Where to start is the number one barrier
The hosts shared results from a LinkedIn poll asking why B2B executives get stuck on AI. The top answer, chosen by 36% of respondents, was that they do not know where to start. Other options included not seeing business value, fearing disruption, and finding AI too complicated, but uncertainty about first steps was the most common response.
Brian noted that this matched what he was hearing at regional roundtables. Companies are under pressure from boards and leadership to invest in AI, but the question of what to invest in remains unclear.
Four states of AI adoption
The guest for the episode was Dr. Lisa Palmer, a futurist, author, and former Gartner executive who now runs an AI advisory firm. She identified four states that organizations typically find themselves in with AI.
The first is trying to figure out where to get started. The second is having started something, experienced mixed results, and now being stuck. The third, which she said applies to only about 5% of organizations according to a recent MIT study, is being ready to scale because things are working. The fourth is having a team that is afraid and either overtly or covertly resisting.
Your team is just afraid, and they are either overtly or covertly resisting.
Dr. Lisa Palmer
Andy added that the fear component is real. At roundtables, when the conversation turns to what AI means for jobs, he has seen the room go quiet and people become reluctant to share their views even in a confidential setting.
The mindset component
Dr. Palmer’s framework for getting unstuck has three parts: mindset, strategy, and action. On mindset, she emphasized four principles.
First, focus on business value. She said she is tired of hearing CEOs complain about lack of ROI from AI when the projects they funded were never designed to generate returns. Second, move with speed but apply rigor. Doing nothing is not an option because competitors and the entire business ecosystem are changing. Third, simplify. The winners and losers in AI are not yet clear, so complex implementations will be painful to unwind. Fourth, avoid over-automation. She noted that companies are already facing fines and customer satisfaction problems from automating too aggressively.
Strategy: focus on customers and scope small on data
On strategy, Dr. Palmer advised starting with how AI can make things better for customers. She also emphasized breaking down silos. Organizations where people hoard information and do not collaborate will struggle with AI, which requires working across functions.
Data readiness was a major theme. She described boardrooms where executives were angry to learn that years of data investment had not made them ready for AI. The issue is that AI data readiness is different from general data hygiene. Her advice was to scope small: identify the specific data needed for a particular use case rather than trying to fix everything.
Please do not boil the ocean. Identify your business use case and maybe you just need ten pieces of data, not a thousand.
Dr. Lisa Palmer
Action: you cannot delegate learning
The action component was about change management. Dr. Palmer said you have to capture hearts before you can capture minds, and the way to do that is to show rather than tell. Visualization tools and hands-on demonstrations are more effective than slide decks.
Her strongest point was that executives cannot delegate learning. Leaders who have not personally tried vibe coding tools, agent-building platforms, or even basic chatbots are not equipped to lead their organizations through AI adoption.
You cannot delegate learning. If you think you can have somebody else learn this for you, you are going to fail.
Dr. Lisa Palmer
She shared an example of a CIO who built something in Claude Code two weeks earlier and said it changed how he leads his team. The hands-on experience reset his understanding of what is possible.
Will AI create or destroy jobs?
Dr. Palmer said she believes AI will result in net job creation, though the distribution of jobs will shift. She noted that coding jobs are not disappearing because vibe coding is creating significant cleanup work that requires skilled developers. However, she expressed concern about entry-level and heavily task-oriented roles.
Andy closed by noting that one roundtable participant said their company measures the cost of inaction, quantifying opportunity cost in a way that most organizations do not. Both hosts suggested this should be standard practice.