What Execs Get Wrong About AI Readiness (Michael Housman)

Nearly every board has asked for an AI strategy, and plenty of executive teams have a polished deck to show for it. But having a strategy and being ready to deploy AI are two very different things. When leadership teams treat AI as a purely technical initiative rather than a human transformation, pilots stall, user adoption falters, and the pressure to ship faster creates significant quality gaps downstream.In this episode of Ready, Test, Go., Dr. Michael Housman, author of Future Proof: Transform Your Business with AI (or Get Left Behind) and co-founder/CEO of AI Performance Lab, joins to discuss what executives get wrong about AI readiness. Michael explains why leaders cannot delegate AI literacy, how leadership blind spots affect QA and engineering teams, and what AI-ready organizations do before shipping to production.About the guest: Dr. Michael Housman is the founder and CEO of AI Performance Lab as well as the author of Future Proof: Transform Your Business with AI (or Get Left Behind). Over a 15-year career, he has built and deployed AI platforms that have reshaped industries, working with both high-growth technology startups and Fortune 500 companies. His research has been published in peer-reviewed journals and profiled by media outlets like The New York Times, Wall Street Journal, The Economist and The Atlantic. Dr. Housman received his Ph.D. in Applied Economics and Managerial Science from The Wharton School and is a frequent guest lecturer at the McCombs School of Business at the University of Texas at Austin.You can find Michael’s book here: https://a.co/d/00VeFpKiHosted by David CartyProduced by David Carty, Samsu Sallah and Joe StellaGraphic design by Karley SearlesTo contact the producers, please email us at [email protected].

Enterprise teams are rapidly integrating AI across development, testing and requirements planning. But what is AI missing about the critical organizational context — how software connects to broader business processes? And how does that manifest in requirements gaps, hidden risks and testing misalignments?Michael Schank, author and founder of Insight Twin, joins the podcast to explain the importance of supplying AI with dynamic models that connect processes, systems, roles and business goals. He explains why AI thrives when it has true operational context — and how it enables engineering and quality leaders to make smarter decisions.About the guest:Michael Schank has spent nearly 30 years helping organizations navigate complex transformations — system implementations, operational excellence programs, risk and compliance, enterprise architecture and large-scale digital change. He's the author of Digital Transformation Success, where he introduced the Process Inventory Framework. Now as founder of Insight Twin, Michael helps give leaders clear visibility into their operations so AI projects align with how the business really works.You can find Michael’s book here: https://a.co/d/0h8TrKqiHosted by David CartyProduced by David Carty, Samsu Sallah and Joe StellaGraphic design by Karley SearlesTo contact the producers, please email us at [email protected].

Good accessibility is not just the result of meeting a standard. Accessible experiences come from understanding how different people actually experience a product — challenging assumptions early and giving users meaningful influence help guide organizations on the path to exceptional products. Then, why do so many organizations struggle to keep the human perspective in mind? And how is AI amplifying that problem?In this episode, HCI professional John McCartney joins us to discuss what it takes to make human-centered thinking a shared organizational capability across design, engineering, product and testing. Our conversation looks at where accessibility most often breaks down, and how direct feedback from people with disabilities can expose problems teams would otherwise miss. He explains why empathy has to be supported by real processes, accountability and evidence to drive meaningful work.About the guest:John McCartney is a UX and design leader with more than 15 years of experience, currently serving as Senior Manager of User Experience at Progress ShareFile. His focus has been on accessibility and inclusivity as core parts of usability, not separate initiatives layered on top. His background in human-computer interaction and human-centered design shapes how he frames problems, defines success and builds teams.He's also spent much of his career scaling accessibility approaches, including helping to build org-wide structures, research capacity and team culture that enable human-centered thinking across the org. To learn more about John’s session at the M-Enabling Summit, please visit: https://www.m-enabling.com/event/c303ac78-b6b9-45b3-a375-10f9ea7bc56b/agenda-schedule?session=70e213fb-0cc7-4a7b-9d54-22e62aafd910\&shareLink=trueTo learn more about how Applause supports Progress Software's ShareFile team in building more inclusive apps, please visit: https://www.applause.com/resources/case-studies/sharefile-case-study/video/Hosted by David CartyProduced by David Carty, Samsu Sallah and Joe StellaGraphic design by Karley SearlesTo contact the producers, please email us at [email protected].

