Compliance and AI

What is the intersection of AI and compliance? What about Machine Learning? Are you using ChatGPT? These questions are just three of the many we will explore in this cutting-edge podcast series, Compliance and AI, hosted by Tom Fox, the award-winning Voice of Compliance. In this episode, host Tom Fox visits Kunal Chopra, CEO of Certivo, an AI-native regulatory intelligence and compliance management platform for supply chains.

Chopra brings nearly two decades of experience across technology leaders like Amazon, Microsoft, and Groupon to the conversation on AI-powered compliance and regulatory intelligence. Drawing on his supply chain background, he argues that compliance should be treated as a market access function that helps companies enter markets faster, protect revenue, and manage global regulatory change more effectively. He believes AI can transform compliance from a reactive, manual burden into a proactive business enabler by continuously tracking rules, extracting key data from documents, and coordinating communication across the supply chain. In his view, this shift frees teams from repetitive work and makes compliance a strategic driver of growth rather than just a legal necessity.

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What is the intersection of AI and compliance? What about Machine Learning? Are you using ChatGPT? These questions are just three of the many we will explore in this cutting-edge podcast series, Compliance and AI, hosted by Tom Fox, the award-winning Voice of Compliance. In this episode, host Tom Fox visits Brian Holyfield, Co-Founder & Chief Product Officer at SendSafely.

Holyfield’s background in ethical hacking and real-world security testing shapes his practical view of cybersecurity. He believes compliance should reflect how breaches actually happen, especially through vendors and service providers, which means organizations must look beyond their own perimeter. For him, data minimization and retention controls are essential: companies should keep only the data they truly need, delete unnecessary copies, and limit where sensitive information lives. Holyfield also stresses reducing the blast radius, arguing that the best defense is to assume a breach will occur and design systems so attackers can access as little data as possible for as short a time as possible.

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What is the intersection of AI and compliance? What about machine learning? Are you using ChatGPT? These questions are just three of the many we will explore in this cutting-edge podcast series, Compliance and AI, hosted by Tom Fox, the award-winning Voice of Compliance. In this episode, host Tom Fox visits with Clarence Chio, co-founder & CEO of Coverbase.

Chio and Coverbase are helping lead the shift toward AI-driven third-party risk management and vendor security. Drawing on his background in machine learning, security, and compliance, he argues that vendor due diligence is moving beyond slow, human-to-human questionnaire exchanges toward AI agents that can analyze standardized, verified evidence directly. He sees this as the next evolution of trust centers and attestation workflows but cautions that automation should not replace genuine accountability in areas that require human judgment. In his view, the best AI systems will accelerate reviews, flag uncertainty, and escalate gray areas to people rather than hallucinate or blindly accept responses.

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What is the intersection of AI and compliance? What about machine learning? Are you using ChatGPT? These questions are just three of the many we will explore in this cutting-edge podcast series, Compliance and AI, hosted by Tom Fox, the award-winning Voice of Compliance. In this episode, host Tom Fox visits with Diego Panama, new CEO of LogicGate.

Panama brings a disciplined, business-focused perspective to the future of AI-driven GRC platform strategy and risk management transformation. He believes AI is turning GRC from a reactive, checkbox exercise into a strategic, board-level capability, where a holistic platform can unify third-party, cyber, supply chain, and enterprise risks in real time. Rather than leaving professionals buried in operational tasks, he sees agentic AI handling assessments, recommendations, and continuous monitoring so teams can focus on risk appetite, governance, and business outcomes. For Panama, the future of GRC is increasingly autonomous but still human-led, with strong data governance, clear priorities, and responsible use of emerging technology enabling faster, more precise, and more valuable risk management.

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What is the intersection of AI and compliance? What about machine learning? Are you using ChatGPT? These questions are just three of the many we will explore in this cutting-edge podcast series, Compliance and AI, hosted by Tom Fox, the award-winning Voice of Compliance. Today, Tom visits with Dr. Gleb Tsipursky about his book, The Psychology of AI Adoption at Work: From Resistance to Results (Georgetown University Press), arguing that AI adoption fails mainly due to human factors, not tool complexity.

Citing Pew research showing widespread anxiety about AI and an MIT finding that 95% of AI pilots fail to scale, Dr. Tsipursky describes three emotional blockers: fear of job loss (“AI alarmists”), identity threat when AI automates work people take pride in (“pragmatic resisters”), and shame-driven “reluctant adopters” who use AI secretly, fueling shadow AI risk and limiting ROI. He advises leaders to commit to growth over layoffs, automate disliked tasks first, model AI use, and create sharing channels and meetings to normalize safe adoption. He also emphasizes governance with clear ethical guardrails and individual accountability, replacing approval bottlenecks that drive shadow use.

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Book: The Psychology of AI Adoption at Work on Amazon

Website: Disaster Avoidance Experts, LLC

What is the intersection of AI and compliance? What about machine learning? Are you using ChatGPT? These questions are just three of the many we will explore in this cutting-edge podcast series, Compliance and AI, hosted by Tom Fox, the award-winning Voice of Compliance. In this episode, host Tom visits with Nikunj Bajaj, Co-founder & CEO at TrueFoundry, to discuss enterprise agentic AI infrastructure, governance, and hidden costs.

