<![CDATA[Guardians of the Data]]>https://www.guardiansofthedata.showhttps://substackcdn.com/image/fetch/$s_!6c6Z!,w_256,c_limit,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2F82bb6092-bf81-4719-a5b9-8777fc9bb5ca_192x192.pngGuardians of the Datahttps://www.guardiansofthedata.showSubstackTue, 22 Sep 2026 00:27:53 GMT<![CDATA[Guardrails in the Wild West - Ronak Patel - Guardians of the Data - Episode # 60]]>https://www.guardiansofthedata.show/p/guardrails-in-the-wild-west-ronakhttps://www.guardiansofthedata.show/p/guardrails-in-the-wild-west-ronakThu, 17 Sep 2026 14:01:19 GMT In this episode, Ward sits down with longtime friend and 25 year cybersecurity veteran Ronak Patel to unpack why AI has turned data security into the Wild West all over again. Ronak walks through how the rapid, ungoverned adoption of AI tools across organizations is recreating the same chaos we saw with early cloud migration, just at a much faster pace. From foundational guardrails like CASB and DLP to the shift from preventing data loss to preventing data exposure, Ronak makes the case that the technology has changed, but the fix still starts with the same thing: understanding your data. The conversation closes with Ronak's candid, hard earned advice for security professionals navigating one of the toughest job markets the industry has seen in years.

Takeaways:

  • AI adoption is moving at hyper speed, and most organizations are rolling it out without the checks and balances that real enterprise adoption requires. Treat AI the same way you’d treat shadow IT: understand what platforms your people are actually using before you try to control them.

  • The conversation around data protection needs to shift from just stopping data loss to preventing data exposure. Copilots and AI agents don’t need to move your data outside the org to create risk, they just need inappropriate access to it.

  • Before you can put guardrails around AI, you need the same foundation good data security has always required: understanding your data, who owns it, where it lives, and who’s allowed to touch it.

  • Foundational controls like email inspection, CASB, proxy, and DLP still matter. Layer AI detection on top of that foundation instead of trying to solve for AI in isolation.

  • In a brutal job market, your network matters more than your resume. Use AI to tailor your resume and cover letter for every role, but go through your connections before you apply cold through a portal.

"A data protection program is not a tool at all. It is a program that has tools, but it also has processes and people, all of this living in harmony to actually be able to protect." - Ronak Patel

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]]><![CDATA[Stop Blaming the Human - Sam Wolf - Guardians of the Data - Episode # 59]]>https://www.guardiansofthedata.show/p/stop-blaming-the-human-sam-wolf-guardianshttps://www.guardiansofthedata.show/p/stop-blaming-the-human-sam-wolf-guardiansThu, 10 Sep 2026 14:03:38 GMTIn this episode, Sam Wolf, assistant director of engineering and data security in financial services, makes the case that security teams have been pointing the finger in the wrong direction. It is not the human who is the weakest link, it is the systems built without the human in mind. Sam breaks down why the "department of no" mindset creates the very workarounds that put organizations at risk, and why the fix starts with understanding what the business is actually trying to accomplish before adding another

Takeaways:

  • Stop blaming the human for finding the path of least resistance. If people keep bumping into the same workaround, that is a design problem, not a training problem. Build controls around how people actually work, not how you wish they worked.

  • Retire the instinct to solve every gap with more training. A secure workflow should not require a class to use safely. If the right way is harder than the easy way, people will find the easy way every time.

  • Before greenlighting the next AI request, ask what happens if you say no. That single question separates a real business need from FOMO, and it gives you a starting point for mapping the request back to strategy and mission.

  • Treat tech debt like a product problem, not just a technical one. Look for the pieces you can decouple and simplify before adding another layer on top, and use contract renewal windows as a natural point to consolidate tools.

  • Document decisions the moment you make them, not after the fact. A shared record of what was agreed protects both security and the business, and it turns “why didn’t you catch this” into “here is what we agreed to.”

“Attitude, aptitude, and initiative. I can figure it out, you can figure it out.” - Sam Wolf

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]]><![CDATA[Guardrails, Not Gadgets - Todd Covert - Guardians of the Data - Episode # 58]]>https://www.guardiansofthedata.show/p/guardrails-not-gadgets-todd-coverthttps://www.guardiansofthedata.show/p/guardrails-not-gadgets-todd-covertThu, 03 Sep 2026 14:01:41 GMTIn this episode, Ward Balcerzak sits down with former CISO Todd Covert, who brings over 25 years of experience across healthcare, insurance, and fintech to unpack why data security still hasn't been solved. Todd breaks down the human side of the problem, from employees just trying to do their jobs without clear guardrails, to the challenge of protecting data whose sensitivity changes by the hour, to how AI tools have made it easier than ever to put information at risk without meaning to. The conversation moves from the technical to the deeply practical, covering how security leaders can build influence, communicate across different audiences, and turn their toughest critics into advocates.

