AI Security, AI Cloud Ops & Infrastructure | ClearTech Loop

What CISOs miss when security only lives in features 

AI security is still getting framed like a technology problem: new tools, new controls, new dashboards, and new rules. In this episode of ClearTech Loop, Jo Peterson talks with Miri Rodriguez, Cofounder and CEO of Empressa.ai, about why that framing keeps breaking in the real world. 

Miri brings a people first lens to AI adoption and security. She argues that security is not just something you install. It is an environment people are willing to enter. When the environment does not feel secure, adoption either slows or goes underground, and then security teams are left trying to govern what they cannot see. 

This conversation connects three practical leadership threads: using GenAI upstream to understand real adoption patterns, embedding security and privacy without slowing innovation by designing for humans, and building governance that becomes habit instead of paperwork. 

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Key Quotes
“The opportunity is massive when you think about security as an environment, not just a technology or a feature.” 
“The features don’t matter. If you can’t tell me why the features are important in my space.” 

Three Big Ideas from This Episode 

1. GenAI beyond the tool stack
   Generative AI can help security leaders widen the lens on adoption. Before policies and controls, leaders need to understand where people hesitate, where they take shortcuts, and why the secure path gets avoided. 
2. Inclusion is a security control
   Speed without inclusion creates blind spots, and blind spots become risk. Security and privacy do not have to slow innovation, but they do have to be designed in a way people can understand and follow. 
3. Governance is behavior
   If governance does not translate into day to day habits, it is just documentation. Training format matters as much as content, and security sticks when people see it as personal responsibility, not corporate paperwork. 

Additional Resources 

• AI Foundations for Women (Empressa AI)
  https://empressa.ai/ai-foundations-for-women/ 
• Most Tools Weren’t Built with Women in Mind, AI Is Just the Latest
  https://empressa.ai/2025/04/03/most-tools-werent-built-with-women-in-mind-ai-is-just-the-latest/ 
• IABC Catalyst, Building Your Brand With Microsoft Senior Storyteller Miri Rodriguez
  https://www.iabc.com/Catalyst/Article/building-your-brand-with-microsoft-senior-storyteller-miri-rodriguez 

About the Guest
Miri Rodriguez is Cofounder and CEO at Empressa.ai, an AI and storytelling strategist, bestselling author, and Microsoft alum. She focuses on ethical innovation, inclusion, and building trustworthy AI environments where women can connect, learn, and thrive. She is also the author of Brand Storytelling: Put Customers at the Heart of Your Brand Story. 

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AI is getting embedded into everything, security workflows, engineering workflows, and customer facing products, often faster than organizations can govern it. The upside is real. The risk is in the assumptions leaders are making while they chase speed. 

In this episode of ClearTech Loop, Jo Peterson sits down with Margaret Dawson, Chief Marketing Officer at SUSE, for a slightly different conversation than our usual guest mix. Same three questions, but through a CMO lens shaped by decades of enterprise buying cycles. 

Margaret breaks down how security leaders can use generative AI to move beyond tools and tech, what it actually takes to embed security and privacy without slowing innovation, and how CMOs should talk about AI without getting trapped in AI washing. The throughline is practical: productivity gains are real, but cost, control, and credibility are not automatic. 

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Key Quotes 
“The mistake that we’re making as leaders is we are assuming that the integration of AI is an automatic reduction in cost.” — Margaret Dawson 

“Until all of a sudden, the CFO got a million dollar cloud bill.” — Margaret Dawson 
“Consumers get smarter, very, very fast, especially BtoB Tech customers, and they start to know what’s real and what’s not.” — Margaret Dawson 

“Being very specific on what it is doing for your product, for that customer, tying it back to the business outcome.” — Margaret Dawson 
“People trust their peers more than any vendor or anyone else.” — Margaret Dawson 

Three Big Ideas from This Episode 

1. AI adoption fails when leaders treat it like automatic margin 
   The board level narrative is tempting, but dangerous. AI can improve productivity, but assuming it instantly reduces cost is how organizations create governance debt and business continuity risk. 
2. Speed is possible, but only with guardrails 
   Embedding security and privacy is not what slows innovation. Confusion, rework, and incidents slow innovation. The answer is clear boundaries, clear accountability, and controls that keep pace with adoption. 
3. In marketing, relevance and proof beat hype 
   Buyers calibrate fast. AI messaging has to be specific, tied to outcomes, and backed by customer evidence. Credibility is built peer to peer, not through louder claims. 

