What does 2026 mean for facilities management (FM)?

Facilities leaders are walking into 2026 with the same old pressures… and a couple of new ones that are quietly more dangerous. Assets are ageing, budgets are becoming increasingly stubborn (if not reduced), hybrid is now “normal” for those responsible for workplaces, and AI has moved from hype to expectation.

What changes this year isn’t that the challenges are new. It’s that the gap between teams who run FM as a data-led operating system… and teams who run it as heroic problem-solving… is about to get painfully obvious.

Having gone through research for a bigger study that Cleverly will shortly be releasing, here are the five shifts that matter most … plus what I’d actually do about them.

1) The “FM Data Analyst” stops being a nice-to-have and becomes the hinge role

Most FM teams already have data. The uncomfortable bit is that a lot of it is … vibes. It’s scattered across email threads, spreadsheets, engineers' notes, photos, “it’s in someone’s head”, and systems that don’t agree with each other.

So the question isn’t “do we have data?” It’s “do we have data we trust enough to put money on?”

What’s really driving this

• The CFO now expects FM to explain performance like any other function.

• Asset strategy is getting challenged harder: “Show me the evidence.”

• AI and automation don’t work on wisdom sitting in someone's head … they work on structured, consistent records.

The move

• Pick a small KPI set you can defend in front of Finance (not 40 vanity metrics).

• Decide what your system of record is … then treat everything else as a feeder, not a competitor.

• Upskill the curious people already in your team. The best analysts are often hiding in plain sight.

A practical starting point (this week)

• Standardise work order categories and close codes across sites.

• Make “complete the fields” the definition of done… not “job finished”.

2) AI won’t be the differentiator… data readiness will

A lot of organisations are “doing AI”. Fewer are getting outcomes. I hve cited before MIT's study about 95% of AI pilot projects failing (and shared my caveats with this data and the conclusions usually drawn). The pattern is predictable: if your workflows are standardised and your data is clean, AI becomes useful fast. If not, it becomes theatre … pilots, demos, and very expensive “learning”.

And here’s the brutal truth: AI magnifies your operational reality. It doesn’t replace it.

What’s really driving this

• AI is only as good as the data it can rely on.

• Executives are shifting from “isn’t this cool?” to “what did it actually change?”

• The early adopters are starting to show measurable wins (downtime reduction, cost optimisation, energy savings).

The move

• Start with use cases where the input data already exists and the outcome is measurable.

• Map dependencies before you build anything (data, integrations, workflow steps, owners).

• Treat AI as an operations programme … not an IT experiment.

Low-risk use cases that tend to work first

• Auto-triage and routing of requests

• Drafting compliant job notes and customer updates

• Spotting repeat faults and likely root causes (when your close codes aren’t chaos)

3) Portfolio right-sizing becomes real … and FM is suddenly in the room

Spend efficiency is real in 2026 and real estate is often a large line item on companies' expenses. For those focused within workplaces, hybrid hasn’t just changed where people work. It’s changed what “value” means for a building. Some sites are quietly turning into underused cost centres. Others are critical, high-performing, and worth investing in.

Real estate leaders need truth … not opinions. And FM often holds the only usable operational truth about condition, backlog, energy, utilisation patterns, and risk.

What’s really driving this

• Occupancy is uneven, so blunt averages lie.

• Leadership wants site-by-site clarity: cost, condition, risk, performance.

• More selective investment strategies mean weak buildings get exposed.

The move

• Build a comparable “building scorecard” across your estate.

• Stop reporting activity… start reporting trade-offs.

• Translate FM into board language: risk, cost, continuity, carbon, experience.

What to benchmark across sites

• Occupancy and utilisation patterns (peak days matter more than averages)

• Reactive vs planned mix

• Maintenance backlog and compliance risk

• Energy intensity and trendline

• Condition and criticality of key assets

4) Maintenance data becomes the backbone of capital planning

Capital planning has always suffered from a credibility gap. Too often it’s “we think it’s failing soon”, delivered with a slightly panicked spreadsheet.

But when maintenance histories are consistent, they become evidence… and evidence gets funded faster.

What’s really driving this

• Leaders want documented proof, not intuition.

• Maintenance data shows patterns a one-time inspection can miss.

• A data-backed capex request is harder to argue with (and easier to approve).

The move

• Treat asset data quality as a capex accelerator.

• Standardise condition, failure types, and cost capture.

• Align with finance on a shared scoring model: condition + criticality + risk.

Quick wins

• Make sure critical equipment has complete histories (not perfect… complete).

• Improve work order documentation so trends are visible without detective work.

• Create a simple “renew vs maintain vs run-to-fail” rubric that everyone understands.

5) The service experience becomes the product … and “unplanned downtime” gets treated like a revenue leak

If you run FM for bars/restaurants, care homes, or manufacturing, the workplace conversation is a distraction. Your buildings aren’t “places to collaborate”… they’re environments that directly shape revenue, safety, and outcomes.

A broken cold store on a Friday night, a boiler issue in a care home, a compressed air leak on a production line … that’s not “a maintenance job”. It’s a commercial and reputational incident with a clock on it.

What’s really driving this

• The customer or resident experiences the building as part of the service. Comfort, hygiene, temperature, odour, noise, uptime … it all lands on brand.

• Regulatory scrutiny is tighter and more visible. In care settings especially, “paper compliance” isn’t enough if reality doesn’t match.

• Supply chains and staffing are fragile. When you lose resilience, you need predictability. That pushes you toward planned maintenance, clearer triage, and faster escalation.

The move

• Run FM like an operations control tower, not a ticket desk. You need real-time visibility of what’s down, what’s at risk next, and what needs escalation now.

• Define “critical assets” by service impact, not asset category. A small extract fan in a kitchen can be more critical than a big plant item… if it shuts you down.

• Make response SLAs reflect reality. You don’t need “gold” response times everywhere… you need ruthless prioritisation for the assets that affect revenue, safety, or resident wellbeing.

• Close the loop with root cause. Repeat failures are a management problem, not an engineer problem. Track recurrence, supplier performance, and time-to-return-to-service.

3 practical KPIs that actually work in these environments

1. Time to restore service (not time to attend)

2. Repeat-fault rate by site and asset (30/60/90 days)

3. Compliance exception rate (missed checks, overdue PPM, failed inspections with open actions)

Quick win (low effort, high return) Create a simple “service impact” field on every job: Revenue risk / Safety risk / Resident wellbeing / Reputation / Normal Then use it to drive routing, escalation, and reporting. Within a month you’ll have a clearer picture of where you’re vulnerable… and where you’re overspending on non-critical noise.

What this means for 2026

There’s one theme underneath all five shifts: FM is becoming more accountable … and more strategic … at the same time.

If you invest in accurate data, integrated workflows, and cross-functional trust, you get compounding returns:

• faster decisions

• better capex outcomes

• fewer surprises

• stronger service experience

• and yes… AI that actually does something

If you do only three things this quarter

1. Standardise how work is logged and closed (because everything builds on this)

2. Build a building scorecard that Finance can understand

3. Choose one AI use case with a measurable outcome and clean inputs … then ship it

#facilitiesmanagement #fm #cafm #cmms #workingcleverly