Tech Talks Daily

Neil C. Hughes

If every company is now a tech company and digital transformation is a journey rather than a destination, how do you keep up with the relentless pace of technological change?

Every day, Tech Talks Daily brings you insights from the brightest minds in tech, business, and innovation, breaking down complex ideas into clear, actionable takeaways.

Hosted by Neil C. Hughes, Tech Talks Daily explores how emerging technologies such as AI, cybersecurity, cloud computing, fintech, quantum computing, Web3, and more are shaping industries and solving real-world challenges in modern businesses.

Through candid conversations with industry leaders, CEOs, Fortune 500 executives, startup founders, and even the occasional celebrity, Tech Talks Daily uncovers the trends driving digital transformation and the strategies behind successful tech adoption. But this isn't just about buzzwords.

We go beyond the hype to demystify the biggest tech trends and determine their real-world impact. From cybersecurity and blockchain to AI sovereignty, robotics, and post-quantum cryptography, we explore the measurable difference these innovations can make.

Whether improving security, enhancing customer experiences, or driving business growth, we also investigate the ROI of cutting-edge tech projects, asking the tough questions about what works, what doesn't, and how businesses can maximize their investments.

Whether you're a business leader, IT professional, or simply curious about technology's role in our lives, you'll find engaging discussions that challenge perspectives, share diverse viewpoints, and spark new ideas.

New episodes are released daily, 365 days a year, breaking down complex ideas into clear, actionable takeaways around technology and the future of business.

