AI could help cleaners spot at-risk contracts early

CleanTasker Founder Kiran Vilasagaram said artificial intelligence can help cleaning companies identify contracts at risk before they are lost.

He said the technology can turn existing operational data into early warning signals for service problems.

Cleaning work is often carried out outside standard business hours and away from client view, making service quality and proof of work harder to track until complaints emerge. Vilasagaram said this often leaves operators reacting only after standards have slipped or client relationships have deteriorated.

He argued that the sector already holds large amounts of information but has struggled to bring it together in a way that shows what is happening at individual sites.

"For many cleaning operators, the first indication of a problem is when a client complains, or worse, cancels a contract," Vilasagaram said. "But we know the warning signs are there in the data - they just haven't been seen or interpreted correctly.

"The introduction of AI offers the opportunity to read the signs not as a singular data input, but as a whole-of-story, highlighting red flags in real time and providing predictive analysis that can potentially save contracts where things haven't been going so well."

The argument centres on combining routine records such as attendance logs, task completion data and service quality measures so managers can spot patterns before they become commercial problems.

Warning signs

Vilasagaram said AI could detect trends such as staff spending more or less time on site than a contract requires, declining satisfaction or quality scores, missed check-ins, incomplete task records and recurring pressures at particular locations. He added that the same data could also help identify employees whose work is consistently strong but may go unnoticed.

According to Vilasagaram, that approach would shift cleaning businesses from a reactive model to a more preventive one. Instead of responding after a complaint, managers could review staffing levels, task allocation and site conditions earlier, or contact clients before concerns escalate.

"If warning trends are flagged early, management can take proactive decisions. Do you need to adjust staff, tasks or other operational elements? Should you check in with your client to assure them you're aware of an issue, or offer increased support?

"We know contracts aren't cancelled over one bin that wasn't emptied or a patch of carpet that was missed. It's a culmination of small frustrations over time that eventually loses the client.

"But with the input of regular data and the support of AI, operations teams can get ahead of small issues before they become major problems, making it near impossible for a client to fall through the cracks. I have no doubt that contracts that would otherwise have been lost will be saved.

"It's an important and much-needed step for the industry," he said.

Sector visibility

The cleaning industry has long faced a visibility problem because much of its work happens when offices, retail sites and other facilities are closed. That can make it difficult for clients to assess performance directly and for contractors to present consistent evidence that work has been completed to standard.

In that context, AI is being framed less as a replacement for workers and more as a tool for interpreting operational information already being collected. Vilasagaram said the gap has not been access to technology alone, but whether tools are designed around the realities of cleaning work.

He said software built specifically for the sector is better placed to reflect contract requirements, staffing patterns and site-level variation than systems adapted from other industries.

"Unfortunately, as a traditionally 'invisible' industry, the specific needs of the cleaning sector have largely been invisible too," Vilasagaram said. "The technology has been available for some time, but the challenge has been recognising what the industry needs and ensuring the solution is purpose-built, not repurposed to fit.

"It's an exciting development, and one that stands to benefit both cleaning companies and their clients."