Everyone is asking "can AI do this?" But that's the wrong question. The right questions are: does it have the right knowledge, the right tools, and clear enough instructions to do the job? And is your enterprise actually ready for what comes after?In this episode, Jon Myer is joined by Christopher and Diego from Epi-use — two experts in AI architecture, governance, and enterprise implementation — for a frank conversation about why so many agentic AI projects fail, what the successful ones have in common, and why the real bottleneck is almost never the AI itself.Topics covered:Why most companies are implementing AI for the wrong reasons and asking the wrong questionsThe difference between generative AI and agentic AI — vending machine vs. sous chefPilot purgatory — why AI projects get stuck and never make it to productionWhy the AI part is usually the easiest part and the foundation is the heavy liftHow governance becomes the enabler not the obstacle when done rightThe difference between human in the loop and human on the loop — and why it matters for designA real-world case study — a bank that ran 350 agentic AI use cases and what actually workedDo we want true autonomy or accountability? The answer is both⏱️ Timeline0:00 — Introduction — Reframing agentic AI as an evolution that demands first principles thinking0:50 — What companies are getting wrong at the very start — the fascination phase2:13 — Is agentic AI truly novel or just a rebrand of what we already had3:03 — The right questions to ask — knowledge context tooling and instruction4:51 — Pilot purgatory — AI projects stuck in QA that never make it to production5:46 — First principles have not changed — what problem are we solving and what outcome do we want8:50 — Are we implementing true agentic AI or just rebranding existing workflows9:59 — Generative AI as a vending machine vs agentic AI as a sous chef11:51 — Model in the loop — when you are really just calling a more sophisticated API13:33 — Where agentic AI adds the most value — exception handling in enterprise workflows16:40 — Governance as an enabler — why dirty data is a governance failure not an AI failure18:19 — What feels familiar and what feels genuinely new about AI adoption today20:29 — The importance of foundation before implementation — and the rush that bypasses it23:29 — 40% of AI projects will fail by 2027 — and the bank that ran 350 use cases25:18 — What actually determines AI success vs quiet failure26:28 — Human in the loop vs human on the loop — why design matters from day one29:41 — Agentic AI is a business project not a technology project31:05 — Do we want true autonomy or accountability? The answer is both🔔 Don't forget to Like, Subscribe, and hit the notification 🔔 ✔ Subscribe: https://www.youtube.com/jonmyer/?sub_confirmation=1📱 Social Media Twitter: https://twitter.com/_JonMyerWebsite: https://jonmyer.comLinkedIN: https://www.linkedin.com/in/jon-myer/Spotify: https://open.spotify.com/show/0wjJzdIwctq4o4pTXM2KSFLike my sounds? Here's my audio source: https://www.epidemicsound.com/referral/fj9o9k#aws #awscloud #podcast #podcasting #costoptimization #finops #cloudcost #cloudoptimization

Data migrations in healthcare have a reputation — difficult, delayed, expensive, and sometimes never fully completed. Years after an EHR go-live, organizations are still running legacy support contracts, paying for systems they should have left behind, and leaving clinical data stranded in systems no one can access.In this episode of Health Reimagined, host Jon Myer (Myer Media, powered by Ingram Micro) sits down with Kaitlin from Quoris — a 26-year-old women-led healthcare IT consulting and staffing firm operating in 10 countries — to talk about what it actually takes to move documentation and data cleanly, on time, and without disrupting patient care.🔗 Learn more at Quoris.com🏥 EHR implementation, optimization, and data migration for healthcare systems across 10 countries — with a true partnership model that doesn't walk away after go-live📋 FastLane — Quoris's proprietary methodology that keeps Epic gallery migrations on time and on target without adding third-party tools or extra layers to the tech stack🔒 Data security and clinical access during migration — clinicians and HIM teams can access patient information throughout the extraction process🌍 Global reach with a local feel — navigating regulatory environments, cultural differences, and relationship-driven healthcare across international markets⏱️ Timeline0:00 — Introduction — Legacy documentation systems and what it takes to move them without disrupting