Enterprise AI: Practical steps for telcos to address customer needs

In the first report in this series we identified the most promising opportunities for telcos to serve enterprise AI needs. This follow-up research focuses on the practical steps telcos must take to execute, differentiate and deliver impact for enterprises adopting AI.

Introduction

The question we posed in our first report in this series is what opportunities can telcos pursue to become more relevant partners in enterprise AI.

For years, telcos have sought to position themselves as essential to digital transformation. Their networks underpin cloud, IoT, and the broader data economy. Yet in the context of AI, that positioning is no longer enough to secure a leading role with enterprise customers.

For most enterprises, connectivity is neither the main enabler — nor a major barrier – to adopting AI. In our enterprise survey, just 9% of enterprises’ selections were ”connectivity provider” when asked who they would turn to for support with AI. Connectivity is assumed to just work. The real challenges are elsewhere:

• Data security and compliance: Putting in place the governance for ensuring data sovereignty, privacy, compliance, copyright and ethical use in line with national and sectoral regulations.
• Talent and skills shortages: Finding the right expertise to build, deploy, and manage enterprise AI applications responsibly.
• Lack of clear business case, funding and ROI: Translating experimental AI projects into measurable business outcomes.
• Limited availability of high-quality data: Managing fragmented or poor-quality datasets that limit model accuracy and performance.

The greatest barriers for enterprises in AI adoption are data security, skills and ROI

Source: STL Partners, Global AI enterprise survey, August 2025, N=303

If you are not a subscriber, enter your details below to download a free copy of the report

This means that initiating AI conversations with ”network” or ”connectivity” is unlikely to resonate with enterprises. It will not lead to meaningful dialogue or help telcos position themselves with enterprises. To stay relevant, telcos must start their enterprise conversations with customers’ priorities.

Our AI enterprise survey revealed a clear perception gap. When asked what would make connectivity providers more relevant to them, enterprises ranked ”security” last, even though it is the greatest barrier to AI adoption. Instead, they prioritised AI infrastructure credentials, proven AI deployments in their industry, and integration with leading AI and cloud platforms.

This is why telcos must first establish themselves as active members of the AI ecosystem. Before trying to compete on credentials or differentiation, they need to prove they are relevant partners for enterprises’ AI journey — that they have access to, and can help enterprises adopt, the AI solutions enterprises already care about. They also need to bring proof-points to assert their claims.

Telcos must show they meaningfully understand and deploy AI

Source: STL Partners, Global AI enterprise survey, August 2025, N=303

Enterprises typically think in terms of outcomes and applications, not compute or connectivity. Telcos therefore need a visible AI offering at the solution layer – delivered either directly or through partners. This may feel unfamiliar, as it requires telcos to shift their mindset: establish relevance at the service and solution layer first. Then later bring network and compute as key enablers. This report delves into how operators should approach each of the key opportunities available to them, and how they should position these to prospective enterprise customers.

Telcos need a clear AI products-and-services offer that leads customers back to infrastructure

Table of contents

• Executive Summary
• Introduction
• Prove relevance through AI solutions
  • Offer recognised AI models and AI-enabled applications
  • Develop AI solutions directly to translate existing sector expertise into differentiated AI-enabled offerings
• Cybersecurity is the logical cornerstone for enabling AI
  • Deliver end-to-end cybersecurity AI services and solutions
  • Provide ongoing, AI-aware managed security services
  • Digital identity: Telcos’ differentiated role in AI-era security
• Professional services support enterprise AI adoption
• Bridging the AI services to infrastructure opportunity
  • Compute underpins all AI, making it the obvious infrastructure focus for telcos beyond connectivity
  • Edge AI provides a potentially complementary, AI infrastructure opportunity for telcos
• Connectivity remains the core of a telco’s AI offer, yet this too must evolve
  • Preparing networks for AI agents
  • Two tactical connectivity opportunities operators should pursue
• Conclusion

Related research

• Enterprise AI: What are the best opportunities for telcos?
• Telco generative AI adoption tracker
• Sovereign AI: A strategic playbook
• How telcos can put their stamp on digital identity
• Not all telcos need to build their own AI factories
• Networks for AI: Segmenting the growth

Jonas Topp-Mugglestone

Jonas Topp-Mugglestone

Consultant

Jonas is a Consultant at STL Partners, specialising in data centres and M&A.