AI Without the BS

From boardrooms to headlines, vendor pitches to strategy decks, AI is suddenly everywhere. For many leaders, the conversations surrounding AI can be confusing and overwhelming. Is AI really helpful, or just overhyped? This episode of the Forward Thinking Podcast features FCCS SVP of Marketing and Communications Stephanie Barton and Michael Thomas, Chief Data Scientist at Ketchbrook Analytics for a conversation about AI without the BS – by demystifying AI misconceptions, exploring AI opportunities and risks, and understanding how leaders today can implement AI into the broader digital transformation journey strategy.    Episode Insights Include: Common AI misconceptions in farm credit boardrooms AI being used for loan decisioning.  Generative AI should not be used to make individual loan data decisions.  AI being used as a general blanket for an entire organization.  Generalized AI models can be leveraged to increase productivity.  AI cannot be thrown at all customized business processes.  Individual questions cannot effectively be answered by AI.    Positive applications of AI in farm credit Microsoft CoPilot is being used effectively to effectively summarize and generalize document content.  Extensive pdf documents can be simplified with AI assistance.  Large language models can assist with the farm credit system.    Possibilities for further AI adaptation Prompt-driven user dashboards can allow for quicker recall of desired information.  Large language models can bring data together for the user.  Product catalogues chatbots can provide quick answers for users.  Try it and see – AI has countless possibilities that may be helpful.    AI versus machine learning and automation AI usually refers to generative AI.  Machine learning generally outputs one fixed idea.  Generative AI is a newer concept that produce varying lengths of output.  Machine learning helps organizations make better, data-driven decisions.  Generative AI helps organizations be more efficient across a variety of day-to-day tasks. Both have applicability to automation.    Promising applications for AI application in farm credit Increased efficiency is guaranteed with AI.  Sales should be working with a large language model to create a polished sales pitch.  AI can be leveraged to review the work that you have already done.  AI can support, review, and enhance your original thoughts and work.    Avoiding the risks and dangers of AI There is little to no room for error in farm credit, and AI is not fool-proof.  AI offers promises including improved hiring and productivity gains.  Critical thinking skills are at risk from AI, as well as the messy deployment of fully autonomous AI agents. Additional improvements include revolutionary game-changers in medicine and science.  Troubleshooting problems can be addressed more quickly with AI assistance.  Longterm adaptation has to be rolled out in a way that complements the workforce.    This podcast is powered by FCCS.   Resources   Connect with Michael Thomas – Michael Thomas   Get in touch – [email protected]   "AI should be thoughtfully baked into the products you're already using." — Michael Thomas   "AI has to be rolled out in a way that complements the workforce." — Michael Thomas   "Don't be afraid to use your brain first." — Michael Thomas   "Do not focus on the tools of AI or machine learning, focus on the problems that you want to solve." — Michael Thomas