Technology Implementation

On this Me, Myself, and AI bonus episode, MIT CISR researcher Barbara Wixom shares insights from 30 years in the field.

The goal isn’t eliminating technical debt but managing it, focusing on the highest-value fixes, and supporting innovation.

This Me, Myself, and AI episode features the NFL’s Jeff Miller in conversation with hosts Sam Ransbotham and Shervin Khodabandeh.

AI’s ability to create value rests on the philosophy determining how and what it learns.

For optimal business innovation, leaders must take a balanced approach to applying generative and analytical AI.

Organizations need to address five key factors to scale AI for tangible business outcomes.

AI experts Thomas H. Davenport and Randy Bean explain the top AI trends leaders should watch in the new year.

This Me, Myself, and AI episode features Heineken’s Ronald den Elzen in conversation with hosts Sam Ransbotham and Shervin Khodabandeh.

This Me, Myself, and AI bonus episode features previous speakers and synthesis from hosts Sam Ransbotham and Shervin Khodabandeh.

The second Artificial Intelligence and Business Strategy report of 2024 looks at how organizations that combine organizational learning and AI learning are better prepared to manage uncertainty.

Applying a comprehensive cost-benefit analysis to generative AI use cases will highlight where the technology pays off.

Two frameworks can help organizations identify potential harms posed by algorithms, AI tools, or large language models.

Prompting users to spot errors when using generative AI to complete reports improves the accuracy of the final product.

Learn why humans miss generative AI mistakes and how AI speed bumps help, in this short video.

Experts debate how effectively organizations are adjusting risk management practices to govern AI.

Business leaders can identify and avoid flawed AI models by employing statistical methods and statistics experts.

Learn three principles for reorganizing work around AI.

Watch this short video to learn more about how AI changes the rules of workforce management.

To succeed with machine learning, manage projects as business initiatives, not technology projects.

Two automation initiatives succeeded by scoring potential processes and combining technical and process knowledge.