For the UK’s telecom and IT sectors, agentic AI could be the new rainmaker.
With its capabilities to understand, adapt, predict and act independently, businesses can now unlock capabilities previously thought impossible. Imagine fully autonomous customer interactions, predictive operations and dynamic system management – the possibilities are unlimited.
According to Gartner, agentic AI sits at the top, offering businesses a virtual workforce capable of offloading complex tasks. Pair this with AI governance platforms that enforce accountability, spatial computing for immersive decision-making and energy-efficient computing to tackle sustainability goals, and we have a tech ecosystem built to redefine industries.
Yet, UK’s telecom and IT sectors, while leading in AI adoption, are ill-prepared to take this leap into the future.
Failure to launch
For a decade, IT and telecom have been tinkering at the edges with digital transformation while the core problems remain untouched. Yes, they have adopted AI, and yes, they lead in implementation statistics, but barely 10 per cent of companies are taking these experiments beyond pilots, and at least 30 per cent are expected to abandon their pilots by the end of the year. Every incremental innovation in AI is met with the same infrastructure bottlenecks, the same struggles with data readiness, and the same patchwork of tools and systems. Even as 87 per cent of operators integrate AI into their network operations, they remain hamstrung by the lack of high-quality data.
Let’s start with the problem. Each use case is tackled as a standalone project, requiring bespoke integrations, significant change management and endless cycles of reengineering. This approach wasn’t scalable a decade ago, and it certainly isn’t now when the landscape is shifting at lightning speed. The Achilles’ heel of many enterprises is their existing infrastructure, which is ill-equipped to meet the demands of an autonomous future. Most companies simply are not ready for this reality.
The UK government is creating AI zones, hoping to create £45 billion in annual savings, but without addressing foundational gaps this vision is at risk of falling flat. What is the ticket out of this decade-long stagnation?
Adopting a platform mindset
For enterprises, becoming AI-first will be a sustained differentiator and a force multiplier. And that’s not going to happen if companies chase the next big use case or the latest tech or model in town. The only way to keep up with advancements is to adopt a unified platform that can accommodate any use case. A platform-centric approach offers a composable, modular architecture that enables businesses to plug and play new AI technologies without disruption. It ensures scalability, flexibility and speed. In a Forrester Consulting report commissioned by EdgeVerve, 70 per cent of companies said that they believed a platform approach could help them achieve their top digital transformation goals.
It’s important to be clear: a platform is not just a tool. It’s a strategy. It’s what allows telecom providers to predict operational disruptions by deploying digital twins of their networks. It’s what enables IT leaders to cut time-to-market with intuitive AI interfaces that make even complex systems accessible to non-technical teams. It’s what transforms call centres into revenue drivers by embedding AI-powered hyper-personalisation into every customer interaction.
And a unified platform addresses the biggest obstruction to AI adoption: data readiness. By centralising and standardising data pipelines, it creates a single and complete source of truth. It also ensures that businesses can easily integrate new models and technologies without rebuilding their infrastructure from scratch.
Enabling applied AI at scale
A platform approach sets the perfect stage for scaling AI while ensuring past investments don’t go to waste, by building on what already exists and amplifying its impact.
Consider the customer service operations of one of the world’s largest telecoms companies. Thousands of agents spread across geographies had to work with inconsistent processes, poor visibility into workflows and a lack of actionable insights. This led to dissatisfied customers and underperforming teams. But it found a way forward. Deploying a unified platform for process intelligence, it unlocked task-level insights, standardised operations and improved agent productivity by 20 per cent, all without disrupting daily work.
Similarly, a global telecom giant was drowning in inefficiency, managing more than 750,000 tower lease contracts riddled with complexities — non-standardised formats, hidden risks and manual data extraction that delayed decision-making and introduced costly errors. Using a platform approach, it automated contract reviews, extracting terms and clauses with precision, while surfacing insights into risks and opportunities. The result was $21 million in savings, a 60 per cent productivity boost and better negotiations driven by instant access to accurate, actionable contract data.
Infinite possibilities
The UK’s AI market is set to reach $26.9 billion by 2030, with agentic AI leading the charge. Companies that are unable to apply AI at scale risk falling further behind, unable to keep pace with the demands of autonomous AI.
The path forward isn’t just about technology — it’s about creating a scalable foundation for innovation. Businesses that succeed will be those that integrate agility into their core, enabling them to adapt as AI technologies evolve. It’s no longer about chasing the next breakthrough, but about being ready for whatever comes next.