Introduction: The Promise and Challenge of Generative AI

Generative AI (gen AI) offers both significant opportunities and challenges for leaders aiming to guide their organizations into the future. McKinsey research estimates that Generative AI could contribute between $2.6 trillion and $4.4 trillion annually to the global economy while amplifying the overall impact of artificial intelligence by 15 to 40 percent. In the technology, media, and telecommunications (TMT) sectors alone, new gen AI applications could deliver between $380 billion and $690 billion in value, with telecommunications contributing $60 billion to $100 billion, media $80 billion to $130 billion, and high tech about $240 billion to $460 billion. Within the next three years, it’s likely that anything not integrated with AI may be considered obsolete.

While some leaders are already scaling gen AI across their organizations, others remain in the pilot stages, and some are still undecided. For companies to remain competitive, executives must understand gen AI’s potential impact and create strategies to incorporate it effectively. This requires an AI-native transformation focused on both the adoption and management of gen AI. McKinsey’s extensive research and practical experience with clients have identified over 100 gen AI use cases across seven key business areas within the TMT space.

Early results demonstrate that telecommunications companies can achieve significant outcomes with gen AI, particularly in customer care and sales, which could account for 70 percent of the total impact. By automating customer interactions, personalizing products and campaigns, and reducing time to market, companies can boost revenue by 3 to 5 percent. Automation of up to 70 percent of repetitive tasks could also improve productivity, while Generative AI’s potential to automate 60 percent of knowledge-based tasks offers further efficiency gains. Developer productivity, too, could rise by 20 to 45 percent thanks to gen AI tools.

However, moving from a road map to scaling gen AI successfully presents challenges. Becoming an AI-native organization means leveraging technology, data, and governance to create a flexible, continuously learning operating model that balances human and machine strengths. Investing in data quality and architecture, such as vector databases and pipelines, is key to enabling gen AI use cases. No aspect—whether talent, technology, or governance—can be neglected.

Organizations that succeed in deploying gen AI share a clear vision and a decisive financial commitment, which includes maintaining or increasing AI budgets. These resources should be allocated toward crafting customized gen AI solutions tailored to industry-specific needs, such as training large language models with telecom-specific data or partnering with IT vendors to accelerate implementation.

Leaders should expect challenges, from securing organizational buy-in and finding large data sets to overcoming talent shortages and addressing regulatory uncertainties. However, these hurdles are surmountable. Developing risk-mitigation protocols and involving end users in model development are crucial for managing risks and ensuring successful AI adoption.

This McKinsey collection offers insights into the transformative power of generative AI and guidance for leaders preparing their organizations to implement the technology at scale. It explores essential factors such as organizational readiness, data management, risk mitigation, and the evolving future of gen AI. With new capabilities and an expanding AI ecosystem on the horizon, the next steps taken by TMT players will determine how they shift from pilot projects to scalable impact.

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• Introduction: The promise and the challenge of generative AI
• State of the Art 
  • The economic potential of generative AI
  • Making the most of the generative AI opportunity: Six questions for CEOs
• Sector View: Telecom Operators 
  • The AI-native telco: Radical transformation to thrive in turbulent times
  • How generative AI could revitalize profitability for telcos
  • Generative AI use cases: A guide to developing the telco of the future
  • Tech talent in transition: Seven technology trends reshaping telcos
• Deploying Gen AI 
  • The organization of the future: Enabled by gen AI, driven by people
  • The data dividend: Fueling generative AI
  • Technology’s generational moment with generative AI: A CIO and CTO guide
  • As gen AI advances, regulators—and risk functions—rush to keep pace
• What the Future Holds 
  • Six major gen AI trends that will shape 2024’s agenda
• Appendix: Generative AI solutions in action
• Glossary

Number of Pages:

• 126 pages

Pricing: 

• Free