The Future Of AI In Telecom Isn't About Better Models. It's About Better Business Models

There’s no shortage of initiatives around AI in telecom. Every week brings new announcements about AI agents, AI platforms and autonomous operations. The expectation is clear - AI will fundamentally change how communications service providers (CSPs) operate.

What's less clear is how that change actually happens.

Much of the discussion assumes a greenfield environment - as if a CSP can simply introduce a new AI operating model and leave everything else behind. The reality is brownfield, as most CSPs are running highly complex businesses built up over decades, with commercial models, BSS platforms, sales channels, partner ecosystems, fulfillment processes and customer operations supporting millions of customers every day.

The challenge is introducing AI into it in a way that makes it work better, and, just as importantly, in a way that creates new revenue from it.
 

AI’s Value Is In The Outcome

The industry often measures AI by the sophistication of its models, or the number of use cases it can demonstrate. That's the wrong measure.

Customers don't buy AI. They buy outcomes.

They want faster onboarding. Simpler operations. Better customer experiences. Lower costs. New capabilities. Greater business agility.

AI is valuable because it helps deliver those outcomes. The real question for CSPs is: "How do we use AI to create more value for customers, for our network, and for our partners?"
 

The Next AI Challenge Is Commercialization

This is where the conversation needs to move next.

Building an AI capability is only the beginning. The harder challenge is turning that capability into something customers can discover, buy, consume and pay for.

Tomorrow, CSPs’ portfolios won't simply include connectivity, cloud and security. They'll increasingly include AI assistants, industry-specific AI services, intelligent automation and digital capabilities delivered through partner ecosystems.

Those services need to be cataloged, packaged, priced, delivered, orchestrated across multiple partners, settled, billed and continuously evolved. Increasingly, they'll involve multiple organizations collaborating to deliver a single customer outcome.

This is why marketplace and ecosystem orchestration are becoming strategically important. Their value lies in enabling commercialization.

AI may create the capability. Marketplace and ecosystem orchestration create the business model that turns that capability into recurring revenue. That's a distinction the industry hasn't fully embraced yet.
 

Hrvatski Telekom Demonstrates A Practical Approach

Hrvatski Telekom is a good example of what this looks like in practice.

Rather than launching AI as a standalone initiative, the company is extending an already modern digital business platform to introduce AI-powered services, embed AI into customer and employee journeys, and simplify internal operations.

The platform was modernized to make the business more agile. AI is now building on that agility.
That's an important distinction. It shows that CSPs can adopt AI by evolving the business they already have - and monetizing what that evolution makes possible.
 

What Commercialization Looks Like In Practice

Commercializing AI requires CSPs to turn technical capabilities into propositions that customers can understand and use. The starting point is a clearly defined business need, supported by a simple explanation of the value the service will deliver.

An AI-enabled offer might improve customer support, strengthen operational performance or enable a new digital experience. Whatever the use case, customers need clarity on how the service works, how they will access it and how its value will be measured.

Delivering that experience will often depend on several partners. CSPs may need to combine their own capabilities with cloud, data, security and AI services from across the ecosystem, while presenting the result to the customer as a single, coherent offer.

This requires commercial flexibility as well as technical integration. Services need to be assembled and adapted quickly, with pricing models that reflect how customers want to buy and consume them.

The proposition should also continue to evolve after launch. Insight from customers, partners and service usage can help CSPs improve the offer, add new capabilities and strengthen its commercial performance over time.

This gives CSPs an opportunity to play a broader role. By coordinating the technologies, partners and commercial structures behind an AI-enabled service, they can become orchestrators of business outcomes and create more repeatable sources of revenue.
 

Competitive Advantage Won't Come From AI Alone

The organizations that create lasting advantage will embed AI into the way they already sell, fulfill, support and monetize services.

More importantly, they'll rapidly turn AI capabilities into products and services customers can discover, buy and consume through a marketplace, orchestrated across a partner ecosystem.

The opportunity extends beyond improving existing operations. AI gives CSPs the potential to expand their role in the digital economy by making complex combinations of technology easier for customers to access and consume.

For CSPs, success will depend on connecting AI investment to clear customer value, scalable delivery and commercial models that can support long-term growth.

In the years ahead, the winners will be the companies that commercialize AI most effectively.