Nikunj Bajaj brings a practical enterprise lens to the rise of agentic AI, shaped by years of working at the intersection of model development and production infrastructure. He argues that enterprise AI is not just a technical challenge but also an organizational one, because federated teams adopting different tools can quickly create sprawl, inconsistent controls, and governance gaps. To address this, he advocates for a unified gateway layer that centralizes observability and control while still allowing teams to build with best-of-breed frameworks, paired with targeted safeguards like auditability, RBAC, guardrails, and the ability to inspect or revert agent actions. Bajaj also stresses that successful enterprise adoption requires disciplined cost management through FinOps, chargebacks, and budget guardrails so companies can move quickly toward ROI without letting agentic systems become a governance risk or a runaway expense.

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What is the intersection of AI and compliance? What about machine learning? Are you using ChatGPT? These questions are just three of the many we will explore in this cutting-edge podcast series, Compliance and AI, hosted by Tom Fox, the award-winning Voice of Compliance. Today, Tom visits with Mouhcine Jalili, VP of Growth – iGaming at Software Mind, to reframe iGaming compliance as a design, delivery, and platform challenge rather than an end-stage legal checklist.

Jalili brings 15 years of exclusive iGaming experience, having grown from operational roles into commercial, team growth, and technology-focused leadership, and he currently serves as Vice President for Growth in iGaming at Software Minds. He views operational compliance and governance as a design-and-delivery challenge rather than merely a legal checklist, because many of the biggest risks arise when product changes are rolled out across regulated markets without the right release management and controls. From his perspective, responsible gambling and other market-specific requirements should be engineered into the product from the start through automated controls, strong configuration management, and close collaboration between compliance, product, delivery, and engineering teams. Overall, Jalili believes iGaming governance works best when compliance is embedded directly into the system architecture and operational process, making the whole organization more resilient and easier to scale.

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What is the intersection of AI and compliance? What about machine learning? Are you using ChatGPT? These questions are just three of the many we will explore in this cutting-edge podcast series, Compliance and AI, hosted by Tom Fox, the award-winning Voice of Compliance. Today Tom visits with Bennett B. Borden, a lawyer-data scientist and former CIA analyst who led DLA Piper’s global AI practice before founding Clarion AI Partners, an AI-focused law firm and development shop building AI solutions with governance “baked in.”

Borden argues generative AI is transformative and that most legal work is highly repetitive and largely automatable, making traditional billable-hour law practice unsustainable. He frames AI governance as a compliance responsibility because AI operationalizes business objectives within regulatory constraints and must produce measurable, defensible proof of compliant behavior. He recommends cross-functional AI committees, using enterprise-licensed tools with enforceable policies, and building trust through controlled systems and quality controls. In a patchwork regulatory landscape, he emphasizes “reasonableness” and proving foreseeable risks are mitigated. He advises boards to oversee AI strategy, warns against delaying adoption, and urges compliance leaders to translate legal requirements into technical metrics (“governance engineering”).

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Clarion AI Partners

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What is the intersection of AI and compliance? What about machine learning? Are you using ChatGPT? These questions are just three of the many we will explore in this cutting-edge podcast series, Compliance and AI, hosted by Tom Fox, the award-winning Voice of Compliance. Today Tom visits with Paul Welter, a German lawyer and former software engineer who co-founded Bayshore AI after research at Stanford Law School’s Codex on automating legal reasoning.

Welter explains Bayshore’s approach: extracting legal decision logic into deterministic, conventional code for predictable, explainable outcomes, while using large language models to gather scenario facts and handle vague legal terms. They discuss regulation as infrastructure for trust and economic activity and how today’s complexity creates bottlenecks that AI can alleviate by providing legal and compliance advice “in abundance.” Welter describes tailoring assessments to each customer’s policies and risk appetite, embedding them into workflows, and building trust through transparency, second-line control, and auditability for regulators. He highlights automation candidates (e.g., gifts/hospitality, third-party reviews) and advises teams to centralize request intake, measure frequency and effort, and automate iteratively.

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Bayshore

What is the intersection of AI and compliance? What about Machine Learning? Are you using ChatGPT? These questions are just three of the many we will explore in this cutting-edge podcast series, Compliance and AI, hosted by Tom Fox, the award-winning Voice of Compliance. Today, Tom visits with Kunal Vankadara, CEO & Co-founder at Haast, about using AI to help regulated organizations scale compliance as content volume explodes and regulatory scrutiny increases.

Kunal, a former attorney and ex-BCG consultant, describes how manual marketing and public-content review once worked when content cycles were slower, but he is now overwhelmed by AI-driven content creation, channel proliferation, and personalization. He explains that many compliance decisions are subjective and tied to organizational risk tolerance, which Haast “teaches” to AI agents to provide first-line content review, reduce iterations, and route only gray-area items for human approval. The discussion covers managing “false positives” via risk-tolerance tuning, creating competitive advantage through speed-to-market and personalization, using an ROI calculator focused on business outcomes, and making regulatory changes more actionable across the business.

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Haast

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