Takeaways:

  • Most employees aren’t trying to misuse data, they’re trying to do their jobs, and often security hasn’t given them a clear, easy path to do it safely.

  • Data sensitivity isn’t fixed. A document can be highly confidential today and public tomorrow, and organizations still haven’t solved how to manage that shifting risk.

  • AI tools have made it dramatically easier to expose sensitive data, often without any bad intent involved, which raises the stakes on getting guardrails right.

  • Winning adoption for a security process means identifying your toughest critics early and working to turn them into advocates, rather than avoiding them.

  • Communication style matters as much as the message itself. Data driven leaders, emotionally driven leaders, and different departments all need to be approached differently to build real buy in.

"If I can take my toughest critics and turn them into advocates, that's where I can have that success." - Todd Covert

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]]><![CDATA[Security Beyond the Code - Omar Sangurima - Guardians of the Data - Episode # 57]]>https://www.guardiansofthedata.show/p/security-beyond-the-code-omar-sangurimahttps://www.guardiansofthedata.show/p/security-beyond-the-code-omar-sangurimaThu, 27 Aug 2026 14:00:43 GMTIn this episode, Omar Sangurima sits down with Ward to unpack why so many organizations are still stuck on the most basic question in data security: do you actually know what data you have and where it lives? Omar draws on his background in sales, finance, and now healthcare cyber governance to explain why the real work isn’t technical, it’s people and process. From navigating legacy environments to earning the trust to push back on executive mandates, Omar breaks down how understanding the business first, and the technology second, is what separates real data protection from what he calls kabuki theater.

Takeaways:

  • Start with inventory, not tools. Before buying another platform, get honest about what data you have and where it lives. Most organizations already own tools that can do this, the real gap is appetite and follow through.

  • Understand the business before you try to protect it. Every organization has a core engine, whether that’s patient care, transactions, or something else, and knowing what fuels that engine tells you what data actually matters. Work backwards from there to build your protection strategy.

  • Pair conversations with telemetry. Relationships give you context, but data gives you proof. Combine both so you can walk into any executive meeting with the problem, the solution, and the ask.

  • Don’t just lift, shift, and plop into the cloud. Migrating without optimizing just moves your old problems to a new address. Listen to the people who know where the risks are buried before you make the leap.

  • Earn the right to push back. Build a reputation for actually getting things done, then use that credibility to challenge a mandate at most twice, respectfully, before executing anyway. Nobody trusts an advisor who only says yes or only says no.

"You have to have the receipts and you have to have the ability to show that you can be trusted, trusted to get stuff done, trusted to only push back when it matters." - Omar Sangurima

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]]><![CDATA[Data Hoarding Equals Liability - Dameon Sherman - Guardians of the Data - Episode # 56]]>https://www.guardiansofthedata.show/p/data-hoarding-equals-liability-dameonhttps://www.guardiansofthedata.show/p/data-hoarding-equals-liability-dameonThu, 20 Aug 2026 09:02:05 GMTIn this episode, Dameon joins Ward Balcerzak to make the case that data security still starts with the fundamentals most organizations think they’ve already solved: knowing what data you have, where it lives, and whether it’s actually trustworthy. Drawing on lessons from combat IT work in Iraq and Afghanistan, nuclear program accreditation with the Navy, and years navigating federal contracting rules, Dameon breaks down why disparate CMDBs, data hoarding, and reactive retention policies leave companies exposed. He also unpacks the looming “harvest now, decrypt later” threat posed by quantum computing and why treating data like a physical asset, cataloged, tagged, and continuously monitored, is the only way to stay ahead of it.

Takeaways:

  • Treat your data like a physical asset. Inventory it, tag it, and catalog it the same way you would any piece of hardware, because you cannot protect what you do not know you have.

  • A CMDB is only as good as its design. Map out the elements you need to capture before you build the system, not after, or you will spend years fixing accuracy problems.

  • Data quality is a security issue in disguise. If you cannot identify what is useful versus erroneous, you cannot apply the right protections or control your storage costs.

  • Retention policies mean nothing if you do not enforce them. Purge data on schedule, because anything sitting past its retention window is pure liability with no upside.

  • Quantum computing has already changed attacker behavior. Encrypted data is being harvested now for decryption later, which makes inventory and deletion discipline more urgent than ever.

"You cannot protect what you don't know that you have." - Dameon Sherman

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]]><![CDATA[Risk Isn't Static - Guardians of the Data - Veena Nagarajan - Episode #55]]>https://www.guardiansofthedata.show/p/risk-isnt-static-guardians-of-thehttps://www.guardiansofthedata.show/p/risk-isnt-static-guardians-of-theThu, 13 Aug 2026 14:02:42 GMTFor most teams, the answer is a scramble, not a process. In this episode, Ward sits down with Veena Nagarajan, interim CISO of a healthcare organization with 15 years in cybersecurity, to unpack why data protection has become as much about disciplined process as it is about technology. Veena walks through how she screens new solutions before they ever touch the environment, why a lean ten question risk assessment beats a bloated 100 question form nobody finishes, and how ongoing reassessment, not a one time checkbox, is what actually keeps organizations safe. She also opens up about her journey from India to becoming a healthcare CISO, and the mentors who shaped the way she leads.