Resources Mentioned 

• The Secret to Digital Transformation is Human Connection by Margaret Dawson: https://devops.com/the-secret-to-digital-transformation-is-human-connection/ 
• INTERVIEW: SUSE CMO Margaret Dawson on AI, Kubernetes & Open Source | KubeCon + CloudNativeCon NA 2025: https://www.youtube.com/watch?v=kUcEl3hfvG8  
• ClearTech Loop: AI Security Needs Better Execution with Zach Lewis: https://www.buzzsprout.com/2248577 

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AI security is getting marketed like it requires a brand-new playbook—new frameworks, new job titles, new spend. 

In this episode of ClearTech Loop, Jo Peterson sits down with Zach Lewis (CIO/CISO and author of Locked Up) for a practical reset: AI doesn’t erase the fundamentals—it punishes you faster when you ignore them. Zach breaks down where GenAI is already helping security programs today (especially tabletop exercises and prioritization), what it actually takes to embed security and privacy into AI models without slowing innovation (data classification, access controls, segmentation, documentation, least privilege), and why adoption fails when leaders treat AI like a tool rollout instead of a behavior change. 

The takeaway is simple and actionable: get the foundations right, use AI to reduce friction where it matters, and build a culture where AI augments people rather than creating fear.  

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Key Quotes 

“Strong AI security… starts with doing the basics well.” — Zach Lewis  

“One of the best use cases I found for it was tabletop exercises.” — Zach Lewis  

“You had a billion alerts… and you’re like, which one’s important?” — Jo Peterson  

Three Big Ideas from This Episode 

1) AI security is data discipline + access discipline 

Before you talk tools, talk foundations: classify data before it touches a model, segment critical workloads, gate access by role and sensitivity, document prompts/sources/model versions, and enforce least privilege with ongoing testing and validation.  

2) GenAI can make readiness more real (tabletop exercises) 

Instead of running the same scripted scenario every year, GenAI can generate realistic incidents, inject curveballs, and help teams identify missed actions—turning tabletops into a real maturity-building loop.  

3) Adoption is a leadership problem, not a platform problem 

AI initiatives stall when people are afraid or unsupported. Training, shared use cases, and visible wins (time saved, friction removed) create a safe environment where AI augments work rather than threatening it.  

📘 Zach’s book: Locked Up: Cybersecurity Threat Mitigation Lessons from a Real-World LockBit Ransomware Response   https://www.amazon.com/Locked-Cybersecurity-Mitigation-Real-World-Ransomware/dp/1394357044 

Resources Mentioned  

• ClearTech Loop with Michael Machado AI Risk is Mostly Not New:https://www.buzzsprout.com/2248577/episodes/18535354-ai-risk-is-mostly-not-new-with-michael-machado   
• Locked Up by Zach Lewis is available: https://www.amazon.com/Locked-Cybersecurity-Mitigation-Real-World-Ransomware/dp/1394357044 
• NIST AI Risk Management Framework: https://www.nist.gov/itl/ai-risk-management-framework 
• MITRE ATT&CK Framework: https://attack.mitre.org/    

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AI is speeding up both attackers and defenders. The goal is not speed alone. The goal is speed with trust. 

In this episode of ClearTech Loop, Jo Peterson sits down with Stefano Righi, Chief Security Architect at AMI, for a hot take conversation on what AI is changing inside security programs. Stefano breaks down how GenAI can move teams beyond reactive, tool centric security into anticipatory defense through predictive threat modeling, dynamic risk assessment, and orchestration. He also explains what secure by design means for AI systems, including privacy, adversarial resiliency, prompt injection, and data poisoning, plus why human oversight still matters. The conversation closes on firmware security below the operating system and why governance aligned to standards becomes an accelerator, not paperwork. 

