The market is converging.

Networking, security, and cloud operations are no longer separate conversations. They are colliding at the operational layer, driven by hybrid environments, AI driven operations, and growing pressure to reduce complexity without losing control.

In this episode of ClearTech Loop Market Perspective, Jo Peterson sits down with Dan DeBacker, Chief Product Officer at Extreme Networks, to explore what this convergence looks like in practice and why simplicity, unified policy, and cloud design are increasingly inseparable decisions.

Dan shares how enterprises are grappling with operational friction created by multiple control planes and fragmented policy engines, and why the market is responding by collapsing domains into platforms. The conversation examines convergence not as a trend, but as a response to real operational pressure.

Through the lens of AI Enhanced Cloud Operations, the discussion focuses on how AI is tightening feedback loops, exposing hidden complexity, and forcing organizations to rethink how visibility, policy, and control operate across cloud and on premises environments.

If you’re navigating hybrid operations, policy sprawl, or the growing pressure to simplify without sacrificing sovereignty, this episode brings clarity to where the market is headed.

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Key Quotes

“If you have to integrate and manage multiple UI experiences, multiple policies, multiple ways of doing things… that’s complexity. Our goal is to reduce friction by bringing those together.”
— Dan DeBacker

“When you talk about NAC policy, VPN policy, Zero Trust policy ideally they should not live in silos. The next evolution is a unified policy engine.”
— Dan DeBacker

“AI doesn’t tolerate fragmentation. The more intelligence we embed into operations, the more exposed complexity becomes.”
— Jo Peterson

Three Big Ideas from This Episode

1. Convergence is an operational reality, not a future state

The collision of networking, security, and cloud operations is happening because fragmented environments cannot keep up with AI driven decision cycles.

2. Policy is becoming shared operational infrastructure

Unified policy models are emerging as the connective tissue across access, security, and network operations, replacing siloed controls that slow response and increase risk.

3. Cloud and on premises now function as a continuum

Organizations are designing for flexibility and sovereignty by treating cloud as an experience rather than a location, applying consistent control across environments.

Episode Notes

🎧 Listen in player
▶ Watch on YouTube: https://youtu.be/75DciQR03DY
📰 Subscribe to the ClearTech Loop Newsletter:
https://www.linkedin.com/newsletters/7346174860760416256/

Resources Mentioned

Extreme Platform ONE Security: Accelerating Zero Trust and Simplifying Operations for Network Leaders
https://www.extremenetworks.com/resources/blogs/extreme-platform-one-security-accelerating-zero-trust-and-simplifying-operations-for-network-leaders

Gartner: AI Enabling Cloud Services Are the Future of Cloud

Security teams have spent years operating in reaction mode. Alerts fire, analysts scramble, and incident response often moves at human speed while adversaries move faster.

In this episode of ClearTech Loop, Jo Peterson sits down with Evan Kirstel to talk about how generative AI is changing that reality. Evan shares practical examples of how AI powered triage is shrinking incident response timelines from hours to minutes and why speed, when paired with better analysis and guidance, can fundamentally change outcomes.

The conversation goes beyond faster detection and digs into what this shift really means for security teams and CISOs:

AI is enabling analysts to move from reacting after the fact to predicting threats as they emerge.

Entry level SOC teams are being up leveled with remediation paths and decision support, not just alerts.

Security and privacy controls can be embedded into AI development early without slowing innovation, and in many cases, actually accelerating it.

And CISOs are being pushed into a broader governance role as AI becomes both a critical capability and a growing threat surface.

If you’re trying to understand how AI is reshaping security operations today and what leaders need to be thinking about next, this episode brings clarity to the conversation.

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Key Quotes

“They can cut incident response times from hours to minutes. Just like an emergency room, minutes matter.” — Evan Kirstel

“I think this gives us a chance to really up level our more entry level SOC folks, and it gives them remediation paths. It doesn’t just find things, it gives solutions to the problem.” — Jo Peterson

Three Big Ideas from This Episode

1. AI powered triage changes the math of incident response

AI is compressing detection, analysis, and decision cycles. When response moves from hours to minutes, outcomes change and teams gain back control during critical moments.