Takeaways:

  • Start every new solution with a short, focused risk questionnaire. Ten well chosen questions about hosting, data elements, and exposure will tell you more than fifty scattered ones ever could.

  • Know your regulatory baseline before you assess risk. Whether it’s HIPAA, PCI, or SOX, identifying which frameworks apply first helps you pinpoint your organization’s true crown jewels.

  • Risk assessment isn’t a one time event. Reassess after a vendor moves from proof of concept to production, since environments and exposure change fast.

  • Defense in depth still wins. Layer email security, EDR, DLP, and network detection together, because the human clicking a bad link remains the most common entry point.

  • Don’t let perfect automation be the enemy of consistency. A well maintained spreadsheet process beats a fancy automated one that nobody checks. What matters most is doing it regularly.

"It doesn't matter if it's manual or automatic. What matters is keeping it regular and consistent. That is the key." - Veena Nagarajan

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]]><![CDATA[Denial of Wallet - Robert Whetstine - Guardians of the Data - Episode # 54]]>https://www.guardiansofthedata.show/p/denial-of-wallet-robert-whetstinehttps://www.guardiansofthedata.show/p/denial-of-wallet-robert-whetstineThu, 06 Aug 2026 14:00:57 GMTAccording to this week’s guest, it starts making its own decisions, and not always the ones you’d want.

Robert Whetstine, known across the industry as the Bow Tie Security Guy, joins Ward Balcerzak to unpack the wave of risk headed toward every organization running AI in production. From a looming explosion in CVEs to a brand new attack called denial of wallet, Robert makes the case that AI isn’t replacing the fundamentals of security, it’s making them non-negotiable.

The conversation moves from technical war stories to Robert’s own path from homelessness to Fortune 500 executive, tying together a career built on embracing discomfort and doing the basics better than anyone else.

Takeaways:

  • Shift from a vulnerability management mindset to an exposure risk model. Know your crown jewels, monitor them closely, and be able to answer in minutes whether a new CVE actually touches your environment.

  • Don’t let AI agents get bored. Chatbots without real guardrails will drift outside their instructions the longer a conversation runs, so build in controls rather than trusting the model to police itself.

  • Budget for token costs the way you’d budget for cloud sprawl. A reckless query or a denial of wallet attack can rack up tens of thousands in charges, so plan for a multiplier, not a flat rate.

  • Treat an unrestricted AI model like a brilliant but unsupervised junior engineer. Lock down RBAC, log everything through a third party, and never take an AI’s own explanation of its behavior at face value.

  • Protect your team from hustle culture before it protects your company from anything else. Burnout erodes judgment fast, and the basics, like tabletop exercises and clear data retention policies, only get done by people who aren’t running on empty.

“If you're not actively preparing for your token cost to have a five X multiplier in the next five years, you're going to be drastically surprised.” - Robert Whetstine

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]]><![CDATA[The Host Gets Hosted - Ward Balcerzak - Guardians of the Data - Episode # 53]]>https://www.guardiansofthedata.show/p/the-host-gets-hosted-ward-balcerzakhttps://www.guardiansofthedata.show/p/the-host-gets-hosted-ward-balcerzakThu, 30 Jul 2026 14:01:26 GMTFor Guardians of the Data's one year anniversary, Kraig Faulkner, Field CTO at InfoLock, flips the script and puts host Ward Balcerzak in the hot seat. Ward finally answers the question he has asked every guest all year: what is the biggest challenge organizations face in data security? His answer is blunt. From people, process, and technology to agentic AI oversight and a bold prediction about the future of SOC analyst roles, Ward pulls back the curtain on twenty years building data security programs at organizations like Allstate and Fidelity National Financial.

Takeaways:

  • Prioritize, strategize, and focus. Most organizations skip straight to buying a tool without appointing a leader or dedicating real resources, and that shortcut is why data security programs stall before they start.

  • People and processes come before technology. Ward ranks people first, processes a close second, and technology last, since governance and documentation often matter more than the tool doing the work.

  • Data security is bigger than DLP. Encryption, tokenization, activity monitoring, and data cataloging all belong under the same strategic umbrella instead of sitting scattered across disconnected teams.

  • AI did not create new risk, it exposed the risk that was already there. Years of neglecting data at rest and access hygiene are now surfacing the moment a copilot lets employees search everything at once.

  • Treat agentic AI like any other technology rollout. Give it a full architectural and security review, build in a UAT stage, and do not let it skip the same tollgates every other system has to pass through.