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Key Quotes 

• “Governance may act as a catalyst, not as a brake to innovation, enabling innovation while ensuring trust.” — Stefano Righi 
• “From the very start, we need to pursue secure by design for AI model… build privacy and adversarial resiliency into AI life cycles… mitigate risk like prompt injection and data poisoning without slowing innovation.” — Stefano Righi 
• “Firmware runs under the operating system, and any attack that could happen at such layer could go undetected by any antivirus solution running in the operating system.” — Stefano Righi 

Three Big Ideas from This Episode 

1. Governance accelerates trusted AI adoption 
   Governance is not paperwork. Done right, it enables innovation while ensuring trust, and it must be cross functional rather than owned by security alone. 
2. Secure by design has to include AI systems 
   Privacy and adversarial resiliency belong in the AI lifecycle from the start, with attention to risks like prompt injection and data poisoning, plus human oversight to ensure compliance and prevent misuse. 
3. Firmware is a visibility blind spot below the OS 
   Platform layers from microcode to BIOS to BMC to Root of Trust create real complexity, and attacks below the OS can bypass controls that security leaders rely on for visibility. 

Episode Notes / Links 

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Resources Mentioned 

• ClearTech Loop: The CSA AI Safety Initiative with George Finney https://cleartechresearch.com/the-csa-ai-safety-initiative-with-george-finney/  
• NIST AI Standards: https://www.nist.gov/artificial-intelligence/ai-standards   
• OWASP guidance for AI: https://owasp.org/www-project-ai-security-and-privacy-guide/  
• CSA: How Generative AI is Reshaping Zero Trust Security https://cloudsecurityalliance.org/blog/2026/01/09/how-generative-ai-is-reshaping-zero-trust-security  

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Cybersecurity has become a tool driven industry. Organizations buy platforms, stack controls, generate alerts, and ask humans to stitch it all together under pressure.  

In this episode of ClearTech Loop, Jo Peterson sits down with Ryan Lutz to explore what changes when AI becomes part of the security workflow. Not as another console, but as an adaptive capability that helps teams interpret signals faster, prioritize more intelligently, and respond with more consistency when the volume is too high for humans to manage alone.  

The conversation focuses on three real-world themes: 
Why the SOC is the best initial use case for AI augmentation, how leaders should think about the inherent exposure that comes with more AI and more code, and why Ryan’s research on AI malware matters for building adaptive defensive responses.  

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Key Quotes 

“Cyber is a very tool driven industry… with the implementation of AI being generative, I think that we’re going to see AI being used more in a way that’s adaptive.” — Ryan Lutz  

“In a setting like a SOC analyst… you have a ton of information coming in… millions of possible attack vectors… it’s very applicable to use AI… to generate a response very quickly and more efficiently.” — Ryan Lutz  

“How should the CISO be thinking about AI adoption… from an organizational governance perspective, because you don’t want to be the Department of no.” — Jo Peterson  

Three Big Ideas from This Episode 

1) Adaptive beats tool-driven 
AI helps security teams move beyond tool sprawl by accelerating interpretation, prioritization, and decision-making in high-volume environments.  

2) The SOC is the natural first use case 
SOC work is overwhelmed by inputs and possible attack paths. Ryan explains why AI can rank what matters, accelerate analysis, and suggest response paths quickly and efficiently.  

3) Governance must guide adoption without killing innovation 
More AI and more code creates more exposure. The leadership job is balance: govern the use and guide adoption without becoming the “Department of No.”  

Episode Notes / Links 

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Resources Mentioned 

• MITRE ATT&CK Framework https://attack.mitre.org/ 
• NIST Cybersecurity Framework (CSF) https://www.nist.gov/cyberframework 
• ClearTech Loop AI Only Works If Your Foundations Do: A Conversation with Dr. Anton Chuvakin https://www.buzzsprout.com/2248577/episodes/18211623-ai-only-works-if-your-foundations-do-a-conversation-with-dr-anton-chuvakin 

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Cybersecurity has been trapped in a reactive cycle for years: a new threat emerges, a new tool gets purchased, and teams get overwhelmed by alerts. 