As AI accelerates code generation, quality teams can't afford to operate as a downstream gatekeeper — when pipeline trust breaks down, the entire delivery engine grinds to a halt. QA leader Nandini Srinivasan joins us to explain why quality at scale is fundamentally a trust problem, and how QA leaders can shift from a late-stage checklist item to a strategic reliability partner.About the guest:Nandini Srinivasan is a quality engineering executive with more than 20 years of experience building and scaling global QA organizations across SaaS, mobile, embedded hardware, firmware, AI/ML, and enterprise platforms. At Motive, she leads Quality Assurance, where she has helped evolve the practice from a reactive release-validation function into a proactive, reliability-oriented operating model. Her work spans shift-left quality, performance engineering, automation strategy, customer-facing reliability, and AI-augmented QA practices.Hosted by David CartyProduced by David Carty, Samsu Sallah and Joe StellaEdited by David Carty, Samsu Sallah and Ian LippincottGraphic design by Karley SearlesTo contact the producers, please email us at [email protected].

AI has made it effortless to generate ideas, prototypes and code, but faster production doesn't guarantee better products. Unchecked speed comes with risks, including overwhelming teams and customers alike with unvalidated output. Product leadership advisor and author Jeff Gothelf joins the podcast to discuss how to shift to an evidence-driven learning approach.About the guest: Jeff Gothelf helps organizations turn technical capability into customer value through better product decision-making, customer-centric metrics and evidence-driven ways of working. He is the co-author of Lean UX, now in its third edition, and Sense & Respond, published by Harvard Business Review Press. He also co-authored Who Does What By How Much?, a practical guide to customer-centric OKRs, and co-founded Sense & Respond Learning with Josh Seiden in 2024 to help leaders and teams adapt product management, development and goal-setting for an AI-shaped environment.You can find more of Jeff's work at senseandrespond.co.Hosted by David CartyProduced by David Carty, Samsu Sallah and Joe StellaGraphic design by Karley SearlesTo contact the producers, please email us at [email protected].

Technology teams are often measured by what they can ship: performance, reliability, efficiency, adoption and scale. But the systems they build also shape privacy, dignity, access, autonomy, care and trust, among other important values. Their work asks a pair of deceptively simple questions: Who is affected by a technology? And what values are implicated by the choices teams make?Value sensitive design pioneers Batya Friedman and David Hendry join the podcast to discuss their framework for integrating these human values into products. Leaning on a few examples and even a demonstration, Friedman and Hendry explain why it's important to go beyond simple performance metrics and broadly support human flourishing in product design.About the guests:Batya Friedman and David G. Hendry are leading researchers in value sensitive design. Their work brings together theory, method and practice to help designers, engineers, researchers, policy makers and technology leaders account for human values throughout the design process. Through concepts such as stakeholder analysis, value scenarios, envisioning cards and multi-lifespan thinking, they have helped establish a practical framework for designing technologies that account for dignity, privacy, care, justice, access and other important human values. They are coauthors of Value Sensitive Design: Shaping Technology with Moral Imagination, which just released its second edition. You can find it here: https://www.penguinrandomhouse.com/books/798075/value-sensitive-design-second-edition-by-batya-friedman-and-david-g-hendry/You can also find their envisioning cards here: https://vsdesign.org/toolkits/envisioningcards/Hosted by David CartyProduced by David Carty, Samsu Sallah and Joe StellaGraphic design by Karley SearlesTo contact the producers, please email us at [email protected].

