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Datos e IA

Beyond the pilot: How to successfully scale production-level generative AI projects

Artículo 11 dic 2024 Tiempo de lectura: min

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Episode notes

At least 30% of generative AI projects will be abandoned after proof of concept (PoC) by the end of 2025, according to a Gartner press release.¹ This underscores a major challenge in harnessing the full potential of generative AI initiatives relative to the investment and confidence most leaders see in the technology. How can organizations effectively scale generative AI PoCs and achieve the expected impact?

In this episode, our experts discuss the future of generative AI in the telecom sector, the role of AI agents in network operations, and the critical need for ethical AI practices. Tune in to discover the criteria and frameworks used to identify generative AI PoCs worth investing in and how to take these concepts from initial ideas to production-level implementation.

Featured Experts

This episode references a Kyndryl and Altman Solon survey that focuses on the challenges customers face with generative AI PoCs. The report will be available on Perspectives on Progress in January 2025. Stay tuned for more details.

On this topic

“When we look at the guidelines we would give towards generative AI, the first one is a recommitment to using AI in a responsible way, and that has a lot of implications. It's not only about security and privacy, which are the core of it, but it’s also about fairness, non-bias and sustainability. We know what it takes to run AI. We should do it in a sustainable way.” - Eugenia

“The thing that needs to be ironed out about this technology [generative AI] is you cannot just leave it and forget it...You want to ensure model accuracy, performance, deterioration and bias." - Priya

“I see Chief AI Officers being a common role in the next 5-10 years...I think there's a strong talent base that is really inspired. They'll go out and they'll learn how to solve and overcome challenges." - Iman

"When we're talking about the network, the focus is around the degree of network autonomy, the costs associated with troubleshooting and how autonomous it could eventually become. Additionally, we focus on enhancing the customer experience through predictive and adaptive capabilities." - Eugenia