The Bridgecast with Scott Kinka

Beyond Compliance: Building a Framework for Trustworthy AI

In this episode of The Bridgecast, host Scott Kinka welcomes Reggie Townsend, Vice President of AI Ethics, Governance, and Social Impact at SAS, for a wide-ranging conversation about what it truly means to build AI that organizations — and society — can trust. Reggie brings something rare to the AI ethics conversation: a commercial backbone. After years at Motorola, IBM, and Sun Microsystems before joining SAS eleven years ago, he approaches responsible AI not as an academic exercise but as a practical business imperative. His core thesis? Doing well and doing good are not mutually exclusive — and organizations that treat ethics as purely defensive are leaving enormous strategic value on the table. What you will learn: * Why "responsible AI" is being replaced by "trustworthy AI" — and why the language shift matters more than most people realize * How to apply SAS's four-pillar AI governance framework (culture, operations, regulations, oversight) inside your organization today * The hidden cost of treating AI governance like a compliance exercise instead of a strategic leadership function * Why AI is not word processing — and what automated decision-making really means for your business risk * How to think about productivity metrics, workforce pipeline, and the human cost of hollowing out junior talent in the AI era * What CIOs should do right now to build a durable governance model across fragmented global regulations Reggie Townsend is the Vice President of AI Ethics, Governance, and Social Impact at SAS, a data and AI company with 50 years in business. He previously served on the National AI Advisory Committee, advising the U.S. Department of Commerce, and currently sits on the board of Equal AI. With a career spanning Motorola, IBM, and Sun Microsystems before SAS, Reggie brings a practically grounded lens to AI ethics — one that insists organizations can simultaneously drive profit and protect people. He leads teams across ethics, governance, regulatory strategy, accessibility, and social impact at one of the world's most quietly consequential AI companies. Episode Highlights: * [15:27] The Language Shift That Changes Everything At SAS, the term isn't "responsible AI" — it's "trustworthy AI." And Reggie explains why that distinction matters far more than it first appears. "No one is going to sign up for irresponsible," he says — which means the term has become politically loaded before the real conversation even starts, entangled in doomer narratives and Luddite debates. Trustworthy AI, by contrast, cuts straight to the question that actually matters: will people invest their trust in this technology? This framing is backed by governments worldwide — the EU, the UN, and both recent U.S. administrations have all gravitated toward it. More importantly, it reframes the business conversation entirely. Trust isn't a constraint on AI deployment. It's the precondition for adoption at scale. Organizations that are still fighting over whether their AI is "responsible" may be having the wrong conversation entirely. * [24:02] The Hollow Pipeline Problem One of the sharpest observations in this episode concerns what happens when organizations race to maximize AI-driven output at the expense of building their talent pipeline. Reggie warns that senior employees who become heavy AI users can now produce at levels that make junior hiring seem unnecessary — but then asks, "What happens when those senior people leave?" The institutional knowledge disappears. And there's no pipeline to replace it. He extends this to the macro level: if GDP is just a measure of output, AI agents producing more may look like a win. But if the people who used to produce are left behind, "we will have missed the boat by a long shot." The implication for leaders is direct: AI workforce strategy isn't just about productivity gains. It's about what kind of organization you intend to be five to ten years from now — and whether you'll have the human foundation to sustain it. * [19:12] The Four-Pillar Governance Framework That Actually Works When businesses ask what good AI governance looks like in practice, Reggie doesn't point to a policy template. He points to SAS's "quad" framework: Culture, Operations, Regulations, and Oversight. Culture asks how normative behaviors in the organization need to shift to absorb AI disruption — and what the psychological impact on employees will be. Operations addresses workflows and how work will actually get done going forward. Regulations covers both compliance obligations and aspirational standards in a currently fragmented