities director uses AI will be different from the way a maintenance planner, workplace experience manager, sustainability lead, helpdesk operator or supplier manager uses AI. Generic AI training may raise awareness, but it will not be enough to change practice.
The second theme shows that AI cannot be separated from work design. Participants warned against applying AI to broken processes and emphasized the need to understand roles, tasks, prompts, decisions and workflows before scaling AI.
The message for FM leaders is clear: do not bolt AI onto broken work. Redesign the work first, then use AI where it can improve outcomes, remove friction, support better decisions and create value.
International Facility Management Association (IFMA) supports over 26,000 members in 140 countries. Since 1980, IFMA has worked to advance the FM profession through education, events, credentialing, research, networking and knowledge-sharing.