the business0:27 — Who Quoris is — 26 years in healthcare IT across 10 countries1:10 — How Quoris operates in a saturated healthcare IT market — true partnership over product delivery1:59 — Making global healthcare IT work across borders regulations and cultures3:18 — Quoris as a women-led organization and what that brings to the industry5:35 — What outside firms still get wrong about healthcare after 26 years6:20 — Why data migrations get stuck and how FastLane was built to solve that7:47 — What FastLane actually does — structured approach automation and proprietary methodology8:09 — What a typical engagement looks like — up and running within two weeks of contract signature9:12 — Data in multiple places is fine — on-prem hybrid and cloud all supported9:21 — The right questions to ask when evaluating a migration partner — and what good answers look like🔔 Don't forget to Like, Subscribe, and hit the notification 🔔 ✔ Subscribe: https://www.youtube.com/jonmyer/?sub_confirmation=1📱 Social Media Twitter: https://twitter.com/_JonMyerWebsite: https://jonmyer.comLinkedIN: https://www.linkedin.com/in/jon-myer/Spotify: https://open.spotify.com/show/0wjJzdIwctq4o4pTXM2KSFLike my sounds? Here's my audio source: https://www.epidemicsound.com/referral/fj9o9k#aws #awscloud #podcast #podcasting #costoptimization #finops #cloudcost #cloudoptimization

Technology is changing every few weeks in healthcare — and health system leaders are expected to keep up, upskill their entire workforce, govern AI responsibly, and still deliver measurable outcomes. That is the reality for Sha, CDIO at Baptist Health of South Florida.In this episode, Sha sits down to share his unfiltered perspective on what it actually takes to lead digital transformation at scale — from the decision to go all-in on Epic without customization, to the data quality principles underpinning their AI strategy, to why agentic AI access control is still unsolved, and whether he would let a robot operate on him in five years.Topics covered:Leading technology transformation at Baptist Health of South FloridaWhy technology is changing every few weeks and what that means for workforce upskillingThe two foundational priorities — AI literacy across the organization and robust governanceWhy Baptist chose Epic and the principle of staying close to the foundation⏱️ YouTube Timeline0:00 — Introduction — Meet Sha CDIO at Baptist Health of South Florida0:39 — The intensity and excitement of leading transformation at Baptist Health1:05 — Technology is changing every few weeks — what that means for leaders2:09 — Core principles for driving measurable outcomes in a fast-moving environment2:40 — Infrastructure foundation upskilling and why quarterly training is already dead3:38 — AI governance — non-deterministic by nature and not easy to implement4:20 — Making sure all stakeholders are represented in the governance structure4:50 — The challenge of AI adoption at scale — turning traditional workers into AI-enabled workers5:55 — The Epic decision — choosing a foundation and sticking close to it6:05 — Why Baptist selected Epic and the principle of minimal customization7:07 — Using Epic's best practice data to structure workflows faster and more stably8:13 — Top AI use cases — ambient listening scheduling imaging and clinical decision support9:42 — Automated workflows reducing patient wait times for urgent studies10:35 — Provider burnout is real and clinical decision support is the next game changer11:24 — The three data challenges — quality at the source velocity and security12:45 — Five years of data investment that prepared Baptist for the current AI wave13:10 — Healthcare is the most attacked vertical — the cybersecurity conversation14:02 — Layered security prevention monitoring and the human element as the weakest link14:54 — Resilience and business continuity beyond just security tooling15:59 — Built-in security vs bolted-on security as agentic AI sprawls across systems16:49 — Agentic AI expands the attack surface and access control is still not solved17:17 — What happens when your workforce depends on agents that suddenly go down17:52 — Three-year prediction — end-to-end workflow automation at a scale not yet appreciated19:20 — Who captures the capacity freed by automation will define the next generation of healthcare20:11 — Would you let a robot perform surgery on you in five years?20:17 — Yes — and why LASIK proves the model for what comes next21:31 — A message of gratitude to nurses physicians and every patient-facing provider22:14 — Technology and IT exist only to support the people who actually deliver care23:33 — Closing remarks — leaders drive the change and AI is there to enable better outcomes🔔 Don't forget to Like, Subscribe, and hit the notification 🔔 ✔ Subscribe: https://www.youtube.com/jonmyer/?sub_confirmation=1📱 Social Media Twitter: https://twitter.com/_JonMyerWebsite: https://jonmyer.comLinkedIN: https://www.linkedin.com/in/jon-myer/Spotify: https://open.spotify.com/show/0wjJzdIwctq4o4pTXM2KSFLike my sounds? Here's my audio source: https://www.epidemicsound.com/referral/fj9o9k#aws #awscloud #podcast #podcasting #costoptimization #finops #cloudcost #cloudoptimization