global landscape. Oversight asks where accountability sits, who monitors AI decisions, and how fast the organization should allow change to move. His advice for getting started: "Don't go try to solve for cancer." Instead, identify repeatable, laborious tasks — what he calls "pearls" — AI-ify those first, build early wins, develop the organizational muscle, and then expand. It's a framework that respects both business reality and human complexity, and it's one any organization can start using today. Episode Resources: * Reggie Townsend on LinkedIn [https://www.linkedin.com/in/reginaldtownsend] * SAS Website [https://www.linkedin.com/company/sas/] * Scott Kinka on LinkedIn [https://www.linkedin.com/in/scottkinka/] * The Bridgecast on Apple Podcasts [https://podcasts.apple.com/us/podcast/the-bridgecast-with-scott-kinka/id1643072015] * The Bridgecast on Spotify [https://open.spotify.com/show/3XON2m9v7cIftFsuDdMFK6?si=6bb5bcbd4d6b4c08&nd=1&dlsi=be415ed3c9d84b7d] * The Bridgecast on YouTube [https://www.youtube.com/playlist?list=PLhxXT9jqi5I_E0jipkfclI7LG7UQw8HTE] The Bridgecast is handcrafted by our friends over at: fame.so [https://www.fame.so/?utm_medium=podcast&utm_source=bcast&utm_campaign=masters-of-community-with-david-spinks?utm_medium=podcast&utm_source=bcast&utm_campaign=fame-client]

Connectivity, Data, and People: The New IT Ecosystem

In this live episode of The Bridgecast, recorded at the Lumen Lounge during the Channel Partners Conference, host Scott Kinka welcomes Danny Benedetti, Vice President of Partner Solutions, and Jim Ortbals, Senior Vice President of Global Partner Solutions at Lumen. Together, they dive into the evolution of one of the industry's most significant players—from the legacy of CenturyLink and Level 3 to becoming a purpose-built infrastructure provider for the AI era.  The discussion moves beyond traditional connectivity to explore how organizations can "cloudify" their networks to scale bandwidth on demand. With Jim joining the conversation on his first day in the role, the episode offers a unique look at leadership during rapid change and the strategic importance of building a "digital workforce" through AI agents. Whether you are managing complex M&A integrations or preparing your infrastructure for agentic AI, this episode provides a roadmap for translating technology into business outcomes.  What you will learn: * How to shift from static to dynamic networking to support the AI economy * The leadership superpowers required to guide teams through constant industry change * Strategies for managing the human fear and systemic risks inherent in M&A integrations * Why internal AI agents are creating immediate ROI by building a digital workforce * The importance of humility and servant leadership in a high-stakes tech environment * Why network control must move from the provider into the hands of the customer About the Guests: Danny Benedetti is the Vice President of Partner Solutions at Lumen Technologies, where he has spent 16 years leading channel strategy through multiple industry shifts. He focuses on helping partners deliver value to enterprise customers in increasingly distributed IT environments.  Jim Ortbals serves as the Senior Vice President of Global Partner Solutions at Lumen. A veteran of the service provider and cybersecurity space, Jim has held leadership roles at Cisco, VMware, Zscaler, and BeyondTrust before joining Lumen to lead their global channel organization.  To find out how Bridgepointe Technologies helps businesses make IT decisions faster with world-class engineering support and ongoing guidance, head to https://bridgepointetechnologies.com/ [https://bridgepointetechnologies.com/] Episode Highlights: * [05:41] Leading Through the "Hard" Danny Benedetti explains that leading through change is about more than logistics; it's about caring for the people you lead. When change creates fear, leaders must steady the boat and help their teams see the opportunity on the other side. Danny shares a core philosophy he uses with his team: "Everything you want is on the other side of hard."  * [09:00] Cloudifying the Network Lumen is moving away from static, telco-controlled networks to a model where the network scales on demand. This "cloudification" allows enterprises to dial bandwidth up or down and move workloads to hyperscalers seamlessly via tools like the Multi-Cloud Gateway. As Danny puts it, Lumen is becoming the "backbone for the AI economy" by ensuring infrastructure can scale with the needs of the enterprise.  * [14:48] The Human Element of Integration Managing corporate mergers isn't just about systems; it's about human fear. Danny notes that people often worry about their own place in a new organization rather than what's best for the technology. Jim adds that from a systemic perspective, security must be a primary focus to ensure integrations don't create new attack vectors while chasing productivity.  Episode Resources: * Danny Benedetti on LinkedIn [https://www.linkedin.com/in/danny-benedetti/] * Jim Ortbals on LinkedIn [https://www.linkedin.com/in/jimortbals/] * Lumen Technologies Website [https://www.lumen.com/] * Scott Kinka on LinkedIn [https://www.linkedin.com/in/scottkinka/] * Bridgepointe Technologies Website [https://bridgepointetechnologies.com/] * The Bridgecast on Apple Podcasts [https://podcasts.apple.com/us/podcast/the-bridgecast-with-scott-kinka/id1643072015] * The Bridgecast on Spotify [https://open.spotify.com/show/3XON2m9v7cIftFsuDdMFK6?si=6bb5bcbd4d6b4c08&nd=1&dlsi=be415ed3c9d84b7d] * The Bridgecast on YouTube [https://www.youtube.com/playlist?list=PLhxXT9jqi5I_E0jipkfclI7LG7UQw8HTE] The Bridgecast is handcrafted by our friends over at: fame.so [https://www.fame.so/?utm_medium=podcast&utm_source=bcast&utm_campaign=masters-of-community-with-david-spinks?utm_medium=podcast&utm_source=bcast&utm_campaign=fame-client]

From Plumbing to AI: The Evolution of Managed Services

In this episode of The Bridgecast, host Scott Kinka welcomes Frank Scanga, Executive Vice Chairman at XTIUM—the powerhouse formed by the combination of ATSG and Evolve IP. With over three decades of experience in the managed services and cloud space, Frank offers a candid look at how technology leadership must evolve from "wrench turning" to driving actual business outcomes. The conversation dives deep into the current state of AI, where Frank reveals a startling statistic: 70% of AI projects fail because organizations take a technology-first rather than a business-outcome approach. From winning top honors in Gartner's Magic Quadrant for Managed Network Services to building an "AI Manager" platform to orchestrate LLMs, Frank explains why the "S" in MSP—Service—remains the most critical component of the tech stack. What you will learn: * Why 70% of AI projects fail and how to pivot toward business outcomes * The definition of a "full-stack" MSP and why point products are no longer enough * How XTIUM uses machine learning and AI for business impact modeling * Why the Windows 10 end-of-life is driving a massive resurgence in Desktop as a Service (DaaS) * The one question every business should ask an MSP: "How do you perform in a failure?" * Why curiosity and listening to customers are the keys to long-term leadership Frank Scanga is the Executive Vice Chairman at XTIUM and a longtime leader in the managed services and cloud industry. A New York native and Fordham University graduate, Frank founded Maxpoint (later ATSG) in 1994 and has scaled the organization to support 1,700 clients across complex IT environments. Today, he helps drive XTIUM’s "security-first, AI-enabled" approach to IT, focusing on providing high-level business value by automating and managing the foundational technology stack. To find out how Bridgepointe Technologies helps businesses make IT decisions faster with world-class engineering support and ongoing guidance, head to https://bridgepointetechnologies.com/ [https://bridgepointetechnologies.com/] Episode Highlights: * [11:17]  The 70% Problem: Tech-First Is the Wrong First Frank opens the episode with a number that stops listeners cold: 70% of AI projects are failing. And the culprit isn't the technology—it's the mindset. "They're taking a technology approach to it and not so much a business outcome approach," Frank explains. This isn't new. It's the same pattern he's watched play out since the dot-com boom, through the cloud rush, and now into AI. CIOs who lead with bits and bytes get tuned out in the boardroom. The ones who thrive frame everything around business impact. The analogy Frank uses is pointed: "It's a service; it should be up and running, period. You turn the lights on, you expect the lights to be on." The moment a CIO starts talking about infrastructure for its own sake, they've already lost the room. The lesson applies directly to AI: a "technology-first" AI strategy isn't a strategy—it's a procurement plan. The organizations winning with AI are the ones asking "what problem does this solve for the business?" before they write a single line of code or sign a single vendor contract. * [13:25]  Building the MSP of AI: Ten Years in the Making While most organizations are just beginning to think about AI governance, XTIUM has been quietly building it for nearly a decade. Their observability platform uses machine learning to distinguish "white