Paving The Data Quality Highway for AI to Drive

InfozechThought LeadershipGeneralPaving The Data Quality Highway for AI to Drive

September 30, 2025

Paving The Data Quality Highway for AI to Drive

Artificial Intelligence has quickly moved from hype to reality in the telecom infrastructure sector. From asset verification to energy optimization, AI is beginning to transform how Tower companies and Telcos operate. But there’s one truth we can’t afford to ignore: AI is only as good as the data it learns from.

At the recent TowerXchange Africa Meetup in Nairobi, I had an opportunity to present a keynote and I shared a simple analogy: imagine driving on a highway riddled with potholes. No matter how powerful your car is, you’re forced to slowdown, adjust, and constantly press the brakes. That’s exactly what poor data quality does to AI adoption. Without trusted data, even the most advanced AI modelsstumble.

A recent MIT study highlights this reality—95% of AI pilots fail to deliver expected results, and the culprit is almost always unreliable or incomplete data.

Data Quality as the Foundation

For telcos and towercos, data isn’t just numbers on ascreen. It’s the invisible foundation on which billions of dollars of infrastructure and operations depend. Weak foundations lead to weak outcomes – just as a tower built on unstable soil is bound to collapse.

At Infozech, our approach is to strengthen this foundation. By embedding AI right at the first point of data capture – whether through mobile devices or IoT sensors, we ensure accuracy before data even enters the system. Layered validation with AI, APIs, and real-time checks creates a single source of truth that operators can trust.

From Theory to Field Reality

The journey from boardroom discussions to field deployment is where the real breakthroughs happen. I was joined by James Langhat, Head- Operations at Safaricom and his experience suggests that Infozech’s solution have been able to deliver tangible results.

Overall, in terms of delivering value in

Asset Verification: By replacing manual entry with AI-enabled image capture of asset name plates, they achieved 97% data accuracy and cut verification timeby 60% across 8,000+ sites.
Diesel Management: With AI-driven capture of generator hours across 4,300 sites, Safaricom virtually eliminated manipulation and errors, restoring trust incritical energy cost data.

These use cases show that data quality paired with AI is not just a lab experiment – it’s solving real-world challenges on the ground.

The Road Ahead

As the industry doubles down on digitization, the focus must shift from collecting “more” data to collecting the right data. High-quality data unlocks powerful AI outcomes:
Accurate alarm correlation reduces site visits.
Correct equipment sizing prevents costly underutilization.
Trusted operational insights build confidence across investors, regulators, and operators alike.

The message is clear: before AI can drive, we must pave the data quality highway. We would love to have a discussion with you on where you are in your data quality journey. Just drop a message and we will connect back with you soon.