Infogov Hot Seat

Information Governance, GenAI, and Records Management in the Federal vs. Private Sectors

8 min · 7 de jun de 2026
Portada del episodio Information Governance, GenAI, and Records Management in the Federal vs. Private Sectors

Descripción

In this live episode of the InfoGov Hot Seat from ARMA’s Federal Summit, host Jim Merrifield sits down with Kon Leong, CEO and Co-founder of ZL Technologies. With over 26 years of experience managing petabytes of unstructured data for Fortune 100 companies, Kon shares his unique perspectives on how the rapid rise of generative AI is changing the landscape of data governance. Highlights from this episode include: * A Personal Look: Kon discusses his interest in Wabi-Sabi, the Japanese philosophy of embracing imperfection, and how it translates to handling the real-world complexities of human data. * Federal vs. Private AI Adoption: An analysis of why the public sector is facing a distinct set of hurdles compared to the private sector when integrating breaking AI technologies. * Unifying the Silos: Why traditional data silos crash and burn under today's massive data volumes, and why a unified platform approach is necessary to satisfy FOIA, NARA, litigation, and privacy regulations. * Key Advice for Federal Records Officers: Kon explains why leaders need to "put on their high beams" and focus on long-term strategy rather than quick-fix point solutions. To learn more about Kon's work, visit zlti.com.

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episode Federal Records Management, AI, and Why "Content is Key" with Hyland’s Wesley Callahan artwork

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episode AI-Driven Information Governance: Inside the ARMA Federal Summit with Will Talbot (Laserfiche) artwork

AI-Driven Information Governance: Inside the ARMA Federal Summit with Will Talbot (Laserfiche)

In this live episode of the InfoGov Hot Seat, host Jim Merrifield (Chief Data Officer, Robinson+Cole) sits down with Will Talbot, Manager of Enterprise Sales at Laserfiche, direct from the ARMA Federal Summit in Reston, Virginia. With over 12 years of experience in records and information management, Will dives deep into the biggest challenge facing federal records officers today: overcoming user resistance and making compliance seamless. He shares how Artificial Intelligence (AI) is completely transforming the Information Governance (IG) landscape—shifting the burden away from manual metadata entry and towards powerful, natural language automation. * The Evolution of Laserfiche: From translating microfiche to laser discs 50 years ago to pioneering modern, paperless cloud enterprise content management (ECM). * AI as an IG Game Changer: How generative AI and intelligent software agents allow users to manage, classify, and audit millions of records effortlessly using natural language commands. * Streamlining Compliance & Transparency: Overcoming the risk of "shelfware" by prioritizing user interface (UI) and user experience (UX) to boost organizational adoption. * The Value Formula: A look at how combining Data + Information + Records ultimately equals core business value. “The easier you can make it for people to manage their records, the more likely they are to actually do it and maintain compliance.” — Will Talbot * Learn more about Laserfiche: Laserfiche Official Website [https://www.laserfiche.com]

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episode AI Readiness and Records Management with John Beglan artwork

AI Readiness and Records Management with John Beglan

In this episode of the InfoGov Hot Seat, host Jim Merrifield sits down with John Beglan from Tungsten Automation live at the ARMA Federal Summit in Reston, Virginia. John discusses how Tungsten Automation (formerly known as Kofax) is tackling the unique challenges faced by the federal government, focusing on driving efficiencies through intelligent capture, case management, and records management. They dive deep into the buzz surrounding agentic AI, the realities of government infrastructure, and why the path forward requires a shared data foundation between industry and the public sector. John also shares a key piece of advice for federal records officers looking to prepare for the future of AI. * Targeted Focus: Rather than trying to "boil the ocean," focus on specific mandates and proven use cases like case, grant, and records management. * The AI Gap: While "agentic AI" is a popular buzzword, the federal government faces constraints in skills, infrastructure, and sustained funding before widespread adoption can take off. * Aging Infrastructure: Approximately 70% of federal IT systems in the country are 10 to 30+ years old, creating a massive hurdle for modern AI readiness. * A Collaborative Solution: Success will require clear standards, strong data foundations, and open collaboration between industry experts and government agencies. * John Beglan – Sales Director, Tungsten Automation * Website: Tungsten Automation [https://www.tungstenautomation.com]

7 de jun de 20268 min
episode Information Governance, GenAI, and Records Management in the Federal vs. Private Sectors artwork