Many organizations make a critical mistake: they layer new AI tools on top of broken, legacy workflows. This creates inefficiencies at best — the opposite of what AI aims to solve — and "digitized chaos" at worst. This is uniquely true in digital healthcare. The challenge isn't so much the technology itself, but the lack of organizational alignment coupled with a failure to design systems around the human beings they are intended to serve.In this episode, Dr. Nasim Afsar, healthcare executive, physician leader and author of Intelligent Health, joins us to reframe the conversation. Drawing on her experience at Oracle and UCLA Health among others, Nasim explains why successful AI adoption requires us to stop building for the silo and start building for the individual. She discusses the vital role of trust in algorithms, the dangers of echo chambers in design and how leaders can finally move beyond point solutions toward genuine, humane digital transformation.About the guest: Dr. Nasim Afsar, MD, MBA, is a healthcare executive and physician leader. She is a leading voice in digital health strategy. Previously serving as Chief Health Officer at Oracle and in executive leadership at UCLA Health and UCI Health, she specializes in operations, quality and digital transformation. She is a dedicated physician-leader committed to improving the care delivery experience.You can find Nasim’s latest book, Intelligent Health: The Movement to Unify Data, Harness AI, and Empower People to Thrive, here: https://www.wiley.com/en-hk/shop/general-introductory-biomedical-engineering/intelligent-health-the-movement-to-unify-data-harness-ai-and-empower-people-to-thrive-p-9781394408276Hosted by David CartyProduced by David Carty, Samsu Sallah and Joe StellaGraphic design by Karley SearlesTo contact the producers, please email us at [email protected].

Many technology leaders view data quality as purely an IT issue, which leads to fragmentation and siloed efforts. The challenge lies the lack of organizational alignment and clear, human-centric data intelligence.In this episode, Roberto Maranca, data excellence practitioner and author of Data Excellence: How Data Leadership Can Drive Stronger Organizational Performance joins us to reframe data governance as a team sport. Roberto explains why successful AI adoption requires "data athletes" and "data personal trainers" to work in concert. He discusses the importance of data consumer stories, the necessity of human judgment in AI and how leaders can rebuild trust by prioritizing clear data context.About the guest: Roberto Maranca is an enterprise data leader and author. He has held senior and executive data leadership roles at organizations including Schneider Electric, Lloyds Banking Group and GE, with work spanning data governance, data quality, data risk, AI readiness and business transformation. Recognized multiple times as one of DataIQ’s Top 100 Data Leaders, Roberto frames data leadership as a performance discipline, which helps organizations build trust, accountability and value.Hosted by David CartyProduced by David Carty, Samsu Sallah and Joe StellaGraphic design by Karley SearlesTo contact the producers, please email us at [email protected].

Testing teaches us to look for hidden assumptions and treat failure as valuable information. But when the standard for professional quality is high, the friction of everyday life can feel like a series of critical defects. Without the right framework, these "bugs" lead to emotional burnout and strained relationships rather than insight.In this episode, Alison McGuigan, Director of Enterprise Quality Assurance, discusses how the testing mindset fundamentally changes how we approach complexity. From boundary testing personal relationships to refactoring daily habits and dead code, Alison explores how to apply technical rigor to personal growth — and vice versa. Learn why treating every defect as a source of insight can improve resilience and navigate the most complex human systems.About the guest: Alison McGuigan is a Director of Enterprise Quality Assurance and author of the blog Testing in Production. She has over a decade of experience driving test optimization and automation strategy.You can find Alison’s blog here: https://testinginprod.substack.com/Hosted by David CartyProduced by David Carty, Samsu Sallah and Joe StellaGraphic design by Karley SearlesTo contact the producers, please email us at [email protected].

Automation is at the core of modern software delivery, enabling enterprises to surface risk earlier and operate with greater speed. That means everything from developer-native security to AI-assisted code generation. However, increased activity and scale do not guarantee quality or confidence. As AI accelerates code production, the risk landscape expands, raising questions about accountability and assurance.In this episode, Nir Valtman, CEO and co-founder of Arnica, joins us to discuss how organizations can design an operating model where automation enhances speed and consistency — all while human judgment, cultural discipline and contextual validation remain central to establishing trust.About the guest:Nir Valtman is the CEO and co-founder of Arnica, where he focuses on advancing developer-first security practices that surface risk earlier in the software development lifecycle. With a strong background in engineering leadership and application security, Nir has worked at the intersection of DevOps, secure SDLC transformation, and automation at scale.His perspective centers on reducing friction for developers while strengthening code-level assurance through AI-assisted remediation and workflow-native security practices. He is a frequent voice in conversations about modern AppSec, AI-driven development, and the evolving relationship between automation and engineering accountability.Hosted by David CartyProduced by David Carty, Samsu Sallah and Joe StellaGraphic design by Karley SearlesTo contact the producers, please email us at [email protected]