AI in telecommunications balances enormous opportunity with an increasingly complex and evolving global regulatory landscape.
AI technologies are now integral to almost every aspect of a telecom operator’s business — from network optimization and predictive maintenance to customer service, churn prevention, and fraud detection. But telcos cannot rely on a purely reactive approach to regulation. To thrive, the industry must proactively promote ethical, responsible AI and build governance into its operations.
Regulators are already stepping in. According to Omdia, telecom operators must navigate formal AI regulation from at least two major jurisdictions: the European Union and South Korea. Both have adopted risk-based frameworks that reserve the strictest requirements for high-risk AI applications.
Those frameworks differ in scope. The EU’s AI Act applies broadly to users of AI systems, creating obligations across the AI value chain. South Korea’s Basic AI Act is more narrowly targeted at developers and providers of AI-powered products and services. These distinctions are important for multinational operators who must map obligations to roles and responsibilities across their organizations.
Beyond the EU and South Korea, other countries are building out regulatory proposals and public consultations, but many of these initiatives are still unfinished. This fragmented and evolving policy environment makes compliance complex for global telecommunications providers and increases the need for forward-looking strategies rather than piecemeal, jurisdiction-by-jurisdiction fixes.
Sarah McBride, Principal Analyst for Regulation at Omdia, stresses that these regimes mean more compliance work and additional costs: “The overarching impact of these two regulations on telcos is the creation of more compliance work and costs to meet the new legal requirements for safety standards.”
Meeting these requirements demands a fundamental change in how AI systems are designed, deployed, monitored, and managed across diverse legal contexts.
Understanding the core AI risks
Policymakers worldwide aim to preserve the benefits of AI while managing potential harms. For telecoms, failure to address these risks threatens customer trust, regulatory exposure, and operational stability.
The primary concerns center on data quality and bias, accountability and liability, security of interconnected AI systems, and ongoing privacy protections. Operators must ensure access to unbiased, accurate, and representative data sets, guard AI-driven systems against cyber threats, and uphold privacy standards even as data flows grow increasingly complex.
Liability is another difficult question: when AI-driven decisions cause harm, assigning responsibility within multilayered supply chains and technical stacks is challenging. Equally important is the need for explainability — making AI decision processes auditable and understandable to regulators, customers, and internal stakeholders.
As McBride notes, “Telcos must navigate key AI regulatory requirements across multiple policy areas, including high-risk situations, prohibited use, transparency, and enforcement. They also face AI-specific policies and regulations regarding data and privacy, critical infrastructure security requirements, consumer protection measures, and digital sovereignty considerations.”
The implication is clear: AI governance must be integrated into the organization’s core practices, not treated as an afterthought.
From AI regulation compliance to telecom industry leadership
A reactive posture will not serve telcos well. Waiting for every jurisdiction to finalize bespoke rules leaves operators exposed and constantly scrambling. Instead, telcos should take the initiative: build robust, organization-wide risk-management frameworks, set high internal standards, and champion ethical AI practices.
This means moving beyond compliance as a box-ticking exercise to embed principles of fairness, transparency, security, and accountability into AI development and procurement. By adopting standards that meet or exceed the most stringent regulatory expectations, operators can create a consistent global baseline that can be adapted to local rules as they emerge.
A proactive strategy reduces the need to repeatedly rebuild processes for each new regulation. It also positions operators to innovate confidently: AI can deliver major benefits for network resilience, customer experience, and operational efficiency, but these gains depend on rigorous risk assessment and adherence to standards for data quality, accuracy, robustness, and non-discrimination.
McBride emphasizes that success will go to those who embrace regulation as guidance rather than a constraint: “AI offers numerous opportunities for telco innovation, but risks must be assessed thoroughly before implementation, and standards for data quality, accuracy, robustness, and non-discrimination must be adhered to.”
Operators that lead on responsible AI will gain competitive advantage. By developing clear, forward-looking strategies and operational controls rather than waiting for regulators to dictate terms, telecom companies can secure long-term success and help build public trust in AI-powered services.
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