The pressure to act on AI has reached the board level, but most enterprises are still scrambling to close the gap between shadow AI in the wild and a governed, sanctioned strategy. In this inaugural Inside Amplix episode, Shawn sits down with Amplix CEO Dan Gill for a candid read on what he's seeing across thousands of client engagements: where real IT cost savings are hiding, why modernization is the unsexy prerequisite to AI value, and what technology leaders keep getting wrong about the full project lifecycle. Dan also unpacks the shadow AI risks most leaders haven't thought through yet, how to talk to your board without becoming the roadblock, and why the pace of change is making outside advisory help less optional than ever.

What You'll Learn:

• Why the macroeconomic pressure on IT budgets is actually funding the next wave of modernization
• Where double-digit cost savings are hiding in telephony, network, mobility, and cloud spend
• Why AI pilots fail — and it's rarely the technology's fault
• How to think about shadow AI before it becomes your organization's next shadow IT problem
• What good AI governance actually looks like: data strategy, classification, and policy that people follow
• Why you should fix the process before you automate it — AI is a catalyst for business process improvement, not a shortcut around it
• How to talk to your board and C-suite about AI risk without being perceived as the innovation roadblock
• Why the pace of change is making outside advisory help less optional — and what to look for in a partner

The contact center is ground zero for agentic AI, and most enterprises have an infrastructure gap they haven't fully reckoned with yet. In this episode, Shawn sits down with Brandon Teegen, VP of Solutions at Cresta AI, to explore what happens when AI stops just answering questions and starts taking action on your customers' behalf. They dig into how to build an AI agent strategy before the volume tsunami hits, why the Klarna story is less about a bad decision and more about a missing playbook, what Cresta's "Agent Operating Center" model reveals about the future of human-in-the-loop supervision, and why agent-to-agent interactions will force enterprises to rethink authentication, brand governance, and margin models from the ground up. If you're a CIO or CTO with a contact center in your portfolio, this is the briefing you didn't know you were missing.

What You'll Learn:

• Why the shift from AI answering questions to AI taking actions is the CX infrastructure gap most enterprises aren't prepared for
• How to sequence your contact center automation strategy — internal use cases first, customer-facing second, and why the order matters
• What the Klarna story actually teaches us about AI deployment risk (and why "dip your toe in" beats "flip the switch")
• Why personal AI assistants like Siri and Claude are weeks away from driving 2-3x your current contact center volume — and what to do about it
• How Cresta's Agent Operating Center model redefines the supervisor role when AI agents are handling the floor
• Why agent-to-agent interactions will require entirely new authentication, discount thresholds, and brand governance policies
• How AI agents are becoming an extension of brand identity — and why marketing needs a seat at the contact center table
• What the CFO conversation about AI token costs needs to look like before spend outpaces the savings

Most financial institutions are approaching AI backwards — starting with the technology and working toward the use case, rather than the other way around. Karan Kashyap, CEO of Posh AI, has spent eight years helping banks and credit unions deploy conversational AI across both customer and employee channels. In this episode, he makes the case that the riskiest thing a CIO can do right now is nothing — and he gives technology leaders a practical framework for deciding what to build, what to buy, and how to design AI experiences that build trust rather than erode it.

What You'll Learn:

• Why financial institutions are still the slowest AI adopters — and why that conservatism is becoming a competitive risk against fintech
• How to design AI that builds customer trust rather than triggering skepticism — and why disclosure is both a regulatory requirement and the right call
• The difference between automating a task because you can vs. because you should — and how regulated industries like banking and healthcare should make that call
• Why voice AI is still in the uncanny valley and where the real low-hanging fruit is (hint: it's your search bar)
• How agentic AI and the rise of specialized "mini agents" is changing the way financial institutions think about customer and employee-facing deployments
• Karan's signature framework: build what differentiates, buy what accelerates — and why the in-house build is usually only 3% of the total effort
• Why the riskiest thing a CIO can do right now is nothing — and how to make the case for an evergreen innovation fund to your board
• How AI technical debt accumulates fast, and what institutions that tried to build in-house eventually discover

Attackers don't need a zero-day anymore. A stolen username and password, accelerated by AI, is cheaper, faster, and harder to detect. In this episode, Brian Zimmer, Field CISO at CyberMaxx, joins Shawn to break down why identity is the real perimeter, how managed detection and response has to evolve to match identity-based attacks, and what CISOs need to do right now to build governance programs that protect users without creating the friction that drives them to bad habits.

