The Hidden Administrative Cost of a Single Work Order Is Slowing Down Property Management Across the UK

Written by:

Alejandra Rodriguez

Date:

16 Jul 2026

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A broken dishwasher seems simple enough. A tenant reports it, someone fixes it, life moves on. But between the initial request and the completed repair, a single work order can pass through dozens of hands, scheduling, compliance checks, site visits, invoicing, job sheet documentation, each step adding cost, time, and administrative friction that building owners rarely see on a balance sheet.

That gap between the apparent simplicity of a maintenance request and the operational reality behind it is where facility management companies lose money, miss compliance deadlines, and burn through back-office staff. It is also where AI is starting to make a measurable difference, not in the flashy, pitch-deck sense that dominates vendor marketing, but in the specific, tedious workflows that no one outside the industry thinks about.

Where the Administrative Chain Breaks Down

Sergey Nasonov, Co-Founder and Chief Technology Officer of TYTEN, the UK-based AI company he co-founded to automate facility-management operations, leads the company’s technology strategy and its engineering team, describes the problem in terms of sheer volume. A facility management company handling hundreds or thousands of jobs must track whether each one has a completed job sheet, photographic evidence, data entries, and documentation proving the work was done. Without that documentation, the FM company cannot invoice its client.

“One job, pursuing one job doesn’t take too much time, maybe a few minutes,” Nasonov says. “But doing it when you have hundreds and thousands of jobs, that’s a completely different story.”

The role of chasing suppliers for documentation is repetitive enough to drive high staff turnover, which compounds the problem. New hires must learn which jobs are outstanding, which suppliers are responsive, and which compliance requirements apply to each contract, knowledge that walks out the door every time someone leaves.

The Compliance Stakes

Documentation gaps are not just an efficiency problem. In sectors like healthcare, where FM companies manage hospital buildings under strict regulatory contracts, missing compliance paperwork can trigger penalties measured in millions of pounds. Nasonov says his company has seen cases where a failure to flag that an asset required remedial works, and then complete those works, resulted in fines of several million pounds imposed by the healthcare provider.

“Nobody wants to be in that situation,” he says.

The penalty structures in these larger contracts make the cost of a missed job sheet far exceed the cost of the repair itself. This dynamic makes automated compliance tracking financially justified even before considering labor savings. For building owners and investors, these penalties represent a hidden liability embedded in the operational layer of their assets rather than the physical one.

What AI Actually Does in a Live Back Office

TYTEN’s approach is narrower than what most AI marketing suggests. The company automates specific administrative workflows: sending chasing emails to suppliers who have not submitted job sheets, validating that returned documents contain all mandatory fields, and pushing completed information into CRM systems. When a submission is incomplete, the system replies automatically, specifying what is missing.

The timing of those automated reminders is calibrated to the work type. For a Legionella assessment, for example, the system waits roughly ten days after job completion before beginning to chase, because the report itself takes time to prepare.

Nasonov contrasts this with how existing CAFM (computer-aided facility management) systems market AI capabilities. “They have to say something to the board that they’re working on AI,” he says. “But does it actually address the biggest pain points? In my opinion, rarely the case.” He argues that existing platforms handle core record-keeping adequately but have not solved the specific, high-volume administrative tasks where automation produces immediate results.

One technical capability that surprised Nasonov was AI’s ability to process documents that have passed through multiple analog-digital conversions. Engineers sometimes handwrite reports, photograph them, send the image via WhatsApp to an admin person who prints it and then photographs the printout before emailing it. “I was shocked that AI can understand that, handwritten notes over a few iterations of digital and analog,” he says. Earlier optical character recognition technology could not handle that level of degradation reliably.

The Build-Versus-Buy Trap

Some facility management companies, impressed by early experiments with tools like Claude or ChatGPT, attempt to build their own automation internally. Nasonov describes three typical patterns: companies that prototype something useful and then want more but lack the integration capacity to expand it; companies that try to become software companies themselves; and companies that simply want an existing proven solution deployed immediately.

The middle category concerns him most. Building production-grade software requires integration with CAFM systems, accounting platforms, and email infrastructure, complexity that goes well beyond a weekend prototype. “You are becoming a software company, and it distracts the management,” Nasonov says. “The facilities management company didn’t have that UI expertise. They don’t have the software development expertise to create software that doesn’t have bugs.”

TYTEN has built 25 automation modules and now processes more than 150,000 work orders a year for enterprise facilities-management clients that manage sensitive facilities and data under strict compliance obligations, coordinating a contractor network of nearly 8,000 suppliers.

What Comes Next

Nasonov expects the pace of AI model improvement to accelerate adoption in facility management over the next year. He points to the gap between capabilities available 18 months ago, when developers were copying and pasting code from ChatGPT, and what frontier models from Google, Anthropic, and OpenAI can do now. “It just changes so fast, and this will have a direct implication on the facilities management industry,” he says.

He anticipates that companies that do not adopt automation will become acquisition targets. “There’ll be a wave of M&A, there’ll be inorganic growth that we will probably see,” Nasonov says. For property owners relying on FM companies that have not invested in operational technology, that consolidation wave may mean a change in service provider, or a push to evaluate whether their current provider’s back-office capabilities match the compliance demands of their contracts.

About the Expert: Sergey Nasonov is CTO and Co-Founder of TYTEN, a UK-based AI company focused on automating administrative workflows in facility management, with 25 automated modules built to date.

This article is based on information provided by the expert source cited above. It is intended for general informational purposes only and does not constitute legal, financial, or real estate advice. Readers should conduct their own research and consult qualified professionals before making any real estate or financial decisions.