Gartner ThinkCast
Scale AI with Data and Analytics
Dec 10, 2024
Gareth Herschel, a VP analyst at Gartner and expert in AI scaling, shares his insights on enhancing AI initiatives with data and analytics. He outlines five key strategies for aligning AI tools with suitable use cases, emphasizing the need for governance that balances innovation with ethical considerations. The discussion also tackles misconceptions around AI and the importance of having AI-ready data. Gareth encourages engaging with diverse audience attitudes to facilitate smoother AI adoption and promote overall organizational change.
22:01
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Quick takeaways
- Organizations must clearly differentiate between AI and generative AI to choose the right tool for specific project needs.
- Continuous measurement of AI initiatives post-launch is crucial for justifying investments and ensuring stakeholder engagement.
Deep dives
Maximizing AI Opportunities
Organizations should always consider AI as an option when initiating data and analytics projects, but it's crucial to differentiate between AI and generative AI (Gen AI). While both can enhance various initiatives, their applications may vary based on project requirements, emphasizing the importance of choosing the right tool for the job. Leaders are encouraged to explore different approaches, including traditional methods, to evaluate the value AI or Gen AI can bring compared to past methodologies. This thoughtful assessment ensures that not every project default to using AI, preventing wasted investments and focusing on use cases that genuinely benefit from these technologies.