What You'll Learn:

• Why credential-based attacks are the attacker's preferred playbook and how AI has made them even cheaper to execute at scale
• How the shift to remote work collapsed the castle-and-moat model and put user identity at the center of every security decision
• What a strong identity governance program actually looks like, from joiners and movers to certificate management and privileged access
• Why authentication and authorization are not the same thing, and why conflating them is a governance gap CISOs need to close
• How to minimize friction for your users while maximizing cost and noise for attackers
• Why AI agents need identity governance just as urgently as the humans using them, and who in the org actually owns that problem
• How modern MDR has to evolve from isolating machines to responding at the identity layer
• The practical steps a CIO or CISO should take today to start treating identity as the new edge

Most enterprises are still shoehorning AI into structures built for a different era, the horseless carriage problem. In this episode, Shawn is joined by Cobus Greyling, AI Evangelist at Kore.ai, and Carl Katz, VP of Global Technology Partners, for the show's first-ever dual-guest conversation. Together, they cover why multi-agent orchestration is outpacing prompt engineering as the critical enterprise skill, how to govern a workforce of AI agents before sprawl sets in, what the shadow AI economy is costing organizations in attribution and compliance, and how technology leaders can make the business case for AI experimentation without a clean ROI to show for it. If you're trying to move urgently but thoughtfully on AI, this one is for you.

What You'll Learn:

• Why multi-agent orchestration is becoming the skill that matters more than prompt engineering and what that shift means for your team
• What "bounded autonomy" is and why setting the right autonomy level per use case is the difference between a useful AI agent and a liability
• How the shadow AI economy works against your attribution, compliance, and AI governance efforts
• Why 80–85% of enterprise AI pilots fail in-house and what the ones that succeed do differently
• The horseless carriage trap: why plugging AI into existing processes without reimagining them is a recipe for wasted investment
• How to frame the AI experimentation business case for your board and finance team when clean ROI isn't available yet
• What an agent control plane is and why you'll need one before your AI agent count gets out of hand
• How to think about the build vs. buy vs. partner decision as agentic AI moves from pilot to production

Unstructured data now makes up 85–90% of everything enterprises create, and most of it is sitting unmanaged on your network, quietly inflating costs, widening your attack surface, and undermining your AI initiatives. In this episode, Shawn sits down with Michael Smith, Director of OEM & Technology Alliances at Congruity360, to make the case for data minimization as the defining IT discipline of 2026. They cover why more data is not better for AI (the right data is), how orphaned and redundant data becomes a weapon for bad actors, what a crawl-walk-run approach to data hygiene actually looks like, and how to bring your CISO, CFO, and board along for the ride.

What You'll Learn:

• Why unstructured data has become your enterprise's #3 most valuable asset, and its biggest hidden liability
• What ROT data (Redundant, Obsolete, Trivial) is costing you in storage, backup, and cyber insurance premiums
• How orphaned and unmanaged data expands your attack surface and becomes an entry point for bad actors
• Why feeding AI models more data creates worse outcomes, and how to identify the "right" data instead
• A crawl-walk-run approach to data classification and minimization that doesn't require boiling the ocean
• How to navigate GDPR, CCPA, HIPAA, and NYDFS without getting paralyzed by compliance complexity
• How to frame the data minimization business case for your CISO, CFO, and board

Everyone is talking about AI, but far fewer organizations are actually scaling it. David Vidoni, CIO at Pega Systems, joins Shawn Cordner of Amplix to cut through the noise and get practical. 

