The Telecom AI Gap No One’s Talking About

AI is rapidly reshaping the world of work. In the telecom sector, its influence is already visible — from intelligent network management to dynamic customer support and the roll-out of AI-enhanced services. But beneath the headlines, a more fundamental shift is taking place: a redefinition not just of skills, but of how employees contribute, how teams are structured and how value is created. The telecom sector has long led on infrastructure scale and technical innovation, but now it must also lead on capability.

CCS Insight’s recent cross-sector report, The AI Skills Gap: Workforce Readiness and What Comes Next, explores how organizations are adapting to AI and where many are falling behind. For telecom providers, the opportunity is clear: firms that invest in workforce capability today stand to unlock the full potential of AI tomorrow and avoid getting stuck in endless pilot mode.

Our Survey: Senior Leadership IT Investment, 2025 revealed that more than 80% of organizations have either deployed generative AI or plan to do so in the next 12 months. However, widespread capability remains elusive. Most companies are racing ahead with tools but leaving their people behind. Structured training is limited. Role redesign is too often an afterthought. And in many cases, AI tools are arriving faster than the skills to use them well. In telecom, this gap is especially pronounced, with high ambition running into structural limits on access, training and leadership ownership, all under mounting pressure from clients, private networks and competition from hyperscalers.

This mismatch is especially stark in the telecom sector, where expectations are rising for smarter services, leaner operations and new sources of growth. The technology is already here. What’s missing is the capability to use it well. In this blog, we explore three areas where telecom organizations have the most to gain and the most to lose by investing in workforce AI skills: product innovation, internal operations and managed service delivery.

Reimagining Products with Human-in-the-Loop Intelligence

Telecom providers are rapidly embedding AI into product offerings, from intelligent customer apps to smart infrastructure and predictive analytics. But real differentiation demands more than access. It requires the skills to guide, interpret and apply AI in ways that deliver business value fast.

Too often, product teams are expected to incorporate AI features without the training or guidance to do so confidently. Our Survey, Employee Workplace Technology, 2024 found that telecom organizations still limit AI access to a narrow group, and few provide the kind of meaningful training that supports confident use. This stifles experimentation and creates capability bottlenecks, making AI innovation dependent on a narrow set of specialists.

This shift is also starting to redefine expectations for employees who are early in their careers. As foundational tasks become automated, junior staff are expected to contribute faster, often using AI from day one. But without structured support, there’s a risk they learn the tool before they learn the job, bypassing the critical thinking and domain understanding that typically develop through hands-on experience. Over time, this erodes the foundation of future expertise.

The companies leading the way are taking a different approach. They’re building capability directly into product teams, encouraging hands-on experimentation and embedding AI into the early stages of design. These teams treat AI not just as a feature but as a partner in creativity and iteration.

Operational Agility Requires More Than Technical Deployment

Internally, telecom providers are already using AI to support a range of operations, from managing network performance and routing support queries to detecting fraud and streamlining resource scheduling. But many deployments remain siloed, with limited operational impact, because employees aren’t equipped to use AI confidently or critically.

Our report revealed a clear divide in outcomes. Where AI tools are embedded into day-to-day workflows and supported with contextual, in-task guidance, the benefits are tangible. In our interviews, teams reported faster decision-making, reduced manual effort and greater autonomy. People can focus on higher-value work and collaborate more effectively across departments.

Some are beginning to address this. Instead of one-off training, they’re embedding AI directly into internal systems. For example, using AI co-pilots to steer employees through routine tasks, or providing on-demand support that builds operational confidence as people work. These approaches make AI part of how work gets done, not a standalone skill to learn later. But these efforts are still the exception.

A major reason for this slow progress is investment. High implementation costs continue to be a major concern for telecom leaders and were often cited as a key barrier to adoption. This continues to fragment deployments and delay meaningful enablement.

In sectors such as professional services and technology, organizations are already embedding AI across roles and building fluency at scale. If telecom providers fail to keep pace, they risk falling behind — not just in terms of internal efficiency, but in their ability to attract talent and deliver at the speed clients now expect.

Managed Services Will Be Defined by Front-Line Capability

As telecom providers expand their managed-service offerings from cybersecurity and device life cycle management to industry-specific platforms, clients are raising the bar. They now expect proactive support, real-time insights and intelligent, outcome-focused delivery. AI can help meet these demands, but only if front-line teams have the skills to apply it effectively.

Too often, AI training is concentrated in innovation or technical teams. Yet our research shows that customer-facing and operational roles stand to benefit just as much, if not more, from the practical use of generative AI. Tasks such as summarizing client interactions, drafting reports or triaging support requests are prime areas for augmentation.

However, our survey highlights a gap. Very few enterprises have a coordinated strategy for building AI capability outside their digital or IT functions. In practice, this means that many front-line employees are given tools without the support to use them confidently or wisely.

Simply providing access isn’t enough. True fluency means knowing how to evaluate outputs, apply judgement and adapt quickly to client needs. Without that foundation, there’s a risk of overreliance or misapplication, particularly in high-stakes service environments.

Our report also highlights that some employees are becoming overconfident in using AI tools, mistaking familiarity for fluency. In managed-service environments, where accuracy, compliance and trust are critical, this can lead to unintentional errors or poor decisions. Without clear guidance on when to use AI, and when not to, telecom providers risk undermining the very services they’re trying to enhance.

Turning AI Ambition into Lasting Capability

One of the clearest messages from our report is that AI adoption alone isn’t enough. The differentiator isn’t access; it’s fluency. In telecom, where the pressure to modernize, scale and compete is high, success will come from how effectively providers equip their people, not just their platforms.

This means moving beyond pilots and technical silos and making AI fluency a strategic workforce priority. Telecom organizations that lead on this front are poised to unlock faster returns on their AI investments and build a more adaptable, resilient and future-ready workforce.

Yet many telecom organizations still treat AI as a technical initiative rather than a strategic business capability. Responsibility often sits within IT, with boards slow to act and still treating AI as a tech experiment, rather than a workforce imperative. Until that changes, workforce transformation will remain fragmented and underpowered.

Our report outlines several priority actions to help telecom organizations build lasting AI capability, from company-wide access to more embedded learning approaches and stronger human oversight. These are the foundations of a more confident, capable AI-powered workforce.

Telecom providers have long led on technology. But as AI reshapes the industry, leadership will depend not just on tools, but on people. Capability will be the differentiator, and those who invest in it will be best placed to compete and grow.

To explore these themes in more depth, including detailed recommendations for workforce leaders, see The AI Skills Gap: Workforce Readiness and What Comes Next, or contact us to discuss the findings.