Tech Talks Daily

*]:pointer-events-auto scroll-mt-[calc(var(--header-height)+min(200px,max(70px,20svh)))]" dir="auto" tabindex="-1" data-turn-id= "request-WEB:46fbdb14-2fd7-425c-ac70-5727a2453611-0" data-testid= "conversation-turn-2" data-scroll-anchor="true" data-turn= "assistant"> Have you noticed how every week brings a new headline about AI driven fraud, yet it still feels hard to tell what is real risk and what is noise?
In this Tech Talks Daily episode, I'm joined by Tommy Nicholas, CEO of Alloy, for a candid conversation that cuts through the fear driven commentary and gets into what fraud teams are actually dealing with right now. 
We start with a simple but important distinction that gets blurred all the time. Tommy separates classic "fraud," where institutions take the hit, from "scams," where individuals are manipulated into handing over money or access. That framing changes how you think about solutions, accountability, and where AI is making things worse.
Tommy also shares why he believes fraud losses are often massively underreported. It is not because people are trying to hide the truth, it is because organizations rarely have a single, clean view of losses across every product line and channel.
Add messy labeling, split ownership across teams, and reporting becomes a best effort estimate rather than an objective number. That reality matters if you're building board level narratives, budgets, or risk models on top of survey data.
From there, we talk about what organizations are getting right. Tommy argues there is no magical "undetectable" attack that forces teams to give up, but there is a very real breakdown happening in old fallbacks, especially human review of images and video.
The bigger shift he sees is banks and fintechs finally pushing for consistent tooling across every channel, web, mobile, branch, call center, support tickets, because fraud does not respect internal org charts.
We then get into why Alloy's AI Assistant is an interesting signal for where agentic AI is heading in regulated work. Tommy explains that agents are only useful when they have rigorous context, strong sources of truth, and clear workflows.
Otherwise they guess, and "looks good" is not the same as "safe to run in production." He also lays out where agents can genuinely outperform humans, like scaling investigations during sudden surges, while keeping processes auditable and repeatable.
We close by looking ahead at agentic commerce, and why Tommy thinks the breakthrough will arrive through weird, emergent behavior rather than a neat protocol roll out. 
When you listen back, do you think the next big leap in fraud prevention will come from better models, better data, or better operational discipline, and what would you bet on if your own customers were the ones on the line?

How do you prepare an entire generation for a world where AI is already shaping how we work, create, and solve problems?
In this episode of Tech Talks Daily, I'm joined by Dr. Tara Nattrass, Chief Innovation Strategist for Education at Lenovo, for a grounded and thoughtful conversation about what responsible AI integration really looks like in K–12 classrooms.
Tara brings more than 25 years of experience inside school districts, including serving as Assistant Superintendent for Teaching and Learning in Arlington Public Schools, so this isn't a theory-led discussion. It's informed by lived experience.
We explore how the conversation has shifted over the past 18 months. AI has been present in schools for years through adaptive software and analytics, but the arrival of generative and now agentic AI tools has accelerated everything. As Tara explains, the debate is no longer about whether AI should be in schools. It's about how to approach it responsibly, strategically, and in ways that genuinely improve learning outcomes.
A big theme in our conversation is AI literacy. Tara breaks this down in practical terms, moving beyond technical understanding to include critical thinking, creativity, collaboration, and the ability to evaluate risk and bias. She shares real examples of students designing AI tools to solve problems in their communities, shifting the focus from passive consumption to active creation.
We also talk about infrastructure readiness. Many school systems have bold ambitions around AI, but there is often a gap between vision and technical capability. AI-ready devices, intelligent infrastructure, cybersecurity, and data governance all play a role in making innovation sustainable rather than experimental.
 Lenovo's approach, as Tara describes it, centers on building education ecosystems rather than simply refreshing hardware.
There is also a careful balance to strike between innovation, privacy, and inclusion. From hybrid AI models to questions around where data is stored and who can access it, schools are navigating complex decisions. Tara shares how Lenovo partners with districts, policymakers, and organizations such as ISTE and ASCD to align infrastructure, professional learning, and governance frameworks.
Looking ahead, we discuss what will separate school systems that truly benefit from AI from those that simply layer new tools onto old teaching models. Vision, educator upskilling, cybersecurity, and rethinking assessment all feature prominently in her answer.
If you are working in education, technology leadership, or policy, this conversation offers a practical view of how AI-ready classrooms are being built today and what still needs to happen next.
As always, I'd love to hear your thoughts. How is AI reshaping learning in your organization, and are you ready for what comes next?