In this episode of ClearTech Loop, Jo Peterson sits down with Jen Waltz (Chief Information Security Officer at IMAJENATIVE) to unpack how generative AI can fundamentally disrupt that cycle—shifting the focus from managing tools to achieving strategic outcomes. 

The conversation goes beyond “faster alerts” and gets practical about what’s changing right now: 

• Moving beyond alert triage into predictive threat hunting, including simulating adversary behavior and generating TTP playbooks—especially when paired with threat intel and MITRE ATT&CK data. 
• Upskilling SOC teams by using GenAI to reduce menial work, provide clearer remediation paths, and support more anticipatory defense postures. 
• Embedding security, privacy, and governance early so “secure-by-design” becomes a business enabler, not a speed bump. 

Jen also gives a clear governance warning: as AI adoption accelerates, organizations must guide usage with approved tools and acceptable-use controls—especially to reduce the risk of sensitive data being dropped into consumer AI chat tools like ChatGPT. 

If you’re responsible for security operations, AI strategy, or governance, this episode offers a grounded path for how to adopt GenAI without losing control. 

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Key Quotes 

“Cybersecurity has long been trapped in this reactive cycle… generative AI… can fundamentally disrupt the cycle by shifting the focus from managing tools to achieving strategic outcomes.” — Jen Waltz 

“The CISO no longer is this superhero defender of the perimeter. You have to become a business strategist…” — Jen Waltz 

Three Big Ideas from This Episode 

1. GenAI can break the reactive cycle—if teams target outcomes, not tools 
Jen frames GenAI as an opportunity to move beyond buying more technology and instead shift security programs toward strategic outcomes and anticipatory defense. 

2. Predictive threat hunting becomes practical with TTP playbooks + MITRE ATT&CK context 
Rather than only prioritizing alerts, Jen describes prompting GenAI to simulate adversaries and generate playbooks—then connecting that to threat intel and MITRE ATT&CK data to anticipate attacker evolution earlier. 

3. AI governance is a leadership mandate—and the CISO role expands 
Jen argues the CISO must operate as a business strategist balancing innovation enablement with risk governance. That includes guiding internal AI use with hardened, approved tools and clear controls—without shutting down creativity. 

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Resources Mentioned 

• MITRE ATT&CK Framework: https://attack.mitre.org/resources/attack-data-and-tools/  
• NIST Cybersecurity Framework (CSF): https://www.nist.gov/cyberframework  
• ISO/IEC 27001 (ISMS): https://www.iso.org/standard/27001  
• ISO/IEC 42001 (AI Management System): https://www.iso.org/standard/42001  

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AI is being embedded into enterprise tools faster than most organizations can govern it. 

Productivity platforms, security systems, and development workflows now include AI capabilities by default, often without a single approval moment or clear ownership model. 

In this episode of ClearTech Loop, Jo Peterson sits down with Nicolas Moy, Founder and CIO of LifeMark Financial and vCISO for Security Engineering at Halyard Labs, to talk about what AI security looks like in practice when it is treated as software, not as a separate discipline. 

Nicolas shares how security teams are already using AI today to accelerate policy development, reduce operational noise, and support threat modeling earlier in the design and build process. The conversation also explores why governance is struggling to keep pace with employee behavior, especially as sensitive information enters AI systems without clear visibility into where data goes or how it is reused. 

Rather than framing AI security as a future problem, this discussion focuses on what CISOs and CIOs are dealing with right now, and why accountability has to keep pace as AI compresses timelines across security and technology decisions. 

If you are navigating AI adoption across security, development, and governance, this episode provides a grounded perspective on how to approach AI without losing control. 

