Dear Colleagues,

It’s Matt Slonaker here, reflecting on our recent Dallas working group discussions this week with big banks, lenders, and solution providers, which yielded three practical, impactful, and remarkably straightforward ideas for immediate implementation. While enterprise-wide AI strategies and large-scale solutions are critical for executive leadership, I believe there’s immense value in exploring smaller, high-leverage initiatives that can be deployed swiftly. These ideas are not only intelligent but also engaging to execute. I encourage you to consider adopting them within your organizations:

Leveraging Meeting Transcripts as a Strategic Asset: One CEO shared an innovative practice of recording and transcribing all company meetings, consolidating these transcripts into a single, searchable repository. Previously, this data was unwieldy, but with AI, it’s become a powerful resource. Operating within a Google Suite environment, this leader utilizes Google’s Gemini AI to analyze years of discussions, uncovering patterns that would otherwise remain hidden. This transforms organizational memory into a dynamic, searchable dataset—a significant asset for strategic planning and decision-making.

Predicting Hiring Outcomes with AI Insights: Following a challenging termination due to behavioral issues, the same CEO revisited the employee’s recorded job interview transcript using AI analysis. The review revealed a critical oversight: excessive use of “I” versus “we” language, a potential red flag. This sparked an idea to categorize historical interview transcripts into performance groups—high performers, average contributors, and problematic hires—then apply AI to evaluate new candidates’ interviews against these patterns. This approach enhances hiring decisions by identifying trends that human evaluators might miss. While there are potential challenges to address, this method merits careful exploration.

Fostering Collaborative AI Engagement: Another CEO took a refreshingly practical approach by feeding three years of company safety data from Excel into ChatGPT to forecast outcomes under various sales and production scenarios. What stood out was the collaborative execution: the analysis was conducted alongside the production leadership team, enabling real-time questioning and discussion of AI-generated insights. The true value emerged not solely from the data but from the strategic conversations it ignited among operational leaders. This underscores that AI is most effective when integrated into collaborative, team-driven processes.

I hope these ideas inspire action within your teams. Wishing you a productive and restful weekend.

Best regards,
Matt Slonaker