noise" from "bad noise" in managed networks—and goes further with business impact modeling that ties network events directly to business outcomes. They built AI into their DaaS cloud management platform as well. But the most forward-looking development is internal: XTIUM built an "AI Manager" to govern how their own teams deploy and use AI—because they experienced firsthand what happens when AI usage becomes sporadic and ungoverned. "We realized our own AI deployment was sporadic, so we centralized it," Frank explains. Now, they're preparing to offer that platform to customers. The positioning is characteristically direct: "Someone's going to manage the robots—why not us?" That's the XTIUM thesis in six words. And given their Gartner ranking—#1 in managed network services, automation/AI, and security in MNS—it's not just a tagline. * [26:50]  The One Question That Exposes Every MSP When Scott asks what question a company should ask when evaluating an MSP, Frank doesn't talk about certifications, headcount, or pricing. He gives a single, deceptively simple answer: "How do you perform in a failure?" It's a question that cuts through vendor theater instantly. "Technology fails all the time," Frank says. "The 'S' is the big part of 'MSP'—it's a services business." What matters isn't how smooth things run when everything's working; it's what happens at 2 a.m. when something breaks. Frank has kept his first customer for over 32 years. His first employee is still with him. That's not a marketing claim—it's the output of a culture that treats trust as the core product, not the technology stack underneath it. "If you trust that we are taking care of the infrastructure, you can focus on your business." Everything else is commentary. Episode Resources: * Frank Scanga on LinkedIn [https://www.linkedin.com/in/frank-scanga-343aaa16] * Scott Kinka on LinkedIn [https://www.linkedin.com/in/scottkinka/] * The Bridgecast on Apple Podcasts [https://podcasts.apple.com/us/podcast/the-bridgecast-with-scott-kinka/id1643072015] * The Bridgecast on Spotify [https://open.spotify.com/show/3XON2m9v7cIftFsuDdMFK6?si=6bb5bcbd4d6b4c08&nd=1&dlsi=be415ed3c9d84b7d] * The Bridgecast on YouTube [https://www.youtube.com/playlist?list=PLhxXT9jqi5I_E0jipkfclI7LG7UQw8HTE] The Bridgecast is handcrafted by our friends over at: fame.so [https://www.fame.so/?utm_medium=podcast&utm_source=bcast&utm_campaign=masters-of-community-with-david-spinks?utm_medium=podcast&utm_source=bcast&utm_campaign=fame-client]

Beyond the Hype: Building Ethical AI for Business

In this episode of The Bridgecast, host Scott Kinka welcomes Dr. Eva-Marie Muller-Stuler, a literal rock star in the world of data science and AI ethics. As the former leader of IBM’s first AI center of excellence and a top advisor to the European Parliament, Dr. Eva-Marie brings a wealth of experience in turning emerging technologies into measurable business outcomes. She challenges the current corporate obsession with "agentic AI" and "autonomous workers" by highlighting the foundational work required in data governance and strategy. Dr. Eva-Marie shares a seminal moment from her career where a major telecom company offered her an intern's worth of raw data without an MOU, illustrating just how far the industry has come—and how many ethical pitfalls remain. The discussion dives deep into "data archaeology," explaining why data for AI requires a much more rigorous standard than data for traditional analytics. What you will learn: * Why AI must always start with a business need rather than a technical capability  * The fundamental difference between data for analytics and data for AI  * How to identify and mitigate "hidden proxies" that create bias in machine learning models  * The framework for choosing between "buying" versus "building" AI solutions  * Why the loss of senior expertise in the workforce is a major threat to AI monitoring and safety  * The reality of current AI regulations and why most models are not yet truly GDPR compliant Dr. Eva-Marie Muller-Stuler is the Founder and Chief AI Officer at The Hummingbird Group, a firm dedicated to responsible, high-performance AI deployment. With over 25 years of experience helping global organizations turn emerging technologies into measurable business outcomes, she has led major AI initiatives at KPMG, Ernst & Young, and IBM—where she built their first AI center of excellence. She has also advised the United Nations, UNESCO, and the European Parliament on AI governance and risk mitigation. Recognized as a Top 10 Most Influential Woman in Technology, World’s Best Data Scientist, and Top Brilliant Women in AI Ethics, Dr. Eva is a leading voice on the