Juan Lavista Ferres, Corporate Vice President and Chief Data Scientist at Microsoft, dives into securing executive buy-in for AI projects that prioritize social good. He discusses the significance of clear communication and starting with small, impactful initiatives. Juan highlights criteria for selecting projects with high societal benefits while addressing misconceptions about AI's role in solving complex issues. He emphasizes understanding AI's limitations and the importance of aligning initiatives with core business values to drive sustainable success.
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Quick takeaways
Effective communication about AI's potential and limitations is essential for setting realistic goals and managing expectations.
Starting with smaller, successful AI projects can build confidence and momentum for larger initiatives that benefit society.
Deep dives
Understanding AI's Capabilities and Limitations
Many organizations struggle with understanding what problems can effectively be addressed with AI, often leading to irrational expectations about its capabilities. It is crucial to clearly communicate both the potential and limitations of AI technologies so that teams can approach their projects with realistic goals. Demonstrating successful applications of AI in various contexts helps to build a better understanding and can inspire innovative thinking in problem-solving. This groundwork creates a more informed environment where stakeholders can recognize the specific challenges that AI can tackle, paving the way for more strategic initiatives.
The Importance of Starting Small for Success
Starting with smaller, manageable projects can lead to significant early wins that help build momentum for larger AI initiatives. Identifying 'low-hanging fruit' projects that demonstrate tangible results increases buy-in from other teams and stakeholders. Focus on projects with a higher likelihood of success fosters confidence and supports the gradual integration of AI into critical business operations. This strategy not only develops the capacity to handle more complex AI projects in the future but also showcases the immediate benefits of AI technologies.
Prioritizing Projects for Societal Impact
When selecting AI projects, prioritizing those that can deliver significant societal impact is essential, especially when resources are limited. This involves evaluating the feasibility of data access and ensuring that the chosen projects align with the capabilities of the organization. Some proposals may present excellent ideas with high societal value but are ultimately unsuitable for AI solutions due to a lack of data or inherent unpredictability of the outcomes. By filtering out projects that do not meet these criteria, organizations can better allocate resources toward initiatives that will drive meaningful change.
Today’s guest is Juan Ferres, Corporate Vice President and Chief Data Scientist at Microsoft. Juan returns to the program to explore how to win buy-in for sustainable AI projects. As a leader in the AI4G Lab and author of the new book AI for Good, Juan shares insights on navigating complex digital transformations, particularly when it comes to initiatives where the return on investment is philosophical rather than immediately measurable. Throughout the episode, Juan and Emerj Senior Editor Matthew DeMello discuss the challenges of managing up and driving forward AI innovations that aim to benefit society as a whole. If you’re interested in unlocking our AI best practice guides, frameworks for AI ROI, and specific resources for AI leaders, visit emerj.com/p1.
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