Jerzy Badowski

When a workforce handles 80,000 service calls daily across 10 countries, manual oversight isn’t feasible. 

This reality has pushed Solutions30, Europe’s largest field services company, to embrace AI.

The Connectivity, energy and technology services provider has deployed AI systems across its 16,000-strong technician workforce, focusing on installation safety and route efficiency.

Jerzy Badowski, Solutions30’s Group Chief Information Officer (CIO), brings over 20 years of IT experience to the challenge. 

His perspective on AI is practical: It must enhance existing frameworks rather than replace them. “AI is a layer on top of all the controls and all the frameworks that already exist,” he says.

How Solutions30 uses AI for safety

Solutions30’s most compelling AI application addresses smart meter installations. 

When technicians replace traditional gas meters with smart devices, connections must be perfect. Poor installation creates dangerous situations for workers and customers.

The company developed the “Deepomatic” system, using computer vision to analyse installation photographs in real time.

During the project, this AI system processed over 1.3 million images, automatically verifying connections and safety protocols.

“We have implemented an image recognition system, which allows our technicians to verify the quality of a job before they do it,” Jerzy says. 

He says the work is “quite risky and dangerous, not only for the technician doing the job but also for the customer.”

The AI system identifies connection points and components, comparing them against standards and flagging deviations immediately. 

Technicians then receive instant feedback before leaving job sites, eliminating separate quality inspections and reducing callbacks.

The second major deployment tackles route optimisation across thousands of vehicles. 

The system processes traffic patterns, appointment schedules and geographic constraints to calculate optimal daily travel paths.

“We can optimise the time of travel, which is good for our end customer because the customer doesn’t need to wait a lot of time,” Jerzy explains.

“From an ESG point of view, we are also reducing carbon footprint and we are reducing fuel use as well.”

For a company operating thousands of vehicles, small efficiency improvements generate substantial benefits. 

Even saving a litre of fuel per vehicle daily creates significant environmental and cost impacts.

When data quality becomes competitive foundation

Solutions30’s AI strategy emphasises data quality as a prerequisite for effective machine learning (ML).

Operating across multiple countries with different languages, currencies and regulatory frameworks creates complexity many companies underestimate.

“We are living in a big data world,” Jerzy notes. 

“We have  hundreds of different databases in use, which generates a lot of data.” 

But volume without quality creates problems: “If we don’t have enough quality in our data, we will make wrong decisions, we’ll go in the wrong direction.”

AI systems learn from historical patterns, so errors in training data produce unreliable algorithms. 

For a company handling safety-critical work, this isn’t just about efficiency – it’s about preventing dangerous mistakes.

Jerzy’s caution extends to broader AI implementation: “AI has two sides, so I would compare it to a knife,” he says. “It can ease your daily activities, but it can also be very dangerous.”

Yet he believes companies cannot afford to delay AI adoption.

“If a company will not use AI technologies within the next few years, I think that it’ll not exist anymore,” he says.

“Use it widely but use it wisely as well,” he advises.

Read the full story HERE.