A modern hospital can have 40,000 endpoints — laptops, lab stations, nursing workstations, medical IoT devices — and a razor-thin IT team responsible for keeping every single one of them patched, compliant, and secure. Miss just one, and attackers will find it.Recorded live at HIMSS 2026, this conversation features an IT specialist from HCL Software breaking down how BigFix IO is helping healthcare organizations move from reactive patching to proactive, automated endpoint management — at scale, across heterogeneous environments, and with AI-powered remediation bots that work around the clock.Topics covered:Why healthcare IT environments are uniquely complex and difficult to secureThe ransomware threat and why unpatched devices are the entry point attackers exploitHow BigFix IO provides complete asset visibility and compliance across 100+ operating systemsA real customer case study — from 60% to 97% compliance across 40,000 endpoints in two monthsPatching 100,000 endpoints in under an hour with smart scheduling and rollback policiesManaging legacy systems and heterogeneous environments in healthcareHow AI and agentic bots are automating level zero and level one IT tasksConversational bots for patients, IT provisioning, and onboarding through chat, mobile, and voiceThe future of AI in healthcare IT operations⏱️ YouTube Timeline0:00 — Introduction — Live at HIMSS 2026 with HCL Software's IT specialist Rajneesha0:26 — The state of healthcare IT — 40,000 endpoints and a thin IT team0:41 — Why managing and securing a modern hospital environment is a nightmare1:37 — Patching at scale — why it is far more complex than clicking a system update1:50 — Legacy systems, compliance documentation, and the cost of missing a single device2:34 — How attackers exploit unpatched healthcare environments and why downtime is a patient safety issue3:24 — Introducing BigFix IO — a single platform for compliance, visibility, and automation4:30 — BigFix is industry-agnostic — built for speed scale and complete compliance intelligence5:03 — Real customer case study — 60% to 97% compliance across 40,000 endpoints in two months6:15 — Heterogeneous environments — managing 100 plus operating systems including legacy systems6:30 — Patching 100,000 endpoints in under an hour with smart scheduling and rollback policies7:56 — AI in healthcare IT — where the technology has matured and what is now possible8:10 — Agentic bots for auto-remediation and reducing the burden on lean IT teams9:01 — Conversational bots for patients and IT users via chat mobile and voice10:19 — Final thoughts — endpoints are both the biggest opportunity and the biggest vulnerability10:33 — Reaching 98 to 99% compliance in healthcare with BigFix IO🔔 Don't forget to Like, Subscribe, and hit the notification 🔔 ✔ Subscribe: https://www.youtube.com/jonmyer/?sub_confirmation=1📱 Social Media Twitter: https://twitter.com/_JonMyerWebsite: https://jonmyer.comLinkedIN: https://www.linkedin.com/in/jon-myer/Spotify: https://open.spotify.com/show/0wjJzdIwctq4o4pTXM2KSFLike my sounds? Here's my audio source: https://www.epidemicsound.com/referral/fj9o9k#aws #awscloud #podcast #podcasting #costoptimization #finops #cloudcost #cloudoptimization

Healthcare call centers are still growing — even as patient portals improve. Patients call to confirm appointments they already know about, reschedule across multiple departments, and check on billing. They wait on hold. They get transferred. They hang up.In this episode of Health Reimagined, host Jon Myer (Powered by Myer Media) sits down with Jeff from SoundHound AI to unpack what agentic AI actually means for healthcare, why voice is the future of the patient experience, and how health systems are using conversational AI to handle complex multi-step tasks — without a single hold time or transfer.