“AI didn't introduce new risks. It exposed the risk that we swept under the rug or neglected for years.” - Ward Balcerzak

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]]><![CDATA[Compiled for Your Protection - Guardians of the Data - Episode # 52]]>https://www.guardiansofthedata.show/p/compiled-for-your-protection-guardianshttps://www.guardiansofthedata.show/p/compiled-for-your-protection-guardiansThu, 23 Jul 2026 14:02:56 GMTIn this special compilation episode, Ward Balcerzak brings together some of the sharpest voices from across Guardians of the Data, including Tobias Simpson, Hans Vargas, Trevor Dolan, Matthew Gonzales, Joshua Copeland, Luis Valenzuela, Ketan Gotmare, Kevin Feck, and Dr. Sergio, for a rapid fire tour through the ideas that defined the show this season. From the real risk of misclassifying data to the business case every CISO needs to make in the boardroom, this episode strings together the moments that stuck with listeners most, plus a sobering look at how far social engineering has come with deepfakes, and lookalike domains.

Takeaways:

  • Misclassifying data is a bigger risk than leaving it unclassified. Several guests point to department level tabletop exercises as the fastest way to find each team’s actual crown jewels before rolling out a blanket policy.

  • Treat data classification like a partnership, not an audit. Approach owners with empathy and make it clear you’re there to help them find what matters, not to punish them for how they’ve stored it.

  • A real governance program rests on five pillars: leadership buy-in, an honest maturity assessment, clear policy frameworks, ongoing training, and the right team structure. Fix the most urgent pain points first, then document the rest as a roadmap so the gaps are defensible later.

  • Boards don’t respond to cyber risk, they respond to business risk. Translate technical exposure into dollars, downtime, and operational impact, or the conversation stalls before it starts.

  • Security leaders are caught in a velocity versus control paradox, expected to move as fast as the business while still verifying everything. At the same time, social engineering has caught up with AI, from cloned voices to deepfaked video, making code words and manual verification more essential than ever.

"Unless you can talk business risk, not cyber risk, and you can talk real dollars and cents to the business, you're gonna fail every single time." – Joshua Copeland

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]]><![CDATA[Stop Chasing Shiny Objects - Dana Kilcrease - Guardians of the Data - Episode #51]]>https://www.guardiansofthedata.show/p/stop-chasing-shiny-objects-dana-kilcreasehttps://www.guardiansofthedata.show/p/stop-chasing-shiny-objects-dana-kilcreaseThu, 16 Jul 2026 14:02:02 GMTIn this episode, Ward Balcerzak sits down with Dana Kilcrease, a nearly two decade cybersecurity veteran and current CISO in higher education, to talk about what actually matters when the pace of technology outstrips the pace of resources. Dana makes the case that velocity, not any single threat, is the real challenge facing security leaders today, and that the answer isn't chasing every shiny new tool. It's nailing the fundamentals, building DSPM and DLP into the foundation, and treating AI governance as a partnership rather than a lockdown. Along the way, he shares how a 95 year old institution turned AI anxiety into stronger cross-functional relationships, and offers some blunt career advice for anyone trying to break into cyber.

Takeaways:

  • Resources aren’t scaling at the same rate as technology or attackers, so leaders have to get comfortable doing more with what they already have.

  • Don’t chase every shiny new tool. Go back to first principles, harden your endpoints, lock down your processes, and build a real incident response plan so the blast radius stays small when something does happen.

  • Start data security with visibility. A DSPM foundation paired with DLP tells you where sensitive data lives, where it’s overshared, and where policies need to close the gap.

  • Treat AI governance as a partnership, not a policing effort. Sitting down with academic and administrative leaders to hear their concerns first turned a contentious relationship into a collaborative one.

  • Certifications don’t replace experience. Get clear on the niche you actually want, whether that’s pentesting or research or something else, and build toward that instead of stacking badges for their own sake.

"Experience trumps everything. If you have the option of taking a certification or getting into the trenches and really learning what this means, get into the trenches by all means and go nuts."- Dana Kilcrease

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]]><![CDATA[Data Never Sleeps - Andy Soodek - Guardians of the Data - Episode # 50]]>https://www.guardiansofthedata.show/p/data-never-sleeps-andy-soodek-guardianshttps://www.guardiansofthedata.show/p/data-never-sleeps-andy-soodek-guardiansThu, 09 Jul 2026 14:03:44 GMTOn this episode of Guardians of the Data, host Ward Balcerzak sits down with Andy Soodek, a privacy strategist and data governance expert with over three decades in the industry, to make a case that reframes the whole conversation: data protection was never a project with an end date. Andy breaks down why consent, data sprawl, and now AI are pulling organizations into a governance cycle that never actually closes, and why the companies still treating it like a checklist are the ones falling furthest behind.

Takeaways:

  • Treat data governance as a continuous loop, not a project you complete and shelve. New data, new tools, and new regulations mean the work never truly ends, so build a governance model that evolves alongside your business instead of expecting a finish line.