*]:pointer-events-auto scroll-mt-[calc(var(--header-height)+min(200px,max(70px,20svh)))]" dir="auto" tabindex="-1" data-turn-id= "request-WEB:b0120523-17fc-4d94-97d7-97b3e135ed14-3" data-testid= "conversation-turn-8" data-scroll-anchor="true" data-turn= "assistant"> What does autonomous IT really look like when you move beyond the slideware and start wiring systems together in the real world?
At Dynatrace Perform in Las Vegas, I sat down with Pablo Stern, EVP and GM of Technology Workflow Products at ServiceNow, to unpack exactly that. Pablo leads the teams focused on CIOs and CISOs, building the workflows and security products that sit at the heart of modern IT organizations. From service desks and command centers to risk and asset management, his remit is clear: enable AI to work for people, not the other way around.
We began with ServiceNow's deepening multi-year partnership with Dynatrace. While the announcement made headlines, Pablo was quick to point out that the real story starts with customers. This collaboration is rooted in a shared goal of helping joint customers reduce outages, improve SLA adherence, and shrink mean time to resolution. The vision of autonomous IT operations is not about hype. It is about connecting observability data with deterministic workflows so that insight can evolve into coordinated, system-level action.
Pablo walked me through the maturity curve he sees emerging. First came AI-powered insight, summarizing data and surfacing signals from noise. Then came task automation, drafting knowledge articles, paging teams, triggering predefined playbooks. The next step, and the one that excites him most, is orchestrated autonomy. That means stitching together skills, agents, and workflows into systems that can drive end-to-end outcomes. It is a journey measured in years, not months, and it depends as much on digitizing process and building trust as it does on technology.
We also explored root cause analysis, still one of the biggest time drains in IT. By combining Dynatrace's AI-driven observability with ServiceNow's workflow engine, enterprises can automate forensic steps, correlate events faster, and shorten the time spent on major incident bridges where teams debate ownership. Even incremental improvements in accuracy can save hours when incidents strike.
Trust, of course, remains central. Pablo was candid that full self-healing systems are still some distance away. What we will see first is relief automation, controlled failovers, scripted actions suggested by machines but approved by humans. Over time, as confidence grows and processes become fully digitized, the balance will shift.
Beyond the technology, a consistent theme ran through our conversation. Outcomes have not changed. Enterprises still want higher availability, faster resolution, better employee experiences. What is changing is the how. ServiceNow is reimagining its platform to deliver those outcomes at a much higher standard, not through incremental tweaks, but through rethinking workflows for an AI-first world.
From design partnerships with banks building pre-flight change checks, to internal teams acting as the toughest customers, this was a grounded, practical conversation about where autonomous operations are headed and what it will take to get there.
If you are a CIO, CISO, or IT leader wondering how to move from theory to execution, this episode offers a clear-eyed look behind the curtain.