🔗 Learn more at soundhound.comTopics covered:Why healthcare call centers keep growing no matter how good patient portals getThe difference between old IVR systems and modern agentic voice AIWhat the first wave of healthcare chatbots got wrong — and what the industry learnedSoundHound's streaming voice recognition engine and real-time word processingThe hybrid model — deterministic authentication plus free-flowing agentic AIHow one call can now handle scheduling, billing, and IT support without transfersCall center attrition rates of 25 to 35% and how AI solves the staffing problemPractical advice for healthcare organizations taking their first step into agentic AIStarter packs — highest volume lowest complexity use cases first for fast ROIWhat makes a healthcare-specific agentic voice platform different from wrapping an LLM⏱️ YouTube Timeline0:00 — Introduction — Agentic AI is no longer just answering questions it is taking action0:32 — Meet Jeff from SoundHound AI at HIMSS0:34 — Where the real AI opportunity sits in healthcare — the call center1:22 — Why patients still pick up the phone even with patient portals2:29 — The shift in trust — from skepticism to expecting a digital agent to answer3:32 — After hours calls multilingual support and not waiting on hold3:57 — How agentic AI handled an earlier appointment without a single hold4:23 — Rescheduling to the day after St. Patrick's Day — natural language in action4:53 — What the first wave of healthcare AI got wrong — chatbots IVR and basic automation5:46 — The move from scripted flows to continuous natural conversation6:08 — One call for scheduling billing and IT without transfers or reauthentication7:39 — Streaming voice recognition — processing each word in real time like a human8:34 — SoundHound's background in restaurants and drive-throughs and why it matters for healthcare9:01 — Where voice fits in the broader healthcare landscape and why vendor sprawl is a problem10:11 — IVR vs agentic AI — MapQuest directions vs Waze navigation11:04 — The hybrid model — deterministic authentication plus free-flowing agentic conversation11:28 — Security identity verification and giving the right patient the right information12:09 — The biggest pain points in healthcare call centers — attrition wait times and growth13:10 — Practical advice for healthcare organizations taking their first step into agentic AI13:57 — Starter packs — highest volume lowest complexity use cases for fast provable ROI14:47 — What makes a healthcare-specific voice AI platform different from just wrapping an LLM16:11 — Measurable KPIs containment rates and proving value year over year🔔 Don't forget to Like, Subscribe, and hit the notification 🔔 ✔ Subscribe: https://www.youtube.com/jonmyer/?sub_confirmation=1📱 Social Media Twitter: https://twitter.com/_JonMyerWebsite: https://jonmyer.comLinkedIN: https://www.linkedin.com/in/jon-myer/Spotify: https://open.spotify.com/show/0wjJzdIwctq4o4pTXM2KSFLike my sounds? Here's my audio source: https://www.epidemicsound.com/referral/fj9o9k#aws #awscloud #podcast #podcasting #costoptimization #finops #cloudcost #cloudoptimization

Hospitals want to be safe and open at the same time — welcoming to patients, families, and staff, but protected from weapons, wandering patients, drug diversion, and operational waste. That's exactly the problem Vision AI was built to solve.Recorded live at HIMSS 2026 in Las Vegas, this fireside chat features Matt Benetti, CMO at Vaidio, and Todd Larson, a consultant running the Transformation Center at Honor Health. Todd brings a rare combination of law enforcement experience and hospital innovation leadership to a wide-ranging conversation about how AI-powered cameras are moving from passive data storage to proactive operational intelligence.🔗 Learn more at vaidio.aiTopics covered:Why healthcare is in a state of flux — staffing shortages, payer mix shifts, and the need for transformationThe economics of a hospital and why you can't just grow your way out of the problemVision AI's three core use cases — safety and security, patient care, and operational efficiencyWeapons detection, fall prevention, wandering patients, and geofencingDrug diversion — the economic, reputational, and human cost and how Vision AI helps passivelyStaff satisfaction and how passive AI monitoring reduces administrative burdenRoom turnover, vendor management, and surgical OR efficiency with license plate recognitionEquipment tracking — wheelchairs, IV pumps, and the nurse workaround problemVisitor and vendor management with facial recognition and color-coded monitoringThe visionary future — hospital at home⏱️ YouTube Timeline0:00 — Introduction — Meet Matt Benetti from Vaidio and Todd Larson from Honor Health0:30 — The state of healthcare today — staffing shortages