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Key Quotes 

“For AI, it’s similar, it’s software, but there’s some new evolutions to it.” 
— Nicolas Moy, CISSP, CCSK 

“If my employee puts this confidential information into an AI chat system, where is that being shipped out to?” 
— Nicolas Moy, CISSP, CCSK 

Three Big Ideas from This Episode 

1. AI security accelerates familiar risks rather than creating new ones 

Treating AI as software brings it into existing security and DevSecOps practices earlier, rather than isolating it as a separate problem. 

2. Governance is lagging behind real employee behavior 

AI tools are being used inside normal workflows faster than policies and controls were designed to handle. 

3. CISOs and CIOs must engage together earlier 

AI security sits between architecture, data governance, and risk ownership, requiring shared accountability across roles. 

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Resources Mentioned 

• OWASP Top 10 for Large Language Model Applications
  https://owasp.org/www-project-top-10-for-large-language-model-applications/ 
• OWASP AI Project
  https://owasp.org/www-project-ai/ 
• ClearTech Loop Episode: AI as a Digital Co Worker with Timothy Youngblood
  https://www.buzzsprout.com/2248577/episodes/18509846-ai-as-a-digital-co-worker-with-the-experience-of-an-intern-with-timothy-youngblood L
• Learn more about Nicolas NicolasMoy.com

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AI did not arrive through a single decision. It crept into enterprises through productivity tools, cloud platforms, security products, and SaaS applications that teams were already using. 

Most organizations did not choose to adopt AI. They woke up and realized it was already there. 

In this episode of ClearTech Loop, Jo Peterson sits down with Travis Farral, Vice President and Chief Information Security Officer at Archaea Energy, to talk about what that reality means for security leaders who are being asked to govern AI systems that are still evolving in real time. 

Travis explains why AI cannot be stopped, only shaped, and why the real risk is not the technology itself but the lack of clarity around what is actually being deployed. 

“This is not something that we’re going to be able to stop,” he said. “Even if we wanted to. It’s like standing in front of a tidal wave.”  

The conversation covers: 

• Why “AI” has become a dangerously vague label 
• How the AI threat model is shifting toward training data, prompts, and model behavior 
• Why frameworks from NIST, OWASP, and MITRE already exist 
• Why fluency, not guidance, is the real gap 
• How CISOs can define guardrails without becoming the Department of No 

If you are responsible for cybersecurity, data governance, or enterprise risk, this episode offers a grounded way to think about AI adoption without losing control of your environment. 

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Key Quote 

“This is not something that we’re going to be able to stop. Even if we wanted to. It’s like standing in front of a tidal wave.” 
Travis Farral, CISO, Archaea Energy  

Additional Resources 

• NIST AI Risk Management Framework Travis specifically called out NIST as one of the primary sources for understanding the risks and controls around generative and agentic AI: https://www.nist.gov/itl/ai-risk-management-framework 
• OWASP Top 10 for Large Language Model Applications When Travis talked about protecting prompts, inputs, and model interfaces, he was pointing directly at the kinds of risks OWASP is mapping for LLMs. https://owasp.org/www-project-top-10-for-large-language-model-applications/ 
• MITRE ATLAS MITRE’s Adversarial Threat Landscape for AI is one of the frameworks Travis referenced when he talked about how attacks against models are different from traditional exploits. https://atlas.mitre.org/ 
• ClearTech Loop with Dutch Schwartz Travis’s comments about guardrails, controls, and not being the Department of No connect directly to Dutch’s episode on pragmatic AI safety. https://cleartechresearch.com/bumpers-not-brakes/ 

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AI has technically been around for years. What changed is not the math, it is the front door. Suddenly anyone in the organization can touch it, feed it data, and make decisions with it and that shift in accessibility is rewriting business risk.  

In this episode of ClearTech Loop, Jo Peterson sits down with Michael Machado, CISO and Chief Data Officer at Hyland, to break down a calm, practical truth CISOs need right now. Most of the AI risk conversation is not new. The disciplines are familiar. Visibility. Data movement. Accountability. Audit trails. Resilience. What is different is the speed and the number of people who can now participate in risk without realizing it. 