2. Proactive security starts with better guidance, not just faster alerts

AI is helping teams predict and prepare, not just react. By offering remediation paths and context, it allows SOC analysts to make smarter decisions under pressure.

3. Governance becomes a core CISO responsibility in an AI driven world

As AI adoption accelerates, CISOs must balance speed with guardrails. Embedded security, privacy by design, and clear governance frameworks are now essential to maintaining trust and reducing risk.

Episode Notes / Links for Suzie to Fill Out

🎧 Listen: in the player above
▶ Watch on YouTube: https://youtu.be/BFkpNCOQfnw
📰 Subscribe to the ClearTech Loop Newsletter:
https://www.linkedin.com/newsletters/7346174860760416256/

Resources Mentioned

• NIST AI Risk Management Framework https://www.nist.gov/itl/ai-risk-management-framework
• The Evan Kirstel Show https://www.youtube.com/@EvanKirstel
• ClearTech Research Insights https://cleartechresearch.com

AI has erased the perimeter. Security teams are no longer guarding walls — they’re managing airspace.

In this episode of ClearTech Loop, Jo Peterson sits down with Deputy CISO Aby Rao to unpack what AI security really looks like when threats move through models, APIs, agents, and identity flows instead of firewalls and fences.

Aby explains why security teams are at an inflection point:

• No code and low code tools now let cyber teams build automation and identity workflows without relying on vendors.
• AI development is outpacing AI literacy, creating a widening gap between capability and understanding.
• And CISOs can no longer operate as castle guards — they must become bridges between high-velocity development and the governance functions responsible for responsible AI.

If you want to understand how CISOs should adapt to a boundaryless threat landscape — and what “air traffic control” for AI security actually means — this episode gives you the clarity you’re looking for.

👉 Subscribe to ClearTech Loop on LinkedIn:
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Key Quotes

“We have to break out of this castle guard mindset and think of us as air traffic controllers.” — Aby Rao

“The pace at which AI development is taking place, it has outgrown AI literacy and AI education.” — Aby Rao

“If you’re not actively involving your CISO, you really need to. You’re short-changing yourself.” — Jo Peterson

Three Big Ideas from This Episode

1. AI gives cyber teams new power — and new ownership.
With no code and low code tools, teams can now build custom workflows and agentic processes on their own data. That freedom comes with long-term responsibility.

2. Security by design only works if AI literacy exists first.
You can’t embed privacy, fairness, transparency, or explainability if the team doesn’t understand AI fundamentals.

3. CISOs must become the bridge.
They now sit between fast-moving developers and governance leaders in legal, audit, privacy, fairness, and ethics — translating risk and keeping the entire airspace safe.

Episode Notes / Links for Suzie to Fill Out

🎧 Listen: on player above
▶ Watch on YouTube: https://youtu.be/7OSuAiLZCgo
📰 Subscribe to the ClearTech Loop Newsletter:
https://www.linkedin.com/newsletters/7346174860760416256/

Resources Mentioned:

• NIST AI Risk Management Framework: https://www.nist.gov/itl/ai-risk-management-framework
• CSA Trusted AI Course Materials: https://cloudsecurityalliance.org/education
• “Pack a Room Full of Governors” https://www.linkedin.com/posts/abyrao_pack-a-room-full-of-governors-standing-activity-7401658932416528384-PFxH/
• Previous Episode: AI Safety with Dutch Schwartz: https://cleartechresearch.com/bumpers-not-brakes/

AI is not a fix for a broken SOC. It exposes weaknesses you already have. In this ClearTech Loop episode, Jo Peterson talks with Dr. Anton Chuvakin — Senior Security Staff in Google Cloud’s Office of the CISO and one of the most respected voices in SOC modernization — about what “AI readiness” really means and why most teams are nowhere near it.

You’ll hear about:

• Why AI accelerates process debt instead of compensating for it
• The two forms of shadow AI already inside every enterprise
• The five foundations of an AI ready SOC: data quality, ownership, interoperability, probabilistic thinking, and metrics
• Why governance has to move at the speed of experimentation, not quarterly reviews
• How to evaluate AI tools through use cases instead of marketing promises

Anton has spent decades shaping security operations — from coining the term EDR to defining detection and response strategies as a Gartner Distinguished Analyst. Today, he helps global enterprises build the structural maturity required before AI can add any value at all.

