Rise of Gig Workforce and Need for Digitalisation

There is a slow, uncomfortable shift happening in building operations that very few people like to talk about openly. It doesn’t show up in glossy brochures or vendor demos. It doesn’t trigger alarms in control rooms. But it is already shaping how buildings are run – and how they will struggle to be run in the years ahead.

The specialists are fading away.

Not dramatically. Not all at once. But steadily, predictably, and almost invisibly.

In my limited time in this industry, I have seen quite a few already. Every year, I meet fewer engineers who truly know a building end-to-end. Fewer people who can listen to a chiller and tell you something is off. Fewer operators who understand why a system was configured a certain way fifteen years ago – and what will break if you change it casually. And every year, I meet more people who are managing buildings with partial context, temporary contracts, and fragmented responsibility.

This is not a skills crisis in the traditional sense. It’s a structural shift in how work itself is organised.

The era of long-tenured, deeply embedded building specialists is quietly ending. In its place is a far more fluid, gig-oriented, outsourced, rotational workforce – one that brings flexibility and scale, but not continuity. And unless buildings themselves change how they capture, retain, and operationalise knowledge, we are heading toward a slow-motion operational doomsday.

How We Got Here (And Why It Was Inevitable)

For decades, building operations relied on a simple but fragile assumption: people would stay.

Operators joined early. They learned the quirks. They absorbed tribal knowledge. They became walking manuals for systems that were poorly documented and rarely updated. The building lived in their heads as much as it lived in drawings or control logic.

That model worked when careers were linear, loyalty was rewarded, and buildings changed slowly.

None of those conditions exists anymore.

Today’s workforce optimises for mobility, optionality, and balance. Younger engineers don’t expect to spend twenty years in one plant room. Specialist skills are increasingly project-based. Outsourcing is no longer an exception – it’s the default. Even critical operations are split across vendors, AMCs, FM partners, and subcontractors who rotate in and out.

At the same time, buildings have become more complex than ever. More systems. More sensors. More compliance. More expectations. The paradox is stark: just as buildings demand deeper understanding, the people with that understanding are becoming rarer and more transient.

This isn’t a judgment. It’s a reality.

The Gig Workforce Is Not the Problem – The Way Buildings Depend on People Is

It’s tempting to frame this as a talent problem. It isn’t.

Gig workers, contractors, and rotating specialists are not inferior. In many cases, they are highly skilled, efficient, and outcome-focused. The problem arises when buildings expect them to behave like long-tenured custodians of institutional memory.

A gig worker arrives to fix a problem, not to inherit a building’s history. They are optimised for speed, scope, and closure – not for slow contextual learning. When systems are opaque, documentation is outdated, and insights are buried in someone else’s experience, the result is predictable: reactive fixes, conservative decisions, and minimal optimisation.

The building survives. It does not improve.

And this is where the real risk begins to compound.

The Coming Operational Doomsday (It Won’t Look Like a Crisis)

The most dangerous thing about this shift is that it won’t fail loudly.

There will be no single outage that signals disaster. No dramatic collapse. Instead, there will be a gradual erosion of operational quality. Energy inefficiencies that no one quite understands. Comfort complaints are treated symptomatically. Maintenance that becomes increasingly defensive. ESG reporting that relies more on estimates than evidence.

Buildings will continue to function – but at a higher cost, with lower confidence, and increasing dependency on external intervention.

This is what operational fragility looks like in the modern era: systems that technically work, but cannot explain themselves, adapt themselves, or improve themselves without human memory filling the gaps.

And that model simply does not scale in a gig-driven world.

Why Digitisation Is No Longer About Efficiency – It’s About Survival

Digitisation in building operations has often been sold as a nice-to-have. Dashboards. Analytics. Reports. Visibility. Those benefits matter – but they are no longer the primary reason digitisation is essential.

The real reason is knowledge continuity.

In a world where people move constantly, buildings must become the stable holders of their own intelligence. They must capture what was learned yesterday, make it available today, and use it to inform tomorrow – without depending on who happens to be on shift.

Digitisation, done properly, turns buildings into living systems of record. Not just for data, but for decisions, context, and behaviour.

