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Data and AI

Generative AI for a competitive product strategy

While applications of Generative AI for product design and customer experience are promising, in-house AI development brings important concerns about governance, security, and ethics.

Investing in generative AI leads to faster creation of business value, which goes with a balancing act between opportunistic use cases for building an AI-fueled competitive advantage, and the challenges faced in responsibly operating and scaling AI.

Building from the findings of both Capgemini Research Institute report and Domino Data Lab, this ebook explores how Generative AI has renewed the focus of business executives such as Chief Data Officers (CDOs) and Chief Data Analytics Officers (CDAOs), on building and operating AI at scale.

Internal LLM strategies are a result of concerns about governance, security, and responsible AI. Even though product design has potential, ineffective governance can be dangerous.

Transformative potential is limited by talent bottlenecks, unified AI platforms, and shortages in collaborative processes. Businesses that do not quickly embrace AI risk facing existential threats.

Given the economic uncertainties, a large majority of executives recognize the critical role that AI/ML solutions play and the urgency with which they must be delivered. Therefore, adopt efficient procedures and tools, and being equipped with solid foundations and AI solutions is decisive for any organizations to maintain competitive edge in this rapidly changing market.

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