  • Get intentional about consent and transparency before you collect data, not after. Once that data gets shared with third parties or reused for new purposes, unclear consent turns into unclear liability down the road.

  • Simplify your data classification scheme rather than over-engineering it. Too many tiers create inconsistent access controls and confuse the people who actually need to use the data, so aim for a system that is easy to train on internally and easy to explain to an auditor.

  • Audit your data retention practices honestly. Most organizations are holding far more data than their own policies allow, and old data sitting around past its useful life adds legal exposure with little upside.

  • Build AI governance into your existing risk framework instead of treating it as a separate initiative. As regulations like California’s ADMT rules expand, organizations need real explainability and human review built into automated decisions.

"It's a never-ending governance cycle. You've got to keep up with what you've got going on now, because the next challenge is already on its way." - Andy Soodek

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]]><![CDATA[Emerging Threats in Data Protection - Anand Thangaraju - Guardians of the Data - Episode # 49]]>https://www.guardiansofthedata.show/p/emerging-threats-in-data-protectionhttps://www.guardiansofthedata.show/p/emerging-threats-in-data-protectionThu, 02 Jul 2026 14:00:14 GMTIn this episode, Ward talks to Anand where he explains why proprietary data has become every organization's most valuable asset and why traditional security approaches are struggling to keep pace. From data lineage and insider risk to agentic remediation and AI driven security operations, he lays out a future where context matters more than tools and where security teams need to understand not just where data lives, but why it moves and who is moving it.

Takeaways:

  • Your crown jewels are your proprietary data. In an AI driven world where public information is being commoditized by the minute, the only thing that gives your organization a true competitive edge is what it knows that no one else does. If you do not have a strong grip on that proprietary data, you do not have a fighting chance.

  • Stop waiting for the perfect moment to turn on visibility. One of the most common traps CISOs fall into is holding off on DSPM adoption until every compensating control is already in place. Start building now, because the longer you wait for perfection, the more your data sprawl grows into something that is genuinely unmanageable.

  • Treat data security as a program, not a product. No single tool is going to solve your data security problem. The organizations making real progress are the ones pairing the right technology with the right people, clear policies, and a genuine understanding of what bad actors would actually want from their environment.

  • Build your insider risk and data security programs together. These two disciplines share the same foundation: knowing where your sensitive data lives, who is touching it, and whether that behavior is normal. Tackle them in silos and you are leaving the most important use cases on the table.

  • Before you automate remediation, earn the right to do it. A crawl, walk, run approach is not timidity, it is strategy. Start with alert only mode, study your false positive rate, and give your model time to learn the nuances of your business before you hand it the keys to take action.

"The model should be almost like a trained security architect or security engineer. It should be able to reason for every single action it's taking." - Anand Thangaraju

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]]><![CDATA[Where Is Your Grandmother's Data? - David Smith - Guardians of the Data - Episode #48]]>https://www.guardiansofthedata.show/p/where-is-your-grandmothers-data-davidhttps://www.guardiansofthedata.show/p/where-is-your-grandmothers-data-davidThu, 25 Jun 2026 14:02:46 GMTIn this episode, David Smith, a cybersecurity leader with 30 years of experience across financial services, biopharma, consulting, and the vendor space, reframes the entire data governance conversation around one deceptively simple idea: custodianship.

David argues that AI did not create the data governance crisis. Organizations handed it 30 years of ungoverned data and said go. What AI did was pull the covers off a problem that has been quietly compounding through every layer of abstraction since the mainframe days

Takeaways:

  • Every new layer of data technology, from data warehouses to cloud to AI, breaks the original rules attached to data. The further data gets from its source, the harder it is to enforce how it should be used or protected.

  • Good data governance isn’t about corporate policies and DLP rules. It’s about custodianship, treating every data set the way you’d treat something precious that belongs to someone you love, and being intentional about who can access it, how it’s stored, and what happens if something goes wrong.

  • AI doesn’t create data governance problems, it inherits them. When organizations feed decades of ungoverned data into AI systems, they’re handing enormous power to a tool that has no way to respect rules that were never properly defined in the first place.

  • Data classification fails most organizations not because the concept is wrong, but because schemas focus too much on what the data is and not enough on what people are allowed to do with it. Traffic Light Protocol is a better model because it defines behavior, not just sensitivity level.

  • Starting a cybersecurity career at the help desk builds skills no technical training can replicate. Learning to solve problems under pressure with frustrated users and outdated systems directly prepares you for the real-world constraints of enterprise security work.

