Bruno Aziza, former distinguished voice at Google, discusses practical applications of generative AI within the enterprise. Topics include: understanding generative AI, trust and data quality, financial impact and adoption, ethical considerations, identifying use cases, aligning enterprise architecture and AI strategy, and driving adoption in the enterprise.
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volunteer_activism ADVICE
Prioritize Productivity And CX Use Cases
Prioritize use cases that increase employee productivity and improve customer experience before chasing novelty.
Target tasks that are repetitive or help junior staff accelerate learning to get quick, measurable wins.
insights INSIGHT
Data Quality Is The Real Competitive Moat
Evaluate models through Reliability, Accountability, Fairness, and Transparency (RAFT).
The real competitive moat is high-quality, well-provenanced data, not just the model itself.
volunteer_activism ADVICE
Target Four High-Value Domains First
Focus initial efforts on four high-value areas: customer operations, marketing & sales, software engineering, and R&D.
Use those domains to capture ~75% of generative AI enterprise value before exploring edge cases.
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In episode 806 of CXOTalk, we discuss practical applications of generative AI within the enterprise with Bruno Aziza, who was a distinguished voice at Google before joining CapitalG. The conversation explore the technical aspects, the importance of data quality, and the ethical considerations surrounding generative AI deployment. Be sure to watch episode 806 for a live, nuanced discussion aimed at elevating your strategic roadmap for enterprise AI. The conversation includes these topics: ► Understanding Generative AI in the Enterprise: A Deep Dive ► The Human-Machine Symbiosis in Generative AI ► Trust and Data Quality in Generative AI ► Financial Impact and Adoption of Generative AI ► Enterprise Trends and Use Cases for Generative AI ► Deploying Generative AI: Ethical and Practical Considerations ► “Trust and Data Quality are the Competitive Moat” ► Data Strategy is the Foundation of Generative AI Strategy ► How to Identify Use Cases for Enterprise AI ► How to Align Enterprise Architecture and AI Strategy ► What Does Data Corruption Mean for Generative AI? ► Deploying Generative AI: Ethical and Cultural Considerations ► How to Drive Adoption of Generative AI in the Enterprise ► Future Prospects: The Evolving Landscape of Generative AI and Enterprise Read the full transcript: https://www.cxotalk.com/episode/generative-ai-strategy-in-the-enterprise Subscribe: https://www.cxotalk.com Bruno Aziza is a Partner at CapitalG, Alphabet's (parent company of Google) independent growth fund. He is a seasoned operator who specializes in high-growth SaaS and enterprise software. Bruno has led product, marketing, sales and business development teams across all phases of growth, from startups to mid-size companies and Fortune 10 software leaders. Michael Krigsman is an industry analyst and publisher of CXOTalk. For three decades, he has advised enterprise technology companies on market messaging and positioning strategy. He has written over 1,000 blogs on leadership and digital transformation and created almost 1,000 video interviews with the world’s top business leaders on these topics. His work has been referenced in the media over 1,000 times and in over 50 books. He has presented and moderated panels at numerous industry events around the world. #enterpriseai #generativeai #cxotalk
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