intersection of technical rigor, ethical AI, and real-world business outcomes. She is based in Dubai and is currently writing a book on how to correctly build AI systems. Episode Highlights: * [04:34] The Data Wild West That Changed Everything Dr. Eva’s pivotal career moment came in 2013 at KPMG, when her team was building “always-on machines for decision support.” With almost no data governance norms in place, they contacted one of the world’s largest telecom companies and asked for all their customer data—who called whom, from where, which bills were paid. The company’s response was essentially: help yourself. They sent an intern with flash drives to pick it up. No MOU. No payment. No legal framework. Sitting with the data, Eva and her team had a sobering realization: they didn’t need AI models at all. They could simply filter behavioral patterns to identify individuals’ religion, health status, and financial situation—with no model required. “We had so much knowledge about individual people,” she recalls. That moment became the catalyst that drove her into AI governance work with the UK government, EU, United Nations, and NGOs worldwide. Even today—with GDPR and the EU AI Act in place—most large language models are not compliant, and enforcement remains dangerously weak. The wild west isn’t over. It’s just better dressed. * [14:30] The Champions Program: Nike's Secret to GitHub Copilot Adoption When Nike rolled out GitHub Copilot, leadership assumed flipping the switch would be enough. It wasn't. Adoption stalled. What unlocked it? Training, targeted use-case discovery, and — most critically — a "champions program" that activated the engineers who were already experimenting on their own. Elaine connects this directly to the shadow IT problem: fear of displacement drives people to go rogue. Organizations that surface those early adopters and give them a sanctioned role in the rollout don't just solve a security problem — they create a self-sustaining adoption engine. Her formula: top-down mandate gives permission, bottom-up champions give momentum. "Build community structures that understand and operate. Then, all of a sudden, you're not just pushing a literacy program; it's creating itself. That's sustainable." * [19:15] Tribal Knowledge Is the Real AI Advantage Elaine lands one of the episode's most counterintuitive insights: it's not Gen Z leading AI adoption in the enterprise — it's the seasoned operators with years of context. AI tools are only as powerful as the prompts fed into them, and great prompts require deep domain knowledge. "Intelligence lives outside the tool," she says. "You can't just apply an agent and think you're diving into the workflow. You have to learn about all the tribal knowledge gained over the years." This reframes the entire upskilling conversation. The goal isn't to teach experienced workers to be tech-savvy; it's to help them see that what they already know is the most valuable input to any AI system — and then invest in developing that capability intentionally. Episode Resources: * Dr. Eva-Marie Muller-Stuler on LinkedIn [https://www.linkedin.com/in/dreva] * Scott Kinka on LinkedIn [https://www.linkedin.com/in/scottkinka/] * The Bridgecast on Apple Podcasts [https://podcasts.apple.com/us/podcast/the-bridgecast-with-scott-kinka/id1643072015] * The Bridgecast on Spotify [https://open.spotify.com/show/3XON2m9v7cIftFsuDdMFK6?si=6bb5bcbd4d6b4c08&nd=1&dlsi=be415ed3c9d84b7d] * The Bridgecast on YouTube [https://www.youtube.com/playlist?list=PLhxXT9jqi5I_E0jipkfclI7LG7UQw8HTE] The Bridgecast is handcrafted by our friends over at: fame.so [https://www.fame.so/?utm_medium=podcast&utm_source=bcast&utm_campaign=masters-of-community-with-david-spinks?utm_medium=podcast&utm_source=bcast&utm_campaign=fame-client]

Innovation Lessons from Nike and Amex

In this episode of The Bridgecast, host Scott Kinka welcomes Elaine Barsoom — Venture Partner at Silicon Foundry and a recognized leader in enterprise AI and corporate innovation — for a wide-ranging conversation on what it actually takes to build an AI strategy that sticks. With 20 years of experience bridging strategy and next-generation technology across Nike, American Express, and multiple sectors including retail, fintech, and hospitality, Elaine brings a rare lens: the view from inside the machine. Her defining insight? Most organizations are asking the wrong question. Instead of "How do we use AI?", the right question is "What problem are we trying to solve, and can AI help?" — a subtle but transformative shift that changes everything about governance, adoption, and ROI. What you will learn: * Why most AI mandates are set up to fail — and