"AI inherited rather than creating the data governance problem. Organizations handed it 30 years of ungoverned data and said go." - David Smith

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]]><![CDATA[Governance Never Ends - Zach Lewis - Guardians of the Data - Episode # 47]]>https://www.guardiansofthedata.show/p/governance-never-ends-zach-lewishttps://www.guardiansofthedata.show/p/governance-never-ends-zach-lewisThu, 18 Jun 2026 14:01:12 GMTThat was the reality Zach Lewis faced, and it became the catalyst for one of the most thorough data governance journeys you will hear on this show. In this episode, Ward sits down with Zach Lewis, CIO and CISO in the healthcare and higher education space, author of “Locked Up,” and a 15 year veteran of the industry. Zach breaks down how a ransomware incident forced a complete reckoning with data classification, what a real multi year DSPM journey actually looks like from the inside, and why normalizing open conversation about cyber attacks might be the most important thing the security community can do right now.

Takeaways:

  • Don’t let a good crisis go to waste. A ransomware event, while devastating, can unlock budget, leadership attention, and organizational urgency that would have taken years to build otherwise. The smartest move after an incident is to channel that momentum into the data governance work you already knew needed to happen.

  • Data classification is not a policy problem, it is an execution problem. Having a policy on paper means nothing if the data isn’t actually tagged, governed, and tied to access controls. The real work starts when you move from defining classifications to enforcing them at scale, and that is where tooling and AI become non negotiable.

  • Data governance is a forever journey, not a project. Even after years of work, Zach’s team is still tackling retention, deduplication, and classification accuracy. The goal is not perfection on day one but consistent progress, eating the elephant one bite at a time.

  • Legal is your secret weapon. General counsel carries a kind of organizational gravity that IT rarely does. When you can align data hygiene and retention efforts with legal risk, people listen and things actually get deleted.

  • AI is shifting the math on what is even possible. Tasks that would have required a team of analysts reviewing files around the clock can now be handled automatically and accurately. Leaders who lean into AI for data security today are building the foundation that makes everything else, from Copilot adoption to regulatory compliance, far less terrifying tomorrow.

"A data governance journey never ends. It's a forever journey. Much like zero trust, the heavy lifting gets done and then it's about setting the right processes in place." - Zach Lewis

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]]><![CDATA[Securing the Future - Jason Torres - Guardians of the Data - Episode # 46]]>https://www.guardiansofthedata.show/p/securing-the-future-jason-torreshttps://www.guardiansofthedata.show/p/securing-the-future-jason-torresThu, 11 Jun 2026 14:02:18 GMTIn this episode, Jason Torres draws on over 20 years of experience in healthcare cybersecurity to make the case that data security still comes down to two fundamentals that most organizations haven’t cracked, knowing where your data lives, and knowing who is attached to it.

Jason breaks down why regulated industries like healthcare face a uniquely relentless challenge where data creation never stops, clinical staff have little patience for security friction, and the stakes of getting it wrong are measured in patient trust and breach costs. He also shares why AI governance committees are the non negotiable first step before any organization touches AI tools.

Takeaways:

  • Start with the basics, know where your data lives. Before any tooling, framework, or governance program can take hold, organizations need to first identify, locate, and classify their data. It sounds simple, but most companies still can’t confidently answer that question, and everything else depends on it.

  • Access and ownership are two different problems. Knowing who should have access to data is not the same as knowing who does. Closing that gap requires ongoing partnership between security teams and business stakeholders, not just a one time audit.

  • AI governance must come before AI adoption. Throwing AI tools at the business without establishing governance frameworks, leadership buyin, and usage policies is, in Jason’s words, “the Wild Wild West.” Forming an AI governance committee to define expectations and outcomes is the essential first step.

  • The business case for security tools has fundamentally changed. Where organizations once needed dedicated headcount to implement and run new solutions, AI-driven automation is shifting that model, enabling teams to repurpose existing talent rather than request new hires, and to justify investments with clearer, metrics backed ROI.

  • Diverse backgrounds build stronger security teams. Some of the most effective security professionals didn’t come up through traditional IT paths. Bringing in people with backgrounds in finance, communications, or even ministry, as Jason did, creates the range of perspectives and communication styles that make security teams more resilient and well rounded.

“Every journey begins with the first step. There's no blueprint for becoming a security leader. It all depends on the time you put in, the knowledge you develop, the action you put forth — and ultimately the relationships you build along the way." - Jason Torres

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]]><![CDATA[Where Are Your Crown Jewels? - Tony Schimizzi - Guardians of the Data - Episode #45]]>https://www.guardiansofthedata.show/p/where-are-your-crown-jewels-tonyhttps://www.guardiansofthedata.show/p/where-are-your-crown-jewels-tonyThu, 04 Jun 2026 14:02:06 GMTIn this episode, Tony Schimizzi draws on years of consulting experience to make a point that cuts to the core of modern data security: this is no longer just a cybersecurity problem. It has become a large-scale business operations and governance challenge.

Tony breaks down why data sprawl across SaaS products, cloud apps, and collaboration tools has made it nearly impossible for most companies to know where their data is, let alone where the crown jewels are and how well they are protected.

Takeaways:

  • Do the Fundamentals First: Asset management, visibility, access control, data classification. These have not changed, and they will not. Most breaches happen because the basics were not in place.

