How AI in telecom is revolutionising the industry

AI in telecom: female telecom worker talking on a phone near a cell tower

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Telecom leaders are facing explosive data consumption growth, modest revenue expansion, intensifying competition, and ever-increasing customer expectations for seamless experiences. The traditional telecom playbook, focused on infrastructure investment and cost optimisation, is no longer sufficient to navigate this complex environment.

Advances in AI, such as agentic AI, can help telecom organisations address these challenges. Nearly nine out of 10 telecom leaders report higher productivity from their AI investments, according to new telecom research from ServiceNow. And more than eight in 10 are seeing improvements in gross margins, cost savings, experiences, and competitiveness.

Table of contents

What is AI in telecom?

AI in telecom is, ideally, a unified intelligence layer that transforms fragmented networks and systems into orchestrated ecosystems. It harnesses the massive data flows generated across communications infrastructure to create predictive, self-optimising systems that continuously evolve.

At its core, AI in telecom is the technological foundation that allows telecom companies to deliver autonomous networks that anticipate needs before they arise and make intent-based decisions. It elevates networks from passive conduits to proactive, adaptive ecosystems.

For forward-thinking telecom leaders, AI serves as both an accelerator and an amplifier, simultaneously removing operational friction and magnifying the impact of every strategy decision.

The most powerful telecom AI implementations seamlessly unify previously disconnected domains—network operations, customer experience, workforce productivity, and service innovation—into a single intelligent fabric that drives outcomes at unprecedented scale and speed.

The most powerful telecom AI implementations seamlessly unify previously disconnected domains into a single intelligent fabric that drives outcomes at unprecedented scale and speed.

What is agentic AI in telecom?

Agentic AI in telecom refers to intelligent, autonomous systems that undertake a variety of tasks, such as analysing and actively optimising networks and operations and assessing and managing business risks. It’s a fundamental shift from reactive to proactive network and operations management.

Traditional AI excels at pattern recognition and prediction. Agentic AI in telecom can help deliver far more across the entire service lifecycle, encompassing sales, fulfilment, and service. By observing, deciding, and acting with minimal human intervention, agentic AI can help telecom companies:

Our research found that 18% of telecom companies are already using agentic AI for risk management, fraud identification and mitigation, network optimisation, and regulation compliance use cases. And 42% are considering adopting the technology within the next year.

How can AI be used in telecom?

More than half (54%) of the telecom companies we surveyed rolled out more than 100 AI use cases last year, spanning every aspect of operations. These include:

Boosted employee enablement

AI-powered knowledge systems provide telecom employees with instant access to critical information, accelerating resolution times and enabling even junior team members to handle complex issues with confidence.

Nearly half (46%) of the telecom leaders in our survey report significant return on investment (ROI) from using AI search capabilities across their value chain—from customer service to infrastructure management to employee enablement.

Supercharged customer experiences

AI-powered self-service helps customers get updates, find answers, and take action. AI-generated case summaries, diagnostic tests, and suggested resolutions empower service workers to resolve issues fast.

Unified omnichannel engagement

Connecting your contact centre as a service (CCaaS) solution to an AI-powered customer relationship management (CRM) platform can unify routing, boost workforce engagement, and simplify communications through cloud telephony.

Service revenue growth

Using AI to optimise lead nurture, order exception resolution, and complex service delivery can open new sources of revenue.

Streamlined issue resolution

Moving to autonomous networks can provide end-to-end automated service assurance. Connected workflows across the business help enable reliable and proactive service experiences that anticipate, communicate, and resolve issues for increased productivity and expedience.

Modernised network management

Comprehensive visibility into the network and tasks such as inventory modelling and service design enables smarter, faster network planning and deployment. Predicting capacity issues in advance and preventing costly overages and service disruptions can decrease costs.

telecom worker in hard hat holding a tablet looking up at some cell towers

What are the challenges of AI in telecom?

Despite compelling returns, implementing AI at scale in telecom environments presents unique challenges. Legacy systems, data silos, and the specialised knowledge required to manage telecom infrastructure and operations create implementation hurdles.

Security concerns are of particular importance in a regulated industry that handles sensitive customer data and critical infrastructure. Only 45% of telecom companies report significant progress creating AI-specific policies to maintain regulatory compliance.

This explains why 31% of telecom companies in our study are using agentic AI to support their cybersecurity strategies, from detecting anomalies to responding to potential threats in real time.

