Articles on building data governance, published here and on LinkedIn. A new piece most months, collecting and extending the arguments in the book.
Predictive maintenance is a milestone, not the destination. Most FM organizations lack the data foundation and decision structures prescriptive maintenance actually requires.
Read the article →Faster systems rarely fail on the technology. They fail when ownership of outcomes stays implicit instead of being deliberately designed.
Read the article →Leadership in 2026 is not measured by decisiveness or visibility. It is measured by how well the organization keeps functioning without constant intervention.
Read the article →Smart building data is becoming an economic asset. Tokenization lets owners share defined, controlled access to it and turn a cost center into a new revenue stream.
Read the article →Quantum computing promises powerful optimization for building operations, but running it raises a real ESG question: whether the savings actually outweigh the cost.
Read the article →Quantum computing is not yet mainstream in facility management, but the groundwork organizations lay today will decide how ready they are when it arrives.
Read the article →AI is redrawing the relationship between facility owners, FM teams and occupants, from predictive maintenance to a more transparent, data-driven collaboration.
Read the article →AI is not only changing FM operations. It is reshaping what leadership itself requires, from data literacy and ethical judgment to a more agile, less hierarchical way of deciding.
Read the article →As AI grows emotionally aware, the human role in facility management does not shrink. It moves toward ethics, creativity and the kind of care no system can fully replicate.
Read the article →Privacy, bias, transparency and job displacement are not side issues in AI-driven facility management. They are the questions that decide whether the technology earns real trust.
Read the article →From narrow, task-specific systems to the theoretical reach of general and superintelligent AI, where a tool sits on that spectrum shapes what it can responsibly do inside a building.
Read the article →Generative AI can sharpen maintenance, space use and energy efficiency in FM, but only if organizations take its energy cost, accountability gaps and data risks just as seriously.
Read the article →Adoption research grounded in the UTAUT model finds one factor predicts AI adoption in facility management more than any other: not ease of use or trust, but attitude.
Read the article →Shorter observations and the ongoing conversation happen on LinkedIn most weeks. The strongest pieces are written up in full and added here roughly once a month.
If a piece here is useful in your own organization, use it. Attribution to The Acceleration Gap is appreciated, and I am always interested in hearing where the mechanism described does or does not match what you see.