  • Security Is a Double Negative: IT can point to uptime as value. Security cannot point to revenue. Understanding that dynamic and learning to communicate in KPIs and measurable outcomes is how security teams earn their seat at the table.

  • Say Yes, And: The most effective security professionals are not the ones saying no. They find the compensating control that lets the business move forward safely. Never no, but. Always yes, and.

  • Build a Risk Council: Instead of having security engineers fight business decisions above their pay grade, bring the right leaders together: CISO, IT, HR, marketing, legal. Let them hash it out. Decisions made there carry weight decisions made at the engineer level never will.

  • If It Matters, It Should Be Measurable: KPIs taken to the board quarterly, along with examples of incidents that did not escalate because controls were in place, are how security teams demonstrate value without a direct revenue line.

  • Understand How the Business Makes Money: Before you can evaluate risk, you need to know what the business actually runs on. If your initiative would slow down the revenue engine, you need to know that going in.

Take Risks When You Are Young: Professionally and personally, the window to experiment, grind, and separate yourself is in your 20s. It is easier to course correct early than to try to change direction later.

"Companies no longer fully understand or control identity, access, and the data movement across their environments." Tony Schimizzi

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]]><![CDATA[Classify First, Secure Everything Else - Cory Zaner - Guardians of the Data ]]>https://www.guardiansofthedata.show/p/classify-first-secure-everythinghttps://www.guardiansofthedata.show/p/classify-first-secure-everythingThu, 28 May 2026 14:02:55 GMTToday’s guest, Cory Zaner, Senior Enterprise Architect for critical infrastructure and trusted advisor to executive leaders, joins Ward to discuss why organizations continue to struggle with data security fundamentals, and what it actually takes to fix them.

With over 20 years of experience across energy, manufacturing, and defense industries, Cory draws on his military background, time at Raytheon, and hands-on work in OT/ICS environments to break down the data security challenges most organizations are still getting wrong.

Takeaways:

  • Start with Data Classification, Not Tools: Before reaching for the latest shiny object, organizations need to define their data tiers. Cory recommends aligning to an established framework like NIST, then mapping your tiers to a simple color-coded system,red, yellow, green, so users can actually act on it.

  • Keep It Simple: Over-complicated classification schemes with 10–20 tags and sub-tags are a recipe for failure. If your users need a secret decoder ring to understand how to classify data, the program has already failed.

  • The Data Owner Classifies the Data: Not IT. Not the tool. The person who knows what the data is worth is the one who should be tagging it. Technology can assist, but it can’t make that judgment call for you.

  • Align to a Framework, Then Scope It: Whether it’s NIST, ISO, or another standard, anchoring your program to an established framework takes the argument off the security team’s plate. You’re not asking people to trust your ideas; you’re pointing to an industry consensus.

  • Start with Unstructured Data First: Cory recommends beginning with your M365 or G Suite environment, where user-generated content lives, before tackling structured data like SQL databases. That’s where the real user behavior risk is.

  • Build the Right Committee: Data classification can’t live in a security silo. Legal, privacy, and HR are essential early partners. Build a governance committee with real ownership, not just initial enthusiasm that fades after the first few meetings.

"Garbage in, garbage out. AI can make things prettier, but we cannot change the mindset of people with technology.” - Cory Zaner

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]]><![CDATA[Navigating the Data Maze - Brian Cherry - Guardians of the Data - Episode # 43]]>https://www.guardiansofthedata.show/p/navigating-the-data-maze-brian-cherryhttps://www.guardiansofthedata.show/p/navigating-the-data-maze-brian-cherryThu, 21 May 2026 14:01:43 GMTThese three questions sit at the heart of every data security challenge and according to Brian Cherry, most organizations still can’t answer them.

In this episode, Brian, a Global Director of Information Security with over 20 years in cybersecurity, joins Ward to dig into the sprawling reality of data security: why data never stays where you think it does, how shadow IT and bad governance quietly create massive exposure, and why AI is raising the stakes on all of it.

Brian also shares how curiosity, mentorship, and asking the right questions shaped his entire career and why those same instincts are the most powerful tools any security professional can have.

Takeaways:

  • Know your data before you protect it. You can’t secure what you can’t find. Start by asking four foundational questions: What data needs protection? Where does it live? Have you truly looked everywhere? And who has access and how did they get it? These questions sound simple, but most organizations haven’t fully answered any of them.

  • Act like an investigative journalist when talking to the business. Going into stakeholder conversations without pretending to have all the answers actually gets you further. When people feel like they’re teaching you, they open up and that’s when you learn where the real data risks are hiding.

  • Governance isn’t sexy, but it’s where the real power is. Red team exercises find problems, but governance is what actually prevents them. Policies, controls, and proper data classification programs are what keep businesses from accidentally creating their own worst security incidents.

