Kim sat down with Drew Beach of BizStream on the Tech Week Live podcast to talk about why AI needs more than excitement and adoption. Kim’s perspective is not simply “anti-AI.” Rather, her point is that organizations need to understand AI’s limitations and use it with intention. The conversation covers human-in-the-loop practices, cognitive offloading, AI-generated content, authenticity, company policies, and why relying too heavily on AI can create more problems than it solves.
AI Is a Tool, Not a Lifeline
It is not enough to hand someone an AI account and assume they know how to use it well. Companies need to ask what the tool is being used for, what information can safely be entered, who reviews the output and who is ultimately responsible for the final result.
Kim also pushed back on the idea that selecting the “right” tool solves the problem. When someone asked her what AI tools she recommended, her answer was that the tool itself is not the most important issue. Any AI system needs guardrails, training and oversight. The key question is not just “Which AI should we use?” It is “How are we using it and who is checking the work?”
The Hallucinations, Cognitive Surrender and AI Slop
Kim also discussed two related concepts: cognitive offloading and cognitive surrender. Cognitive offloading is using tools to handle mental tasks, like using a calculator or GPS. This can be efficient. Cognitive surrender is when people stop thinking critically and let the tool do the thinking for them. Kim warned that if we stop using mental muscles for writing, strategy or research, they get weaker.
The conversation also touched on “AI slop,” or low-quality AI-generated content. Kim shared an example where she hired a company for a lead generation campaign and spent over $15,000, only to receive content that appeared AI-generated and lacked her brand’s voice. She had to rewrite everything. Drew noted that this is a human accountability problem: the tool may generate weak content, but the user chose to publish it.
AI is a powerful tool, but it’s not a substitute for judgment, accountability or critical thinking. Organizations that treat AI adoption as a checklist item are setting themselves up for the kind of costly, off-brand “AI slop” Kim described. The organizations that get it right are the ones that pair AI with clear policies, human oversight and ongoing training, keeping people firmly in the loop rather than outsourcing their thinking to the machine.