Subscribe to the ClearTech Loop Newsletter on LinkedIn:
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Episode Description (Short):

Jo Peterson and Dr. Anton Chuvakin break down what AI readiness really requires and why most SOCs are not prepared for what AI will expose.

Timestamps

00:00 Intro and Anton’s background
01:15 Why AI exposes foundational weaknesses
03:45 Process debt and SOC workflow failures
05:20 Two forms of shadow AI inside enterprises
07:10 Data quality, ownership, and workflows
09:22 Five foundations of an AI-ready SOC
11:18 Why interoperability matters
12:40 Leaders and probabilistic thinking
14:05 Governance at the speed of AI
17:10 How to evaluate AI tools
19:25 Closing thoughts

About the Guest

Dr. Anton Chuvakin is Senior Security Staff in the Office of the CISO at Google Cloud. Previously a Research Vice President and Distinguished Analyst at Gartner, he has authored multiple books on security monitoring and log management and co hosts the Cloud Security Podcast.

Resources

Anton’s YouTube playlist
https://www.youtube.com/watch?v=iX5SvgMpS0s&list=PLkdSRxA6DyHtxH623M1WYuAYGpEXdvEqp

Google Cloud security best practices
https://cloud.google.com/security/best-practices

CSA AI Safety Initiative
https://cloudsecurityalliance.org/ai-safety-initiative

ClearTech Loop: George Finney on the CSA AI Initiative
https://cleartechresearch.com/the-csa-ai-safety-initiative-with-george-finney/

A practical framework for AI ROI: visibility, accountability, and value

Episode description / show notes

Last week, you probably caught my chat with Ajay Patel, GM of Apptio and IBM IT Automation. If you missed it, this episode breaks down how a layer of financial intelligence turns AI from experiments into measurable business value.

We walk through a simple framework that leaders can actually run with. First, visibility across every AI initiative and its real costs, including people, data preparation, governance, and change management. Second, accountability that ties projects to business objectives, not activity. Third, value that tracks both hard returns and soft returns so the story holds up with finance and the board.

Adoption and trust matter just as much. AI programs don’t stall for lack of models. They stall when people can’t trust the data or see the wins. Start with accurate, contextual data and repeatable outcomes. Build confidence with useful insights that remove busywork. Then let automation follow.

Listen in for what CIOs and CFOs need to align on the same page and move faster with less risk.

What you’ll learn

1. How to inventory AI initiatives and total cost drivers
2. How to link projects to measurable outcomes that matter
3. How to measure hard and soft ROI without hand-waving
4. How to build trust so automation becomes a natural next step

Key quotes
“AI starts with the productivity tool. It starts providing me rich insight and making smarter decisions. It starts taking away some of that mundane work, and you kind of walk into building that trust… till you get to a point where the user says, ‘I trust it — can you automate that action for me?’”

“What if you could have a series of financial experts available at your fingertips? That’s what enterprise financial intelligence is all about — building those experts from your own data so every decision gets smarter.”

Links
LinkedIn clip of the conversation: [add link]
ClearTech Research episode page: [add link]
Apptio and IBM IT Automation: https://www.ibm.com/apptio
Apptio FinOps Framework: https://www.apptio.com/solutions/finops/
Subscribe to ClearTech Loop: https://form.typeform.com/to/EESYYt4a

About the guest
Ajay Patel is the General Manager of Apptio and IBM IT Automation, leading Apptio, Turbonomic, Instana, and AIOps across hybrid environments. His leadership spans VMware, Oracle, BEA Systems, and Apigee. He focuses on using financial and operational intelligence to optimize technology investments and outcomes.