how to reframe the right question * How to map current-state workflows and redesign around human needs before selecting tools * Why experienced employees with tribal knowledge outperform younger workers when using AI * How Nike's GitHub Copilot rollout almost stalled — and what a champions program did to fix it * The top-down mandate + bottom-up build model for sustainable AI adoption * Why most AI governance frameworks are "theater" and what to do instead * Real-world CX wins: Lowe's Milo, Wingstop's Smart Kitchen, and what they teach about ROI * The bold prediction that AI agents will soon outnumber humans in enterprise org charts Elaine Barsoom is a Venture Partner at Silicon Foundry and a globally recognized leader in AI strategy and corporate innovation. She spent 20 years helping Fortune 500 organizations marry strategy with next-generation technologies, most recently serving as Global Head of Tech Innovation, Partnerships, and Strategy at Nike. Her career also includes pivotal leadership roles at American Express, where she built one of the company's first e-commerce ventures in the years following September 11th. A first-generation daughter of Egyptian immigrants and a systems thinker at her core, Elaine now works with mid-market organizations and leaders to navigate AI transformation with rigor, empathy, and measurable results.  Episode Highlights: * [09:52] Ask the Right Question First Elaine's most foundational piece of advice for AI-overwhelmed CIOs reframes the entire conversation. At Nike, before touching any tool or vendor, the team asked: "What problem are we trying to solve, and can AI help?" — not "How do we use AI?" This single reframe changes how friction points get identified, how workflows get redesigned, and ultimately whether AI gets used at all. Elaine is unambiguous: "Just putting a tool on top of a tool just incurs more technical debt. Don't just do AI for AI's sake." She also challenges the very structure of governance conversations, arguing that IT leaders must walk in with systems and frameworks already in place — not reinvent the wheel for each vendor conversation. A pre-agreed risk framework between IT and legal isn't bureaucracy; it's the only way to move fast and stay protected. * [14:30] The Champions Program: Nike's Secret to GitHub Copilot Adoption When Nike rolled out GitHub Copilot, leadership assumed flipping the switch would be enough. It wasn't. Adoption stalled. What unlocked it? Training, targeted use-case discovery, and — most critically — a "champions program" that activated the engineers who were already experimenting on their own. Elaine connects this directly to the shadow IT problem: fear of displacement drives people to go rogue. Organizations that surface those early adopters and give them a sanctioned role in the rollout don't just solve a security problem — they create a self-sustaining adoption engine. Her formula: top-down mandate gives permission, bottom-up champions give momentum. "Build community structures that understand and operate. Then, all of a sudden, you're not just pushing a literacy program; it's creating itself. That's sustainable." * [19:15] Tribal Knowledge Is the Real AI Advantage Elaine lands one of the episode's most counterintuitive insights: it's not Gen Z leading AI adoption in the enterprise — it's the seasoned operators with years of context. AI tools are only as powerful as the prompts fed into them, and great prompts require deep domain knowledge. "Intelligence lives outside the tool," she says. "You can't just apply an agent and think you're diving into the workflow. You have to learn about all the tribal knowledge gained over the years." This reframes the entire upskilling conversation. The goal isn't to teach experienced workers to be tech-savvy; it's to help them see that what they already know is the most valuable input to any AI system — and then invest in developing that capability intentionally. Episode Resources: * Elaine Barsoom on LinkedIn [https://www.linkedin.com/in/ebarsoom/] * Scott Kinka on LinkedIn [https://www.linkedin.com/in/scottkinka/] * The Bridgecast on Apple Podcasts [https://podcasts.apple.com/us/podcast/the-bridgecast-with-scott-kinka/id1643072015] * The Bridgecast on Spotify [https://open.spotify.com/show/3XON2m9v7cIftFsuDdMFK6?si=6bb5bcbd4d6b4c08&nd=1&dlsi=be415ed3c9d84b7d] * The Bridgecast on YouTube [https://www.youtube.com/playlist?list=PLhxXT9jqi5I_E0jipkfclI7LG7UQw8HTE] The Bridgecast is handcrafted by our friends over at: fame.so [https://www.fame.so/?utm_medium=podcast&utm_source=bcast&utm_campaign=masters-of-community-with-david-spinks?utm_medium=podcast&utm_source=bcast&utm_campaign=fame-client]