What happens when nearly half of organizations admit they have no AI-specific security controls, yet AI-driven data leaks are accelerating at the same time?
In this episode of Tech Talks Daily, I spoke with Aayush Choudhry, CEO and co-founder of Scrut Automation, about what he sees as a blind spot in the cybersecurity industry. While much of the market continues to design tools for Fortune 500 enterprises with deep pockets and large security teams, Aayush argues that the real existential risk sits with the 99 percent of businesses that cannot survive a serious breach.
Aayush brings a founder's perspective shaped by firsthand pain. Before launching Scrut, he and his co-founder experienced the grind of managing compliance and security as a cloud-native startup trying to sell into enterprises. They were outsiders to GRC and security at the time, forced to learn from first principles. That experience became the foundation for Scrut Automation, a modern GRC platform built specifically for small and mid-sized companies that cannot afford six-month implementations, armies of consultants, or half-million-dollar tooling budgets.
We explore why treating compliance and security as separate functions increases risk for smaller organizations. In the mid-market, the same small team is often responsible for both. When compliance is handled as a box-ticking exercise and security as a separate technical discipline, gaps emerge. Scrut's approach converges governance, risk, and security signals into a unified layer that translates hundreds of technical alerts into context-aware risks that actually matter to the business.
Our conversation also tackles AI complacency. Using the classic confidentiality, integrity, and availability framework, Aayush outlines what minimum viable AI security hygiene looks like in practice. That includes ensuring AI agents are not over-privileged compared to the humans they represent, placing guardrails around sensitive data fed into models, and extending supply chain security thinking to agentic integrations. For resource-constrained teams, these are not theoretical concerns. They are daily realities.
Perhaps most compelling is his view that AI can act as a force multiplier for small teams. By embedding accumulated expertise into agents trained on anonymized patterns and edge cases, Scrut aims to democratize security know-how that would otherwise require multiple full-time analysts. The goal is simple but ambitious: make enterprise-grade security outcomes accessible without enterprise-grade headcount.
If you are leading a small or mid-sized business and wondering how to balance growth, compliance, and AI risk without breaking the bank, this conversation offers a candid look from the trenches.

How do you build enterprise software for the companies that keep the world turning, while also building a leadership culture where people can actually thrive?
In this episode of Tech Talks Daily, I spoke with Kerrie Jordan, Chief Marketing Officer and SVP at Epicor, about her journey from studying literature to helping shape cloud ERP strategy at a global software company serving more than 20,000 customers worldwide. Kerrie's story is a reminder that there is no single path into technology leadership. Sometimes the foundations are laid in unexpected places, through storytelling, creativity, and a deep curiosity about people.
Kerrie shares how her early career in product lifecycle management opened her eyes to the human side of software. Interviewing customers and writing case studies showed her that behind every system implementation is a personal story, a career milestone, or a business trying to survive and grow. That perspective still shapes how she approaches product and marketing today at Epicor, a company recently recognized as a Leader in the Gartner Magic Quadrant for Cloud ERP for Product-Centric Enterprises for the third consecutive year.
But this conversation goes far beyond market recognition. We talk openly about burnout, resilience, and the reality of leading through pressure. Kerrie reflects on the importance of protecting time, creating space to reconnect, and building a culture where empathy is practiced, not just discussed. Her view of leadership is grounded in communication, psychological safety, and being tough on problems rather than people.
Mentorship is another thread running throughout our discussion. Kerrie explains why powerful mentorship is not passive. It requires vulnerability, preparation, and a willingness to hear difficult advice. A single phrase from a mentor early in her career, "stick-to-itiveness," continues to shape how she approaches hard problems today.
We also explore the future of women in manufacturing and technology. Kerrie highlights the need for intentional change across education, early career development, and leadership visibility. She believes technology, particularly AI, can expand access, enable upskilling, and introduce flexibility that supports long-term career growth. At the same time, she makes a simple but powerful point. Women in tech want the same thing as anyone else: the space and autonomy to do their jobs well.
From customer co-innovation and community-driven product roadmaps to inclusive leadership under commercial pressure, this episode offers a candid look at what it really takes to lead in enterprise technology today.
If you are building products, leading teams, or questioning your own next career step, I think you will find something in Kerrie's story that resonates.