Chapter markers

00:00 Intro and why financial intelligence matters
00:23 Guest welcome
01:47 From AI hype to ROI
02:53 Financial intelligence vision inside the enterprise
04:58 The framework: visibility, accountability, value
06:39 Adoption, governance, and responsible AI
07:29 Data quality, trust, and building confidence
10:35 Fourteen years of customer data and lessons learned
11:04 Benchmarking, unit economics, and practical guidance
12:43 Closing and conference note

Enterprises are not trying to modernize in a vacuum. They are running mission-critical workloads on mainframes and ERPs, while also deploying cloud apps, SaaS platforms, and mobile services at scale. Now leaders are expected to layer in AI without disrupting operations.

Hybrid integration is how they do it.

In this ClearTech Loop special edition sponsored by IBM webMethods, Jo Peterson breaks down real-world integration patterns and what IT leaders need to enable AI-ready operations across legacy, cloud, and SaaS environments.

Topics include:

• Modernizing legacy systems without disruption
• Wrapping core systems with APIs for real-time access
• Connecting cloud platforms and on-prem applications
• Managing event-driven automation and data unification
• Treating APIs as digital products with governance and scale
• Why a hybrid control plane matters for AI outcomes

Hybrid integration is not a temporary bridge. It is the operating model for the AI era.

Links & Resources

Learn more about webMethods Hybrid Integration: https://ibm.biz/Bde6n2
Start a free 30-day trial: https://ibm.biz/Bde6nf

Subscribe to the ClearTech Loop newsletter: https://www.linkedin.com/newsletters/7346174860760416256/
Watch this episode on YouTube: https://youtu.be/3_2ZTq-jdmM

Guest

Jo Peterson
Chief Analyst, ClearTech Research
VP of Cloud and Security Services, Clarify360

Sponsored by

IBM webMethods Hybrid Integration

Short Preview Copy
Hybrid integration is how enterprises modernize without disruption. Jo Peterson explains real-world use cases and why webMethods is becoming core to AI-ready architecture.

How do you enable AI inside one of the most highly regulated industries on the planet — without slowing the business or attracting regulatory heat?

In this episode, veteran financial-services CISO Parrish Gunnels joins Jo Peterson to break down the real playbook for operationalizing AI in banking environments.

This isn’t theory. It’s where risk appetite, regulation, and revenue meet reality.

We cover:

• Why “turn off AI” was a knee-jerk — and why it can’t last
• Moving from prohibition to auditable enablement
• How financial-services CISOs model AI-risk in dollars
• Why human-in-the-loop is still non-negotiable
• Designing paved roads that stop Shadow AI
• The 90-day maturity model for regulated AI adoption
• Culture, training, and trust as the real control surface

“There isn’t a great model for ROI in security… I think of it as downtime, reputational risk, lost revenue, and the cost of fines per record.” — Parrish Gunnels

If you’re in a regulated space — banking, healthcare, insurance, public sector — and trying to balance innovation with compliance, this one’s your blueprint.

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🔗 Connect with Parrish on LinkedIn
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See you in the Loop.

Episode Description:
In this episode of ClearTech Loop, Jo Peterson sits down with John Carse, Field CISO at SquareX and former CISO at Dyson and Rakuten, to talk about why modern CISOs must move beyond fear, uncertainty, and doubt — and start quantifying risk in business terms.

Carse explains how two levers — risk appetite and budget alignment — determine every security decision, and why the browser has become the new edge of enterprise risk. From AI prompt attacks to malicious extensions, Carse offers a practical blueprint for translating security posture into measurable business impact.

🎧 Listen to the full episode: ADD LINK
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Key Topics Covered:

• Why “talking dollars, not FUD” earns board trust
• The connection between risk appetite and budget allocation
• The browser as the modern enterprise perimeter
• How the Field CISO role bridges business and technology
• Practical ways CISOs can quantify risk and value

About the Guest:
John Carse is a three-time CISO and currently serves as Field CISO at SquareX, helping enterprises defend against browser-based threats and translate security strategy into business impact. His previous roles include CISO positions at Dyson and Rakuten and security leadership at Expedia and JPMorgan Chase.

Additional Resources

• Security Magazine: John Carse hired as Field CISO at SquareX
• The CISO Perspective with John Carse Podcast
• The Browser Blind Spot: Rethinking Enterprise Security