The United Kingdom, Australia, Canada, Japan, and the United States of America collaborate through the Global Coalition on Telecommunications (GCOT) to advance telecommunications technology innovation, fostering security, growth, and societal benefits across all participating jurisdictions.
Out of 73 economies evaluated by an AI maturity index, only Canada, Mainland China, Singapore, the UK, and the U.S. are recognized as AI pioneers. More than 70% of economies scored below the halfway point in critical categories such as ecosystem participation, skills development, and research and development (R&D) capabilities.
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As future networks evolve over the next decade and beyond, AI will play a transformative role, becoming an integral “AI-native” component of telecommunications infrastructure. Unlike traditional systems that incorporate AI as an add-on, these networks will seamlessly integrate AI and data capabilities into every layer of their operations.
To maximize the benefits of this transformation while addressing potential risks, GCOT partners have established key principles for the responsible use of AI in telecommunications. These guidelines are designed to help industry leaders, researchers, and AI developers ensure AI technologies are implemented safely, securely, and with trustworthiness at their core.
- Innovation and Competition
AI systems in telecommunications should drive innovation, enhance competition, and respect intellectual property rights. GCOT partners emphasize investing in infrastructure, data access, skills, and R&D to promote interoperability and support new market entrants. Regulatory measures must remain fair and minimally restrictive.
A key example of this is how the UK is leading AI regulation with a GBP 100 million investment, ensuring ethical and accountable deployment. Similarly, the Latin American Artificial Intelligence Index (ILIA) 2024 highlights Chile, Brazil, and Uruguay as regional AI pioneers, excelling in governance, research, and adoption. Meanwhile, responsible AI (RAI) is poised to transform the Asia Pacific telecom industry, unlocking new revenue opportunities and promoting sustainable growth.
- Transparency, Explainability and Human Oversight
AI systems in telecommunications must ensure transparency and explainability to build trust and accountability, especially for critical functions. Transparency should cover the entire supply chain, with clear details on AI development, methods, and data sources. Best practices include governance measures, audits, and stakeholder engagement. AI-driven decisions, such as network traffic rerouting, must be understandable and open to challenge, while retaining human oversight for critical decisions.
To advance AI transformation, TM Forum and Amazon Web Services (AWS) have introduced GAMIT, a Generative AI Maturity Interactive Tool. Based on insights from over 200 AI decision-makers globally, GAMIT helps CSPs benchmark their GenAI maturity, identify key use cases, and accelerate scalable production.
- Privacy
Continuous improvement is key to aligning with evolving privacy regulations. AI systems in telecommunications must prioritize privacy by safeguarding user data and individual rights through privacy-preserving technologies, strong data governance, and ongoing monitoring.
The GSMA has introduced the first industry-wide Responsible AI (RAI) Maturity Roadmap to help telecom operators assess and improve their ethical use of AI. With AI's potential value in telecom reaching up to USD 680 billion, the roadmap provides tools and guidance for telecom organizations to advance AI while adhering to responsible practices and ethical standards.
- Fairness
AI systems in telecommunications must ensure fairness by minimizing bias and promoting equitable outcomes. This includes implementing governance measures to identify and address biases, engaging stakeholders, conducting audits, using diverse datasets, and maintaining transparency in decision-making.
For example, the European Union's AI Pact, effective sinceAugust 2024, encourages organizations like Nokia to refine processes and comply with evolving regulations, including conducting rights impact assessments. Additionally, the AI Convention, a global treaty signed by multiple countries, represents a significant step toward regulating AI technologies while protecting human rights.
- Security and Resilience
AI systems in telecommunications must be designed for security and resilience, protecting against cyber threats and ensuring operational stability. These systems should be resistant to attacks like dataset poisoning and backdoor intrusions, and capable of recovering from disruptions.
Resilience involves advanced cybersecurity measures, such as real-time threat detection, automated responses, and regular security audits. It also includes testing AI models before, during, and after deployment, and sharing information about security incidents across networks.
The US AI Safety Institute Consortium (AISIC) brings together a diverse group of stakeholders, including AI creators, users, researchers, and government organizations, to focus on the safe and responsible development of AI technologies.
TELUS, the first Canadian telecom to join this initiative, also signed Canada’s voluntary code of conduct for generative AI. This code establishes principles for the responsible development of AI, emphasizing transparency, fairness, and ethical considerations in AI use, serving as a model for others in the industry.
In 2023, Canada introduced the Voluntary Code of Conduct for Advanced Generative AI Systems, providing guidelines for organizations to ensure the ethical management of generative AI. This was followed in 2024 by the launch of the Regional Artificial Intelligence Initiative (RAII), including PrairiesCan and PacifiCan, aimed at enhancing Canada’s ability to address AI safety challenges. Additionally, the Canadian Artificial Intelligence Safety Institute (CAISI) was created to further strengthen Canada’s capacity to manage AI safety risks and maintain ethical standards in AI development and deployment.
- Environmental Sustainability
AI systems in telecommunications should actively contribute to environmental sustainability by minimizing their own impact. This includes deploying energy-efficient systems, optimizing data centers, and using low-carbon energy sources where possible. The US-based Artificial Intelligence Competition Center (AICC) is working to establish AI energy efficiency standards, explore AI’s role in transforming the energy sector, and create a roadmap for grid modernization to meet future AI energy demands.
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