Pondering AI

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.

Masheika Allgood delineates good AI from GenAI, outlines the environmental imprint of hyperscale data centers, and emphasizes AI success depends on the why and data. 
 
Masheika and Kimberly discuss her path from law to AI; AI as an embodied infrastructure; forms of beneficial AI; if the GenAI math maths; narratives underpinning AI; the physical imprint of hyperscale data centers; the fallacy of closed loop cooling; who pays for electrical capacity; enabling community dialogue; starting with why in AI product design; AI as a data infrastructure play; staying positive and finding the thing you can do. 
 
Masheika Allgood is an AI Ethicist and Founder of AllAI Consulting. She is a well-known advocate for sustainable AI development and contributor to the IEEE P7100 Standard for Measurement of Environmental Impacts of Artificial Intelligence Systems. 
Related Resources 
Taps Run Dry Initiative (Website) 
Data Center Advocacy Toolkit (Website) 
Eat Your Frog (Substack) 
AI Data Governance, Compliance, and Auditing for Developers (LinkedIn Learning) 
A Mind at Play: How Claude Shannon Invented the Information Age (Referenced Book) 
A transcript of this episode is here.

Kati Walcott differentiates simulated will from genuine intent, data sharing from data surrender, and agents from agency in a quest to ensure digital sovereignty for all.
Kati and Kimberly discuss her journey from molecular genetics to AI engineering; the evolution of an intention economy built on simulated will; the provider ecosystem and monetization as a motive; capturing genuine intent; non-benign aspects of personalization; how a single bad data point can be a health hazard; the 3 styles of digital data; data sharing vs. data surrender; whether digital society represents reality; restoring authorship over our digital selves; pivoting from convenience to governance; why AI is only accountable when your will is enforced; and the urgent need to disrupt feudal economics in AI.
 
Kati Walcott is the Founder and Chief Technology Officer at Synovient. With over 120 international patents, Kati is a visionary tech inventor, author and leader focused on digital representation, rights and citizenship in the Digital Data Economy.
Related Resources
The False Intention Economy: How AI Systems are Replacing Human Will with Modeled Behavior (LinkedIn Article)
A transcript of this episode is here.