A digitised operation remembers:

• What “normal” actually looks like for this building
• How assets have behaved over time
• Which interventions worked and which didn’t
• How usage patterns change across seasons and tenants

That memory doesn’t resign, retire, or get reassigned.

From Human-Centric Operations to System-Centric Intelligence

This is the uncomfortable transition many organisations are now facing. For years, operations were human-centric. Systems supported people. Knowledge lived with individuals. Processes were flexible because people compensated for gaps.

In the emerging model, systems must support people who cannot afford to learn everything from scratch.

Digitised platforms don’t replace human judgement – they scaffold it. They give gig workers, new operators, and external specialists immediate context. They reduce the time it takes to be effective. They prevent repeated mistakes. They ensure that learning compounds rather than resets.

Without this shift, every personnel change becomes a soft reset of operational maturity.

Why AI Changes the Equation Entirely

Digitisation alone is not enough. Static digitisation still assumes someone is interpreting what they see.

AI changes the role of systems from passive record-keepers to active participants in operations.

AI doesn’t just store data – it understands patterns. It learns what matters. It flags anomalies in context. It prioritises actions. It explains why something is happening and what is likely to happen next.

In a gig-driven workforce, this is transformative.

A rotating technician doesn’t need to know everything about the building’s past. The system can surface what’s relevant now. A new operator doesn’t need months to understand baseline behaviour. The platform already knows it. A portfolio manager doesn’t need bespoke reports from each site. The intelligence is standardised, comparable, and current.

AI becomes the continuity layer that people can no longer be.

The False Comfort of “We’ll Train Them”

One of the most common responses I hear to this shift is, “We’ll just train better.”

Training is necessary. It is not sufficient.

Training assumes stability. It assumes time. It assumes retention. In a gig-heavy environment, training often becomes repetitive, expensive, and quickly outdated. Worse, it places the burden of system understanding back on individuals rather than embedding it where it belongs – in the platform itself.

Digitised, AI-assisted operations reduce the cognitive load required to run complex systems. They allow people to focus on judgement and execution rather than reconstruction and guesswork.

That is the only sustainable model when specialists are no longer guaranteed to stay.

Business Continuity Is Now an Intelligence Problem

Traditionally, business continuity in buildings meant redundancy: backup power, spare parts, fail-safe modes.

Those things still matter. But the bigger continuity risk today is loss of understanding.

When systems are complex and undocumented, when decisions are implicit rather than explicit, when performance depends on memory rather than insight, continuity becomes fragile. The building works – until it doesn’t – and no one is quite sure why.

Digitisation and AI create continuity at the cognitive level. They ensure that understanding persists even as people change. They turn buildings from brittle machines into resilient systems.

What This Means for Owners and Operators

For owners, this shift reframes risk. The question is no longer just whether assets are maintained, but whether the building can sustain performance independent of who is running it at any given moment.

For operators, it reframes control. The goal is no longer to know everything personally, but to work with systems that already know – and can explain – what matters.

For both, it reframes investment. Spending on digitisation is no longer about marginal efficiency gains. It is about preserving operational capability in a world where human continuity is no longer guaranteed.

The Buildings That Will Cope – and the Ones That Won’t

The buildings that will struggle are not the oldest ones. They are the ones that rely most heavily on unspoken knowledge, manual interpretation, and heroic individuals.

The buildings that will cope – and eventually thrive – are the ones that treat intelligence as an asset in its own right. Ones that capture learning digitally. Ones that allow AI to shoulder cognitive load. Ones that are designed to be run by changing teams without degrading performance.

In other words, buildings that assume people will change – and design accordingly.

A Final Thought

The fading of specialists is not a failure of the workforce. It is a natural evolution of how work happens.

The mistake would be expecting buildings to remain frozen in an older operational model.

Digitisation is no longer about being modern. It is about being viable. In a future shaped by gig workers, rotating teams, and increasing complexity, the only way out of the coming operational strain is to ensure that buildings themselves become the most consistent, intelligent participant in the system.

Because when people move on – and they will – the building still has to perform.