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The Role of Change Management in AI

Knownwell

AI Knowhow Episode 62 Summary

  • Laying out a vision for how a technology like AI should be utilized in an organization is a precursor to successful innovation
  • Understanding user wants and needs is a vital, yet often overlooked, step in the change management process
  • To drive innovation with AI, there needs to be a centralized, federated place for data that everyone has access to

In the rapidly evolving world of Artificial Intelligence, change management has emerged as a vital competency. It’s a necessity to ensure that all members of an organization are on board an AI transformation, not just the early adopters. And as AI technologies become more integrated into modern business practices, bringing everyone along on this journey is crucial for achieving transformative success.

Expert Interview: Andrew DeBerry on The Importance of Change Management in AI

Andrew DeBerry, a member of the Knownwell AI Advisory Board, highlights his experiences with change management while working on AI initiatives at companies like Microsoft, AWS, Meta, and Google X. Andrew explains that successful AI implementation depends on integrating new concepts into existing infrastructures, adapting processes, and developing a culture that embraces innovation. For example, his work with X’s Bellwether Project, which TIME just named one of the best inventions of 2024, showcases how AI can transform disaster and emergency management by making data processing more efficient and informing strategic planning.

Transforming Through AI Innovations

Organizations striving for AI-driven transformation must recognize the barriers to change management and devise strategies to overcome them. Andrew identifies the critical factors for innovation: having a clear vision, leadership that champions AI, and individuals who are open to adopting new technologies.

Those companies who have the most success will be those who are able to both reimagine what their business can look like and rapidly adjust their existing worfklows to accommodate such a shift. “This is a new time of reimagining what’s possible,” Andrew says. “But fast following that with, well, what can we do today? And then starting to couple those together.”

For AI specifically, Andrew recommends that organizations focus on a federated approach to data management so that all teams working with AI have access to the same data. This includes utilizing centralized data models and a single data team that can permeate use cases across an enterprise.

What’s the AI Knowhow Team Thankful for This Year?

For a special version of our AI Knowhow roundtable, Courtney, David, and Mohan share a few things they’ve been most thankful for in the AI space this year. Courtney points to the wave of AI transcription tools like Otter.AI, Fireflies, Trent, and Supernormal that are taking care of the painstaking work of writing meeting summaries and follow-up items that were formerly the job of humans.

David says he’s grateful for ChatGPT’s advanced reasoning models’ rapidly advancing capabilities. He recently used the GPT-o1 preview to help craft OKRs for the entire company, and he was blown away by how thorough o1’s response was when he asked for help creating them.

Mohan cites medical breakthroughs in AI-powered drug discovery, which made advancements in 2024 that he sees driving big improvements in quality of life down the line as the thing he’s most thankful for.

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