Jon Groth on Expert Vetting, Retainer Tips & Courtroom Credibility

What happens when your expert witness backs out right before trial? Or when they rely on ChatGPT and get excluded?In this explosive episode of On the Stand, host Ashish Arun sits down with veteran trial lawyer Jon Groth to explore how expert witnesses can make or break a personal injury case—and how AI is complicating everything.👀 What to Expect:The real-life story of an expert who ghosted a trial last-minuteWhy the wrong expert can sink your case—and your clientHow Jon evaluates and vets expert witnessesWhy a Stanford professor was excluded for using ChatGPTHow to protect your case from AI hallucinationsWhat retainer agreements should always includeThe balance between credibility and marketing for expert witnessesTips for attorneys working with experts across borders and time zones📝 Key Highlights:🔥 90%+ of PI cases never go to trial—so why do experts still matter?⚠️ The red flags Jon looks for when hiring an expert🧠 Why experts need teaching skills more than technical jargon🤖 AI in the courtroom: dangerous shortcut or powerful tool?📜 What every expert should know about Wisconsin disclosure rules💡 Best practices for document retention, communication, and transparency⏱️ Timestamps00:00 – Intro: From jazz saxophonist to trial lawyer03:30 – How experts impact litigation outcomes08:15 – The expert that backed out: what happened13:00 – Hiring across borders: building a 30+ person law firm17:40 – Vetting expert witnesses: what matters22:05 – The Stanford professor & ChatGPT disaster27:00 – AI risks and how Jon’s firm uses “AI in a box”31:20 – Retainer agreement must-haves35:10 – Should experts advertise? Jon’s take40:00 – Final thoughts + where to find Jon📌 Subscribe for more episodes with legal minds, litigators, and tech pioneers reshaping the courtroom.👍 Like, 💬 comment, and 🔔 hit the bell so you never miss an episode.#ExpertWitness #PersonalInjuryLaw #TrialLawyer #LegalPodcast #CourtroomAI #LitigationStrategy #LegalTech #ChatGPTInLaw #OnTheStandPodcast