Fireside Chat, Panel
'Architecting the Future The Enterprise Revolution through GenAI' | RAISE Summit 2024 | Paris
RAISE SummitFlorence Verzelen, Victoria Weller, Gilles Babinet, Emilie Sidiqian, David Martineau, Charles-Edouard Bouée
- Generative AI is expected to drive growth in life sciences research by using virtual twins to test molecules against viruses and optimize energy efficiency in building and construction by 40 to 60 percent.
- Digitalization strategies involving GenAI are projected to accelerate elevator repair capabilities, enable the generation of "very easy code" faster than developers, and eliminate coding tasks such as passing and infrastructure work while preserving the roles of coders and accountants.
- Management consultants anticipate dedicating less time to non-human tasks and more to high-value delivery, with tools integrating GenAI into platforms like Salesforce, PowerPoint, and Photoshop within the current year, necessitating changes in team acculturation.
- A shift from "test and learn" to value-based use cases is imminent, with two categories of applications becoming market standards for productivity growth and a third category involving specific models potentially facing high training costs and limited availability.
- Without GenAI, certain media ventures like Eleven Labs would not exist, while future applications include converting blogs to audio, expanding dubbing to more markets, and implementing text-to-speech in publishing, gaming, advertising, and chatbots.
- The public sector is identified as a key area for rapid efficiency gains, with GenAI viewed as a critical productivity tool to address environmental challenges, potentially contributing to the $3 trillion in annual spending required to meet the 2050 agenda and decarbonization goals.
- The IT landscape is forecast to undergo a reinvention by 2025 regarding vendor selection, characterized by a bifurcation between full-stack providers and open ecosystems where clients orchestrate deployment.
- Companies are advised to avoid delaying GenAI implementation to first clean all data, as the technology can deliver value through fact-based accuracy even without 100% precision, provided the right question is asked.
- Regulatory frameworks are expected to evolve to create national "sandboxes" or "playing fields" that allow innovations like autonomous cars to scale without being blocked by current regulations.
- The transformation of small and medium-sized enterprises is identified as a major challenge, as these entities cannot adopt the seven-pillar roadmaps designed for large enterprises and face rapid model obsolescence every two to three weeks.
- A massive skill shift is anticipated, requiring micro-personalized training for high-pro-code work alongside democratized low-code tools, with an urgency to address the lack of digital skills among 81 percent of CEOs.
- Implementation requires a human-in-the-loop approach due to current tool imperfections and hallucinations, with teams advised to treat GenAI vendors as partners rather than consumers to stay ahead of the technology curve.
- Success in the next year is predicted to depend on the adoption of "trusted AI," the integration of critical thinking into ecosystems, and the prioritization of specific data quality over broad experimentation.