Gretchen Stewart knows she doesn’t know it all, always asks why, challenges oversimplified AI stories, champions multi-disciplinary teams and doubles down on data.

Gretchen and Kimberly discuss conflating GenAI with AI, data as the underpinning for all things AI, workflow engineering, AI as a team sport, organizational and data siloes, programming as a valued skill, agentic AI and workforce reductions, the complexity inherent in an interconnected world, data volume vs. quality, backsliding on governance, not knowing it all and diversity as a force multiplier.

Gretchen Stewart is a Principal Engineer at Intel. She serves as the Chief Data Scientist for the public sector and is a member of the enterprise HPC and AI architecture team. A self-professed human to geek translator, Gretchen was recently nominated as a Top 100 Data and AI Leader by OnConferences.

A transcript of this episode is here.

Dr. Chris Marshall analyzes AI from all angles including market dynamics, geopolitical concerns, workforce impacts, and what staying the course with agentic AI requires.

Chris and Kimberly discuss his journey from theoretical physics to analytic philosophy, AI as an economic and geopolitical concern, the rise of sovereign AI, scale economies, market bubbles and expectation gaps, the AI value horizon, why agentic AI is harder than GenAI, calibrating risk and justifying trust, expertise and the workforce, not overlooking Rodney Dangerfield, foundational elements for success, betting on AIOps, and acting in teams.

Dr. Chris L Marshall is a Vice President at IDC Asia/Pacific with responsibility for industry insights, data, analytics and AI. A former partner and executive at companies such as IBM, KPMG, Oracle, FIS, and UBS, Chris’s mission is to translate innovative technologies into industry insights and business value for the digital economy.

Related Resources

• Data and AI Impact Report: The Trust Imperative (IDC Research)

A transcript of this episode is here.

A retrospective sampling of ideas and questions our illustrious guests gifted us in 2025 alongside some glad and not so glad tidings (ok, predictions) for AI in 2026.

In this episode we revisit insights from our guests and, perhaps, introduce those you may have missed along the way. Select guests provide sparky takes on what may happen in 2026.

Host Note: I desperately wanted to use the work prognostication in reference to the latter segment. But although the word sounds cool it implies a level of mysticism entirely out of keeping with the informed opinions these guests have proffered. So, predictions it is.

A transcript of this episode is here.