The conversation focuses on leadership realities, not hype: 

• Why there is risk in doing things and risk in not doing things 
• How AI accessibility changes governance pressure inside enterprises 
• Why governance should start with business goals, not tools 
• What it means to build an AI governance model that is multi department by design 
• Why CISOs should measure adoption and value signals, not only exposure 

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Key Quotes 
“Waves of technology come. Cloud, SaaS, mobile, AI. The muscles we flex are things we have seen before.” 
Michael Machado 

“There’s a risk of doing things and a risk of not doing things, and it’s important to strike a balance when we’re having that conversation.” 
Michael Machado 

Three Big Ideas from This Episode 

1. AI risk is not new, accessibility is 
   The models are not the headline. The fact that anyone can use them is. That changes how quickly data moves and how quickly decisions get made. 
2. Governance starts with the business problem 
   Tool first governance creates policies that look responsible and work poorly. Start with the objective, map the data movement, then apply controls that support the mission.  
3. Measure value analytics alongside risk analytics 
   It is not enough to track what could go wrong. CISOs also need visibility into whether tools are being used and whether adoption is producing meaningful value. 

Episode Notes / Links
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• Resources Mentioned
  An Evolution of Defensive Security Operations: From Simple Detection to Modern SOC Automation https://www.linkedin.com/pulse/evolution-defensive-security-operations-from-simple-modern-machado-unctc/  
• NIST AI Risk Management Framework https://www.nist.gov/itl/ai-risk-management-framework  
• ClearTech Research Insights https://cleartechresearch.com  

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As AI becomes embedded across security operations and business workflows, organizations are confronting a new reality. AI is no longer just a tool. It is behaving like a digital co-worker acting on data, surfacing decisions, and influencing outcomes. 

In this episode of ClearTech Loop, Jo Peterson sits down with Timothy Youngblood, a four-time Fortune 500 CSO and CISO, board member, angel investor, and adjunct professor, to explore what it really means to manage AI responsibly at scale. 

Tim introduces a powerful and practical analogy: AI as a digital co-worker with the experience of an intern. Capable, fast, and eager, but not ready to operate without oversight, guardrails, and accountability. 

The conversation looks beyond hype and focuses on leadership realities: 

• Why AI capability is advancing faster than accountability models 
• How AI agents quietly expand risk through data aggregation 
• Why governance must be operational, not policy driven 
• How oversight enables innovation instead of slowing it down 
• What CISOs and executives must own as AI becomes embedded across the enterprise 

If you are responsible for cybersecurity, risk, or enterprise technology strategy, this episode offers a grounded way to think about AI adoption without losing control. 

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Key Quotes 

“That digital worker right now has the experience of a slightly experienced intern. And you wouldn’t let a slightly experienced intern go off on their own and start doing things without some oversight.” 
— Timothy Youngblood 

“I’ve been in this industry 30 years, and I try to make sure people can learn from all the mistakes I’ve made. And I’ve made many.” 
— Timothy Youngblood 

Three Big Ideas from This Episode 

1. AI should be treated like a junior employee, not an autonomous system 

AI can move fast, analyze data, and surface insights, but it lacks judgment and accountability. Treating AI as a digital co-worker reframes governance around supervision and responsibility. 

2. Guardrails must exist before AI is deployed, not after 

AI agents aggregate data and create new risk simply by combining systems. Governance applied after deployment documents exposure instead of preventing it. 

3. Oversight is the control that enables sustainable innovation 

Human review, scoped access, and accountability are not blockers. They are what allow organizations to experiment with AI without creating consequences they cannot unwind. 

Episode Notes / Links 

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Resources Mentioned 

AI’s Newest Employee: Who Bears the Burden of Your Digital Co-Workers
https://tdan.com/ais-newest-employee-who-bears-the-burden-of-your-digital-co-workers/ 

To Fix AI Governance, Stop Building It Backwards
https://www.reworked.co/digital-workplace/to-fix-ai-governance-stop-building-it-backwards/ 

ClearTech Loop: AI, Trust, and Growth with Mike Britton
https://cleartechresearch.com/clear

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