The conversation covers where enterprise leaders should be focusing their automation efforts across finance, HR, and legal functions; how to approach the pilot-to-scale gap and what the widely cited MIT finding that 95% of AI pilots fail to produce ROI actually tells us; and why the phased, iterative approach to modernization consistently beats the high-risk big bang. David also shares how enterprises can build the governance and quality controls needed to trust AI at scale, what explainability and audit trails look like in regulated industries, how to vet AI vendors for supply chain risk, and why change management remains the variable that determines whether any of it sticks. 

If your organization is past the curiosity stage and ready to build something that lasts, this episode is the starting point.

What You'll Learn:

• Where AI automation is generating real ROI beyond the obvious entry points, including finance, HR, and legal functions
• How to structure a POC that is designed to scale from day one and avoid the pilot-to-scale trap
• Why phased modernization consistently outperforms big bang migrations and how to build the case internally
• What governance, audit trails, and quality controls need to look like before you trust AI to run autonomously
• How to manage AI model drift in regulated industries subject to SOX compliance and HIPAA requirements
• What ISO 42001 certification means and why it should factor into your vendor selection process
• How to evaluate supply chain risk when AI is embedded in the platforms your business depends on
• Why change management determines whether AI adoption succeeds or stalls regardless of the technology

AI is rewriting the rules of software development, but are your teams and processes ready to capture the value? Vertikal6 CTO Vin DiPippo joins host Shawn Cordner to cut through the hype, revisit the hard lessons of vibe coding, and lay out what it actually takes to turn AI tooling into measurable business outcomes. A must-listen for technology leaders navigating the gap between experimentation and execution.

What You'll Learn:

• Why vibe coding fell short — and how spec-driven development is changing the approach to AI-assisted coding
• What the data actually says about AI productivity gains, and why the real-world numbers often tell a different story
• How to integrate AI into DevOps and DevSecOps without sacrificing code quality or security
• Why AI in development is a lot like offshore outsourcing — and the lessons from that era tech leaders can't afford to ignore
• How to set realistic expectations with business stakeholders and measure ROI before and after AI adoption
• Practical advice for standardizing AI tools across your development team and building a culture of shared learning

What does AI actually change about customer experience, and what doesn’t? 

In this episode, Shawn Cordner sits down with Gary Sorrentino, Global CIO of Zoom, to explore how one of the world’s most recognizable collaboration platforms thinks about AI, customer experience, and the future of work.

Gary shares how CX, employee experience (EX), and digital experience (DX) are converging into a single, continuous experience, and why organizations need to design from business outcomes backwards, not from tools forward. They discuss how AI should eliminate friction and busywork, where human judgment still matters most, and what enterprises must get right around governance, trust, and change management as agentic AI and digital assistants move into production.

If you’re responsible for IT, CX, or digital transformation, this conversation offers a practical, executive-level view of what it takes to scale AI in a way that drives real value.

What You’ll Learn

• How Zoom approaches AI in customer and employee experience
• Why CX, EX, and DX are now inseparable
• What agentic AI means for moving from answers to action
• How to design journeys starting with outcomes, not features
• Why does human change management determine success or failure
• How leaders should think about AI governance, trust, and ROI

In this episode of The Amplitude of Tech, Shawn Cordner talks with Joe DeLuca, Senior Director of Voice, Contact Center, and Collaboration at Wyndham Hotels & Resorts, about what it really takes to apply AI in customer experience without sacrificing trust, quality, or brand. 

Joe shares how large enterprises are balancing cost pressure, rising customer expectations, and rapid advances in AI, and where technology leaders should focus first to see real impact. The conversation goes beyond hospitality to explore universal challenges around automation, personalization, data readiness, and governance that apply to any organization modernizing its CX and operations.

If you’re a CIO, CTO, or CX leader thinking about AI beyond pilots, this episode offers a grounded look at what’s working, what isn’t, and how to build a foundation for scale.

What You’ll Learn

• Where AI can drive meaningful cost savings today without hurting CX
• Why bad automation is usually a design problem, not a technology problem
• How enterprises think about personalization when data is fragmented
• What governance looks like when AI starts touching real customer interactions
• How to prioritize CX and AI investments when budgets are tight