Answerable AI is a podcast by J.M. Wofford based on a four-paper research series about how organizations measure, govern, and defend artificial intelligence in the real world. Each episode explores AI capability, compliance, maturity, risk, and accountability in clear practical terms.
Have a question or perspective on this episode? Send me a message. What if your AI gives you the wrong answer—not because the technology failed, but because the information behind it wasn't reliable? In the first installment of Behind the AI, JM Wofford takes us beneath the polished interfaces and impressive demonstrations to explore something most people never see: the data systems that feed artificial intelligence. Through a relatable business story, we explore how information moves, what h...
18 Oct 2026
Who Holds the Switch?
Have a question or perspective on this episode? Send me a message. Who Holds the Switch? | An Answerable AI Special When technology becomes essential, does the ability to control it create responsibilities that go beyond the contract? The Ukraine–Starlink controversy raises a question that reaches far beyond satellite communications: Who holds the power to change, restrict, or withdraw technology that others depend on? In this standalone special of Answerable AI, JM Wofford examines the often...
16 Oct 2026
Before You Sign: What an AI Vendor Should Prove
Have a question or perspective on this episode? Send me a message. The demonstration was impressive. The answers sounded confident. But before you sign, what should an AI vendor actually be able to prove? In this episode of Answerable AI, JM Wofford follows a fictional retailer through an AI purchasing decision, exploring the evidence behind performance claims, human oversight, governance, and incident response. What does an accuracy score really tell you? Can the person reviewing an AI-gener...
10 Oct 2026
When AI Becomes the Source of Truth, Who Checks the Facts?
Have a question or perspective on this episode? Send me a message. What happens when accurate data leads to the wrong conclusion? Organizations have spent years establishing a source of truth. But as artificial intelligence increasingly interprets, summarizes, and transforms enterprise information, a new challenge is emerging: How do we know when an AI-generated answer deserves our trust? In this episode of Answerable AI, JM Wofford explores a fictional retail company preparing for its busies...
7 Oct 2026
You Clicked Approve. Was It Your Decision?
Have a question or perspective on this episode? Send me a message. A human approved the recommendation. But how much of the decision had AI already shaped? In this episode of Answerable AI, JM Wofford introduces a debate between two AI-generated voices exploring human oversight, independent judgment, and accountability. The discussion connects to JM’s research on what AI measurements actually prove. A recorded approval establishes that someone authorized an action. It tells us much less about...
4 Oct 2026
When AI Looks You in the Eye
Have a question or perspective on this episode? Send me a message. When AI feels like someone who understands you, how does that change what you trust? In this episode of Answerable AI, JM Wofford explores Tavus, its evolution into real-time conversational video, and its recently announced Griffin research preview. Drawing on her research and work helping clients assess AI implementations, JM examines the space between a convincing interaction and evidence that a system deserves our confidenc...
2 Oct 2026
When AI Goes Rogue, Who Answers for It?
Have a question or perspective on this episode? Send me a message. “Rogue AI” makes a compelling headline. But it may be the wrong governance question. As AI moves from generating answers to taking actions, risk no longer sits neatly inside the model. An agent can act through identities, permissions, tools, APIs, data, and business processes, creating consequences far beyond where the original risk began. In this episode of Answerable AI, JM Wofford explores what happens when every technical ...
25 Sept 2026
The Control Exists. But Did It Actually Reduce the Risk?
Have a question or perspective on this episode? Send me a message. AI governance is getting better at proving that controls exist. But proving a control exists isn't the same as proving it reduced the risk. In this episode of Answerable AI, JM Wofford examines the gap between governance activity and actual risk reduction. What does a passing control really tell us? What happens when risk moves beyond the model into agents, tools, data, and business processes? And once the controls have operat...
22 Sept 2026
The Compliance Lens - When Passing the Test Isn't the Same as Being Safe
Have a question or perspective on this episode? Send me a message. What does it actually mean when an AI system is described as compliant? In this episode of Answerable AI, J.M. Wofford examines the limits of compliance as a measure of AI safety and performance. An organization can complete required reviews, document controls, approve the use case, assess the vendor, and satisfy policy requirements... and still have an AI system that performs poorly or produces an unacceptable outcome. That d...
22 Sept 2026
Who Answers for What AI Does?
Have a question or perspective on this episode? Send me a message. When AI influences a decision, who is actually accountable for the outcome? In this episode of Answerable AI, J.M. Wofford examines the gap between involvement and accountability in AI governance. An AI system may involve vendors, technology teams, data owners, business leaders, legal, compliance, and human decision-makers, yet an organization can still struggle to answer a basic question: Who answers when the system produces ...
21 Sept 2026
The 80 Percent AI Failure Problem: What Organizations Are Measuring Wrong
Have a question or perspective on this episode? Send me a message. Enterprise AI failure is often treated as a technology problem. This episode asks whether the deeper problem is how organizations define success, measure readiness, assign accountability, and govern AI after deployment. In the first full episode of Answerable AI, J.M. Wofford examines the research behind Why 80 Percent of Enterprise AI Fails and the organizational conditions that separate experimentation from durable enterpris...
20 Sept 2026
Welcome to Answerable AI
Have a question or perspective on this episode? Send me a message. Answerable AI is a research-driven podcast by J.M. Wofford exploring how organizations measure, govern, and defend artificial intelligence in practice. Based on a four-paper research series, the show examines AI capability, compliance, maturity, risk, and accountability, and why those distinctions matter when organizations move AI from experimentation into real-world use. Answerable AI asks a simple question: when an organizat...
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