payer mix and the need for transformation1:44 — How hospitals actually make money and why the economics are under pressure3:24 — The reformation happening in healthcare — unity of command communication and operations6:05 — Introducing Vision AI and the three core use cases for hospitals7:02 — Use case 1 — safety and security weapons detection wandering and geofencing8:04 — Why cameras as data storage is reactive not proactive9:08 — The Las Vegas casino model — open secure and unintrusive10:56 — Fall prevention and how AI vision replaces physical restraints12:46 — Real world wandering calls from Todd's law enforcement days13:42 — Staff optimization and operational efficiency through Vision AI14:41 — Room turnover throughput and autonomous monitoring examples18:22 — Use case 2 — drug diversion and passive multifactor authentication21:14 — The full cost of drug diversion — economic reputational and regulatory25:32 — Staff satisfaction and the body camera parallel from law enforcement28:15 — Surgeon license plate recognition and OR efficiency gains32:41 — Equipment tracking wheelchairs IV pumps and the nurse workaround35:50 — Three practical Vision AI recommendations for hospitals today37:09 — Visitor and vendor management with color-coded real time monitoring40:32 — The visionary future — hospital at home in 10 to 20 years🔔 Don't forget to Like, Subscribe, and hit the notification 🔔 ✔ Subscribe: https://www.youtube.com/jonmyer/?sub_confirmation=1📱 Social Media Twitter: https://twitter.com/_JonMyerWebsite: https://jonmyer.comLinkedIN: https://www.linkedin.com/in/jon-myer/Spotify: https://open.spotify.com/show/0wjJzdIwctq4o4pTXM2KSFLike my sounds? Here's my audio source: https://www.epidemicsound.com/referral/fj9o9k#aws #awscloud #podcast #podcasting #costoptimization #finops #cloudcost #cloudoptimization

Healthcare has spent years and billions modernizing its technology — but how much of it has actually changed outcomes for patients, clinicians, or the bottom line?In this episode of Health Reimagined, host Jon Myer (Myer Media, powered by Ingram Micro) sits down with Monica from Sublimation Health to unpack why so many digital transformation efforts stall, what the difference between modernization and true transformation actually looks like, and what it takes to get people, process, and technology moving in the same direction at the same time.From migration stalls and AI hype cycles to cloud security concerns and merger integration playbooks, this is a frank conversation about what healthcare IT leaders are really up against — and what change management done right actually looks like.🔗 Learn more at sublimationhealth.comTopics covered:The emotional state of healthcare IT leaders today — excited, exhausted, and nervousModernization vs. transformation — why they are not the same thingWhy transformation projects stall and how to avoid itThe people, process, and technology triad that drives successful migrationsAI hype cycles in healthcare and the risk of early vs. late adoptionWhy billions in digital investment still fail to produce measurable outcomesCloud as a strategic platform enabler, not just a migration destinationCloud security — immutable architecture, zero trust, and the shared responsibility modelDesigning infrastructure for mergers and acquisitions with 30/60/90 day playbooksWhat change management looks like when it is done right⏱️ YouTube Timeline0:00 — Introduction — The gap between transformation and outcomes0:27 — Meet Monica from Sublimation Health0:29 — The emotional state of healthcare IT leaders today1:09 — Skills gaps and upskilling while implementing1:24 — Organizational alignment as the hardest part of transformation1:49 — Modernization vs. transformation — what is the honest difference?2:58 — Can you do modernization without transformation?3:42 — Is AI consuming too much oxygen before the groundwork is done?4:58 — The constant upgrade cycle for early AI adopters5:38 — Why billions in digital investment still fail to produce measurable outcomes6:50 — People process technology — why you cannot focus on just one7:23 — Migration stalls caused by leadership changes and oversized goals7:43 — Agile approaches quick wins and incremental migration waves9:22 — Are we past cloud migration or should hospitals think platform strategy?9:30 — Cloud as a strategic enabler for AI and innovation at scale10:12 — How cloud modernization strengthens security rather than introducing new risk11:20 — Shared responsibility — security of the cloud vs. security in the cloud12:02 — Designing infrastructure for mergers and acquisitions13:06 — 30/60/90 day playbooks for integrating acquired organizations14:57 — Why technology transformations fail because of people not technology15:08 — What change management looks like when it is done right16:06 — Parallel workstreams keeping people process and technology aligned16:38 — Closing remarks and where to learn more🔔 Don't forget to Like, Subscribe, and hit the notification 🔔 ✔ Subscribe: https://www.youtube.com/jonmyer/?sub_confirmation=1📱 Social Media Twitter: https://twitter.com/_JonMyerWebsite: https://jonmyer.comLinkedIN: https://www.linkedin.com/in/jon-myer/Spotify: https://open.spotify.com/show/0wjJzdIwctq4o4pTXM2KSFLike my sounds? Here's my audio source: https://www.epidemicsound.com/referral/fj9o9k#aws #awscloud #podcast #podcasting #costoptimization #finops #cloudcost #cloudoptimization

Doctors are spending hours after dinner finishing clinical notes — what the industry calls "pajama time." They're typing while patients talk, missing details, and burning out. And some are retiring early because of it.In this episode of Health Reimagined, host Jon Myer (Myer Media, powered by Myer Media) sits down with Laurent from Nabla to explore how AI-powered clinical documentation is transforming the patient-physician relationship — and why reliability, trust, and deep EHR integration are what separate real clinical AI from tools that are still finding their way.🔗 Learn more at nabla.comTopics covered:What Nabla does — listening to clinical encounters and generating structured notes automaticallyWhat makes Nabla different — privacy-first, deeply customizable, and EHR-integratedWhy reliability in clinical AI is fundamentally about trust and transparencyWhy clinicians cannot afford five minutes of downtime once they depend on the toolHow AI as a "side memory" changes how doctors show up for patientsThe pajama time problem — clinicians documenting for hours after their shift endsFour clinicians who delayed retirement because Nabla reduced their administrative burdenImplementation in as little as two weeks with Epic, Oracle Cerner, Athena, and othersPrivacy — Nabla transcribes in real time without recording or storing conversationsThe partnership with MAI Labs and what world models mean for clinical decision supportWhat's driving Nabla's growth and the move to support all specialties⏱️ YouTube Timeline0:00 — Introduction — What it takes to build AI that is dependable at clinical scale0:36 — What Nabla does — listening summarizing and automating clinical workflows0:57 — What makes Nabla different — privacy customization and deep EHR integration1:13 — How crowded the clinical AI space has gotten and what separates the ready from the rest1:26 — Three years 200 health systems and the messy reality of real-world encounters2:04 — What reliability actually means when AI is embedded in a clinical workflow2:12 — Trust transparency and keeping the clinician in control at all times3:09 — Why 99.9% uptime is non-negotiable when doctors depend on AI as their memory3:36 — What happens when AI goes down and clinicians revert to old habits3:56 — AI as a side memory — the phone battery analogy4:34 — Right data right patient right prescription — the accuracy case for clinical AI4:59 — The patient experience when the doctor stops typing and starts listening5:34 — A personal story — what it is like to watch your doctor type instead of listen5:59 — Pajama time — clinicians documenting for two hours after dinner6:30 — Four clinicians who delayed retirement because Nabla reduced their burden7:10 — How clinical leaders evaluate AI differently after past technology failures7:52 — Implementation in two weeks with Epic Oracle Cerner Athena and more8:30 — Privacy consent and why 99.9% of patients say yes9:46 — Better outcomes fewer missed orders prescriptions that actually get sent10:39 — LLMs vs world models — what the next generation of clinical AI looks like11:46 — The MAI Labs partnership and clinical decision support that reasons like a doctor12:42 — What is behind Nabla's growth and the move to support every specialty13:52 — Closing remarks and where to learn more🔔 Don't forget to Like, Subscribe, and hit the notification 🔔 ✔ Subscribe: https://www.youtube.com/jonmyer/?sub_confirmation=1📱 Social Media Twitter: https://twitter.com/_JonMyerWebsite: https://jonmyer.comLinkedIN: https://www.linkedin.com/in/jon-myer/Spotify: https://open.spotify.com/show/0wjJzdIwctq4o4pTXM2KSFLike my sounds? Here's my audio source: https://www.epidemicsound.com/referral/fj9o9k#aws #awscloud #podcast #podcasting #costoptimization #finops #cloudcost #cloudoptimization