Revive Your Stalled AI Initiative — Without Starting From Scratch

Many enterprises have tried AI, only to see their ambitions hit a wall. The good news is that they don’t need to start over — they just need to stop treating their data as an afterthought.

A reality check for AI promises

If investing in the right tools and hiring smart people were enough to guarantee success, we wouldn’t be seeing so many AI projects quietly stall. But across industries that’s exactly what’s happening: ambitious projects are fizzling out despite heavy investment. Teams are understandably reluctant to speak openly about it. Leaders are left wondering what went wrong — and how to get back on track.

At the recent Capacity Europe 2025 event, Exadel’s Miglena Dogan joined a panel discussion and met over 150 telecom decision-makers. A recurring theme emerged: Their AI ambitions aren’t dead—they’re just stuck. But despite the setbacks, leaders aren’t ready to walk away just yet.

That’s why Exadel’s consultancy-led approach resonated so strongly during the event. We don’t sell platforms or promise silver bullets. We meet companies where they’re at, assess what’s working, and build on it — rather than starting over.

What Telco Leaders Really Want From AI

What surprised us most wasn’t the number of stalled AI pilots. It was the candidness with which telecom leaders talked about what they don’t want: more AI hype, and yet another overhaul pitched as the only way forward.

What they do want is the right kind of help. Our message of building on their existing investments struck a real chord. No new platforms and no resets – only progress based on what’s already there.

Our idea of turning disconnected pilots into shared enterprise services got an enthusiastic response from those present. With the right guidance, their existing models and infrastructure could serve multiple departments — multiplying value rather than starting over every time.

As one executive put it: “We don’t need to be told where to go. We need help getting there, based on what we’ve already done.”

The Real Bottleneck: Your Data, Not Your Ambition

When AI initiatives fail to live up to expectation, the tools often shoulder the blame. In reality, it’s more often because the data isn’t ready.

Common culprits for stalled AI:

• Legacy systems and siloed data
• Unclear ownership and governance
• Lack of alignment between business goals and technical implementation
• Mistaking hype for value

What “data readiness” actually means:

To adopt AI successfully across the enterprise, your data needs to be:

• Unified: Integrated across silos and departments
• Compliant: Secure, and regulation-ready
• Relevant: Focused on the right metrics and goals
• Contextualized: Structured in ways AI models can meaningfully use

When this foundation is in place, AI becomes less experimental and more operational.

Two Paths Forward: B2B vs. B2C

While the underlying challenge is shared, the way AI creates value looks different depending on the type of business.

For wholesale operators (B2B):

• Automation reduces manual quoting
• Improves operational excellence through AI-powered workflows
• Leverage integrated data for forecasting and dynamic routing

For B2C businesses:

• Speed up time-to-market for new offerings
• Predict churn using behavioral models
• Focus marketing spend on likely-to-convert segments

There are encouraging signs – with some telcos reported already seeing results. And the green shoots are growing in familiar soil. One operator we spoke to saw 90% of their departments adopt AI once the right model and support were in place.
Another reported a 60% reduction in time-to-market by reviving and scaling an underused AI capability. Others pointed to millions in potential annual savings once AI models were relaunched across departments.

Let’s Work with What You’ve Got

At Exadel, we specialize in reviving and realigning AI initiatives. We don’t start from scratch, and we don’t push platforms. Instead, we

• assess what you’ve already built
• keep the parts that work
• scale it into a shared capability across departments

Our consultancy-first model is designed to transform AI from a patchwork of pilots into a unified enterprise capability. By working modularly and department-by-department, we help organizations adopt AI as a shared service that yields measurable value.

It’s Not Too Late to Make AI Work

If your AI initiative has lost momentum, you’re not alone. But you’re also not at the end of the road.
What our participation at Capacity Europe 2025 showed us was that getting results starts with being ‘vulnerable’: willing to admit what’s not working and ask for help before pushing ahead. The companies seeing the most success are the ones that own their failures and ask for help. Unrealistic expectations rarely lead anywhere; honest, pragmatic action does.

Let’s pick up the conversation where Capacity Europe left off.