Information Governance, GenAI, and Records Management in the Federal vs. Private Sectors

In this live episode of the InfoGov Hot Seat from ARMA’s Federal Summit, host Jim Merrifield sits down with Kon Leong, CEO and Co-founder of ZL Technologies. With over 26 years of experience managing petabytes of unstructured data for Fortune 100 companies, Kon shares his unique perspectives on how the rapid rise of generative AI is changing the landscape of data governance. Highlights from this episode include: * A Personal Look: Kon discusses his interest in Wabi-Sabi, the Japanese philosophy of embracing imperfection, and how it translates to handling the real-world complexities of human data. * Federal vs. Private AI Adoption: An analysis of why the public sector is facing a distinct set of hurdles compared to the private sector when integrating breaking AI technologies. * Unifying the Silos: Why traditional data silos crash and burn under today's massive data volumes, and why a unified platform approach is necessary to satisfy FOIA, NARA, litigation, and privacy regulations. * Key Advice for Federal Records Officers: Kon explains why leaders need to "put on their high beams" and focus on long-term strategy rather than quick-fix point solutions. To learn more about Kon's work, visit zlti.com.

7 de jun de 20268 min
episode AI Governance and Defensible Disposal: A Practical Roadmap for 2026 artwork

AI Governance and Defensible Disposal: A Practical Roadmap for 2026

In this episode of the InfoGov Hot Seat, experts tackle one of the biggest mistakes organizations make with defensible disposal: treating it as an all-or-nothing initiative that must be completed at once. Learn why this approach erodes credibility and how to build a sustainable framework for compliance instead. The discussion covers practical implementation strategies for defensible disposal, AI governance controls, and the critical roadmap for information governance success in 2026. KEY TOPICS COVERED: - Why large-scale, poorly socialized disposal initiatives fail - How failed big-bang projects make it harder to restart IG efforts - Starting small with low-hanging fruit to build momentum - Managing large-scale matter mobility between law firms - Expanding governance across collaborative platforms (Microsoft 365, Teams, SharePoint) - Providing better insights into physical records disposition - Executing large-scale destruction pilots in the first 90 days - Robust audit utilities for ISO and SOC 2 certification requirements - AI governance controls built on governance-first architecture - Managing sensitive data like PII and PHI in AI environments - Navigating retention requirements for AI prompts and outputs CRITICAL INSIGHTS: → Defensible disposal is not all-or-nothing—start small and scale → Failed big initiatives damage credibility and make restarts harder → Target low-hanging fruit first to demonstrate value quickly → Build a compliance framework incrementally over time → AI should augment human governance, not replace it → Governance-first architecture is essential for AI controls → AI prompt and output retention requires sector-specific evaluation → Avoid introducing guesswork into AI governance decisions → Risk versus benefit analysis is crucial for prompt retention IG PRIORITIES FOR 2026: - Large-scale matter mobility between firms - Cross-platform governance for collaborative tools - Physical records disposition insights and automation - Microsoft 365 integration to meet users where they work - First 90-day destruction pilots for physical and electronic records - Comprehensive audit trails for regulatory compliance AI GOVERNANCE APPROACH: - Build controls on top of governance-first architecture - Focus on managing PII and PHI in AI workflows - Evaluate geopolitical and sector-specific requirements - Research and education needed for prompt retention policies - Balance innovation with defensible governance practices PRACTICAL IMPLEMENTATION: - Be pragmatic—perfection is the enemy of progress - Pilot initiatives to work through stakeholder communication - Start with one practice group or department - Document successes to build organizational buy-in - Use audit utilities to demonstrate compliance value - Celebrate quick wins to maintain momentum FINAL RECOMMENDATION: To improve IG outcomes in the next 30 days, be pragmatic and start small. Focus on piloting initiatives that allow you to work through stakeholder communication and potential challenges before scaling firm-wide. WHO SHOULD WATCH: - Information governance professionals planning disposal projects - Records managers dealing with retention backlogs - Legal operations leaders implementing AI governance - Compliance officers preparing for audits - IT directors managing collaborative platforms - Anyone who has seen a big-bang IG project fail This conversation provides the honest, practical guidance needed to avoid common pitfalls and build sustainable information governance programs that actually work. Subscribe for more insights on information governance, defensible disposal, and AI governance strategies. #DefensibleDisposal #InformationGovernance #AIGovernance #LegalTech #IGDay

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