Strategic AI implementations require significant investment at a time when many telecom companies are under pressure to reduce expenditures. The solution is to prioritise use cases with clear ROI pathways, allowing initial wins to fund broader transformation.

Why telecom AI can't wait

The telecom industry stands at an inflection point. Our research reveals that while AI maturity scores for telecom companies dropped 10 points year over year, 79% of these organisations increased AI spending in the same period. This disconnect signals a widening gap between investment and effective implementation—a gap that creates both risk and opportunity.

"Many telcos spend too much time trying different AI solutions or building the perfect LLM [large language model] before launching it," says Rohit Batra, general manager of manufacturing, telecom, media, and technology at ServiceNow. "Meanwhile, less risk-averse competitors are jumping ahead."

This "analysis paralysis" isn't just delaying progress. It's also creating competitive vulnerabilities that more agile players are actively exploiting. As a senior vice president at a Swedish telecom company observed, too many organisations falsely believe they "know what they are doing with AI," when the data clearly indicates otherwise.

How is AI changing jobs in telecom?

AI is redefining the skills that telecom professionals need—not replacing workers. Only 31% of telecom companies strongly agree they have talent with the appropriate skills to execute their AI strategy. As intelligent systems take on routine tasks, telecom workers are transitioning to strategic roles that require uniquely human capabilities: relationship building, creative problem-solving, and innovating.

With AI, network engineers can oversee AI systems that handle routine problems automatically, freeing them to focus on architecture rather than troubleshooting. Customer service representatives can become experience designers rather than transaction processors. And data teams can shift from collecting information to extracting actionable intelligence that drives business transformation.

Perhaps most significantly, AI is creating entirely new roles that didn't previously exist in telecom—from AI ethicists who ensure responsible implementation to data scientists who develop next-generation algorithms tailored to telecom challenges.

The telecom companies that posted the highest AI maturity scores in our study, a group we call Pacesetters, are addressing this new reality through comprehensive reskilling programs. More than eight in 10 (81%) Pacesetters have implemented training and support programs, and 67% host AI learning events.

Many telcos spend too much time trying different AI solutions or building the perfect LLM before launching it. Meanwhile, less risk-averse competitors are jumping ahead. -Rohit Batra, General Manager of manufacturing, telecom, media, and technology, ServiceNow

How to implement AI in telecom

Successful AI implementation in telecom comes down to strategic, enterprise wide transformation with clear execution pathways. By taking that approach, Pacesetters in our study have increased their revenue 1.84 times in the past year. Based on our research, we recommend these steps to implement AI in telecom:

  1. Lead with an innovation mindset: Successful AI transformation begins with cultural reinvention. More than eight in 10 telecom Pacesetters encourage employees to experiment with AI.
  2. Take a single-platform approach: Fragmented AI initiatives create fragmented results. Nearly two-thirds (64%) of telecom Pacesetters use an AI-powered platform to connect people, data, and processes across their entire ecosystem.
  3. Nurture AI talent and skills: Technology transformation requires human transformation. Leading telecom companies are systematically upskilling their workforces. Pacesetters are 1.6 times more likely than their counterparts to feel they have the right mix of talent and skills to achieve their AI strategy.
  4. Prioritise data governance and management: AI is only as effective as the data feeding it. An enterprise wide data governance framework can help balance innovation and compliance. Nearly two-thirds (62%) of Pacesetters in our study have formalised data governance and compliance.
  5. Embrace agentic AI: AI agents offer new ways to unlock AI value. One-third of telecom Pacesetters are using agentic AI, compared to 15% of other telecom companies.
  6. Set a long-term shared AI vision: Successful AI balances ambitious future vision with pragmatic present action. Half of the Pacesetters in our study say they operate with a shared AI vision that’s clearly communicated across the company.

What is the future of AI in telecom?

The future of the telecom industry belongs to organisations that view AI as a business transformation imperative. As agentic AI systems evolve from experimental to operational, they will enable entirely new service models imbued with the adaptability and intelligence of advanced AI across the entire service lifecycle.

The telecom companies that will thrive in this future aren't waiting for it to arrive—they're actively creating it through decisive implementation, strategic investment, and organisational transformation. While some companies debate theoretical concerns, leaders are systematically capturing value that will fund their continued AI evolution.

For telecom executives, the path forward is to act with urgency, implement with purpose, and transform with intention.

Find out how ServiceNow can help you put AI to work for telecom.