AI value in FM should be measured through business, sustainability and human outcomes, not efficiency alone.
This theme captures the way participants moved beyond a narrow efficiency narrative. Efficiency was part of the discussion, but it was not enough. Participants connected AI to value creation, ESG performance, carbon impact, building optimization, space planning, job enrichment, inclusion and better business outcomes.
One of the strongest signals from the notes was the crossing out of “efficiency” and the emphasis on “value creation.” Another comment suggested that AI can “enrich jobs, lifestyle…and deliver better business outcomes.” This suggests that AI value should not be defined only by whether it makes work faster or cheaper. It should be defined by whether it creates better outcomes for organizations, people, buildings and the environment.
AI is often justified through efficiency. This is understandable because AI can automate tasks, reduce administrative effort, improve analysis, accelerate reporting and support faster decision-making. However, Roundtable data suggests that efficiency is not a sufficient measure of value.
FM leaders are responsible for outcomes that extend beyond productivity. They influence building performance, workplace experience, employee well-being, supplier performance, operational resilience, sustainability, energy use, space utilization, risk management and long-term asset value. AI should therefore be assessed against this wider value landscape.
The ESG discussion makes this especially clear. Participants saw opportunities for AI to support environmental data analytics, smart building optimization, space planning and footprint reduction. This positions AI as a practical enabler of operational sustainability. AI can help FM teams identify patterns, reduce waste, optimize resource use and connect data to action.
At the same time, participants recognized that AI has its own environmental consequences. AI tools depend on digital infrastructure, computing power, data centers, energy and water. This means AI should not be treated as automatically sustainable. Its benefits need to be weighed against its footprint.
The human dimension is equally important. Participants connected AI to job enrichment, equal opportunities, inclusion and better work. If AI simply removes tasks without improving the quality of work or strengthening opportunity, then its value may be limited. If AI removes low value activity and gives people more time for judgment, creativity, service, learning and relationships, then its value becomes more meaningful.
FM leaders should also consider creating a simple AI value scorecard before scaling major use cases.
FM leaders should work closely with sustainability, IT, real estate, finance, HR, procurement and operations teams. AI value will often sit across functions. For example, an AI use case that optimizes space may affect real estate strategy, workplace experience, carbon reporting, employee behavior and financial planning. A use case that supports energy optimization may require coordination between FM, sustainability, IT, vendors and building users.
The sixth theme shows that AI value in FM must be measurable, sustainable and human centered. Participants resisted a narrow efficiency narrative and connected AI to business value, ESG performance, carbon impact, smart buildings, space optimization, job enrichment, inclusion and better outcomes.
The message for FM leaders is to measure AI by the value it creates, not only by the speed or cost savings it produces. AI should help FM deliver better buildings, better work, better sustainability outcomes and better decisions, while also accounting for its own environmental and human consequences.
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.