  • AI is amplifying your existing data problems, not creating new ones. If sensitive data is scattered in shared directories, staging environments, or forgotten backups, any AI tool with access to it becomes a liability. Getting AI-ready means solving the fundamentals first classification, access control, and visibility.

  • Find a mentor, and be one. A mentor who pushes you to understand the business side of security, not just the technical side, can completely change your trajectory. And when you’ve made it, look back. The best investment you can make in the profession is helping someone else ask the next question.

"If you don't ask questions, you're never going to know the answer. That's where my career started, and it's still the most powerful tool I have." - Brian Cherry

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]]><![CDATA[Fighting AI Risk with AI - Kevin Feck - Guardians of the Data - Ep #42]]>https://www.guardiansofthedata.show/p/fighting-ai-risk-with-ai-kevin-feckhttps://www.guardiansofthedata.show/p/fighting-ai-risk-with-ai-kevin-feckThu, 14 May 2026 14:04:00 GMTToday’s guest, Kevin Feck, Director of Data Protection and Security Architect, joins Ward to unpack how AI is reshaping the data security landscape.

With over two decades in cybersecurity, Kevin shares why the industry’s long-standing challenges of data classification, access control, and visibility have suddenly become urgent in the age of AI. From the risks of copilots and LLMs to the reality of “AI readiness,” this conversation dives into what organizations are getting wrong and how to fix it.

Kevin also breaks down why trying to “boil the ocean” with data security initiatives often fails, how to scope efforts effectively, and why security teams must evolve from perceived roadblocks to true business enablers.

Takeaways:

  • Classify Your Data Before Connecting AI to It: AI tools like Copilot can instantly surface sensitive data that used to take weeks to find manually. Granular, contextual data classification is the foundation.

  • Correlate Sensitive Data With Permissions: Knowing where your sensitive data lives isn’t enough. Lock it down to authorized users so AI agents can only access what they should.

  • Fight AI with AI: Regex based DLP tools are no longer sufficient. Invest in AI powered data security that can understand context, not just patterns.

  • Build an AI Governance Program: Get lawyers, procurement, security, and technical staff aligned on what “AI” actually means in each vendor contract. Not all “AI” is equal.

  • Treat User Education as a Core Security Control: No tool is 100% effective without trained users. Ongoing security awareness training is essential to make data classification stick culturally.

  • Prioritize “Better Together” over a single pane of glass fantasy: No one tool covers every environment perfectly. Integrated tooling with shared intelligence is more effective than waiting for a perfect unified solution.

  • Hire For Passion, Not Just Credentials: In a field evolving daily, someone deeply motivated to do the right thing will outperform a technically skilled person who is just checking boxes.

“It’s always been about the data. Tell me what that data is and I’ll tell you how much I have to care about it.” - Kevin Feck

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]]><![CDATA[AI Governance: Navigating the Speed of Change - Sweeney Williams - Guardians of the Data - Ep #41]]>https://www.guardiansofthedata.show/p/ai-governance-navigating-the-speedhttps://www.guardiansofthedata.show/p/ai-governance-navigating-the-speedThu, 07 May 2026 14:02:17 GMTIn this episode of Guardians of the Data, Ward sits down with Sweeney Williams, Head of Responsible AI, to unpack the biggest challenge facing data security today … speed.

With over 20 years of experience spanning cybersecurity, privacy, and AI governance, Sweeney shares how the rapid acceleration of AI is reshaping everything from geopolitical competition to regulatory approaches and security threats. What once felt like a manageable evolution now demands constant adaptation, forcing organizations to rethink how they govern, secure, and deploy AI in real time.

The conversation explores why traditional approaches to regulation and risk management are struggling to keep up, how bad actors are leveraging AI to scale attacks, and why organizations can’t afford to wait for clarity before taking action. Sweeney also outlines practical steps for building a strong AI governance foundation, emphasizing the importance of fundamentals like data governance, transparency, and cross functional collaboration.

Takeaways:

  • Speed is the Defining Challenge of AI. AI isn’t just evolving quickly. It’s forcing rapid change across regulation, geopolitics, and security. Organizations are struggling to keep pace with constant shifts in capabilities and expectations.

  • Regulation is Lagging and May Stay That Way. Global attitudes toward AI regulation have shifted dramatically, with many regions prioritizing innovation and competitiveness over strict governance.

  • AI is Amplifying Security Risks. Bad actors are using AI to launch more sophisticated and scalable attacks, lowering the barrier to entry and increasing the pressure on security teams.

  • Fundamentals Still Matter! Strong data governance, transparency, access controls, and bias mitigation remain essential, even as the technology evolves.

  • You Can’t Wait for Clarity! Organizations that delay action until regulations stabilize risk falling behind. The best time to build AI governance is now.

  • Third party AI Risk is a Growing Blind Spot. Vendors are rapidly embedding AI into their products, often without clear visibility, making third party risk management more complex than ever.

“The best time to plant your AI governance tree… is right now.” - Sweeney Williams

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