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June 3 · 23 min
Zscaler's Ripple Effect Report Reveals The Cyber Resilience Gap
Are organizations investing enough in cybersecurity, or are they simply spending more money while falling further behind? In this episode of Tech Talks Daily, I speak with Martyn Ditchburn, CTO in Residence for EMEA at Zscaler, about the findings from the company's latest Ripple Effect Report and what it reveals about the growing gap between cybersecurity investment and true organizational resilience. Drawing on insights from more than 1,700 IT leaders across 14 countries, Martyn explains why many organizations are still struggling to adapt to a threat landscape that is evolving faster than their security strategies. While cyber resilience budgets continue to rise, many leaders admit their approach remains too inward-looking, leaving critical vulnerabilities across supply chains, cloud environments, third-party ecosystems, and emerging AI deployments. We explore why shadow AI is rapidly becoming the new shadow IT challenge, with employees adopting AI-powered tools faster than governance frameworks can keep pace. Martyn discusses how AI is quietly being embedded into countless business applications, creating visibility and security challenges that many organizations have yet to recognize fully. The conversation also examines the growing importance of supply chain resilience. As businesses become increasingly dependent on external providers, cloud platforms, and interconnected digital services, traditional security perimeters continue to disappear. Martyn shares why third-party risk remains one of the biggest blind spots in modern cybersecurity programs and how organizations can better understand their expanding attack surface. Agentic AI is another major focus of our discussion. As AI systems move beyond assisting users and begin taking autonomous actions, security teams face entirely new challenges around identity, governance, accountability, and risk management. Martyn explains why many organizations are racing ahead with adoption while still lacking the guardrails needed to manage these emerging technologies safely. We also discuss lessons from previous technology shifts, including cloud computing and shadow IT, and why history keeps repeating itself when innovation outpaces security planning. Martyn offers practical advice on limiting risk, reducing blast radius through segmentation, and treating AI agents as digital identities that require the same controls and oversight as human users. As organizations pursue AI-driven growth and competitive advantage, are they building resilience into their foundations or creating new risks they cannot yet see? And in a world where AI is becoming embedded in everything, how can security leaders stay ahead of threats that are evolving faster than ever before?
June 2 · 28 min
Outshift By Cisco On Connecting The Next Generation Of AI Agents
At Cisco Live, I sat down with Papi Menon, Vice President of Product Management at Outshift by Cisco, to explore one of the most ambitious ideas emerging in the AI world today. While much of the industry remains focused on larger models and individual AI agents, Outshift is asking a different question. What happens when millions of AI agents need to collaborate across organizations, platforms, and industries? Papi joined me to explain the thinking behind Outshift, Cisco's emerging technology and incubation group, and the work they're doing to help shape the next era of AI. Our conversation explored concepts such as the Internet of Agents, the Internet of Cognition, and AGNTCY, an open-source initiative designed to create the foundations for agent-to-agent collaboration at scale. We discuss why connecting AI agents is only the first step, why shared intent and shared context could become as important as connectivity itself, and how organizations may need entirely new infrastructure to support an increasingly agent-driven future. Papi also shares his perspective on the challenges of interoperability, governance, trust, and security as AI systems become more autonomous and interconnected. The discussion moves beyond today's AI headlines and into the bigger questions facing the technology industry. If the internet connected people and systems, what infrastructure will be needed to connect intelligence itself? And what role can open standards play in ensuring that future remains collaborative rather than fragmented? Whether you're a technology leader, developer, strategist, or simply curious about where AI is heading next, this conversation offers a fascinating glimpse into how Cisco is thinking about the future of agentic computing and the foundations that may underpin the next major platform shift in technology. How do you think AI agents will collaborate in the future, and should that future be built on open standards or closed ecosystems?
June 2 · 38 min
Zoho On Balancing AI Innovation With Trust, Control, And Digital Sovereignty
Can businesses embrace AI without surrendering control over their data, technology choices, and future direction? In this episode of Tech Talks Daily, I sit down with Sachin Agrawal, Managing Director of Zoho UK, to discuss one of the biggest challenges facing organizations today. As AI adoption accelerates, many leaders are finding themselves caught between the pressure to innovate and the responsibility to maintain trust, transparency, and control. Sachin shares his perspective on what separates successful AI adoption from costly experimentation. Drawing on his experience leading Zoho's growth in the UK, he explains why organizations achieving the best results are focusing on clearly defined business outcomes rather than chasing headlines or reacting to fear of missing out. We discuss how AI is already improving customer service, sales operations, application development, and decision-making, while also highlighting the importance of digital maturity as a foundation for meaningful AI success. A major theme throughout our conversation is the growing concern around black-box AI systems. Sachin explains why transparency, explainability, and contextual intelligence are becoming increasingly important for businesses operating in regulated environments. We explore how organizations can build trust by keeping AI close to the systems where their data already resides, thereby creating more auditable, accountable outcomes. The discussion also turns to digital sovereignty, a topic that has rapidly moved from technical teams into boardroom conversations. Sachin outlines the different dimensions of sovereignty, including data residency, infrastructure, model choice, intelligence ownership, and vendor flexibility. As geopolitical tensions, regulatory expectations, and concerns about technology concentration grow, organizations are taking a closer look at how dependent they want to become on a small number of technology providers. We also examine whether AI will strengthen the dominance of major technology firms or create new opportunities for diverse software providers. Sachin argues that while the largest players may own much of the underlying infrastructure, customers are increasingly focused on practical outcomes, transparency, and flexibility rather than simply choosing the biggest platform. Along the way, we discuss cloud fragmentation, governance, responsible AI adoption, data privacy, and the importance of challenging AI rather than unquestioningly trusting its outputs. Sachin offers practical advice for leaders who want to balance innovation with accountability while maintaining independence in an increasingly interconnected technology environment. As AI continues to reshape business software and digital operations, how can organizations remain agile without sacrificing control? And what role will digital sovereignty play in determining who succeeds in the next era of enterprise technology?
June 1 · 20 min
Risk Ledger Explains The Hidden Risks Inside Modern AI Supply Chains
What happens when the weakest link in your technology supply chain becomes the entry point for a national security incident? In this episode of Tech Talks Daily, I welcome back Haydn Brooks, CEO and founder of Risk Ledger, to discuss why supply chain security has moved from an IT concern to a boardroom and government priority. As organizations race to adopt AI, connect more systems, and depend on increasingly complex ecosystems of vendors, partners, cloud providers, and third-party services, the attack surface continues to expand in ways many businesses still struggle to understand. Haydn explains why supply chains remain one of the largest blind spots in cybersecurity, despite years of warnings and a growing list of high-profile incidents. We explore how attackers increasingly target smaller suppliers that lack the resources and expertise of larger enterprises, using them as stepping stones to reach critical infrastructure, government agencies, and major corporations. The conversation also examines how AI is reshaping the risk equation. As organizations rapidly integrate AI tools, APIs, and third-party models into existing technology stacks, many are creating new forms of concentration risk. What happens when multiple services rely on the same AI provider? And how can businesses maintain visibility over technology dependencies that are constantly evolving? Haydn shares his perspective on why collaboration and information sharing have become far more common across the cybersecurity community, and why security leaders are beginning to recognize that defending against modern threats requires collective action rather than isolated efforts. We also discuss accountability, resilience, and why organizations must move beyond simply identifying risk and develop the ability to understand the impact of incidents when they occur. Along the way, Haydn offers practical advice for security leaders, explains why now is the time to reassess supply chain security strategies, and shares insights into Risk Ledger's international expansion as the company grows its presence in the United States. As AI accelerates innovation and organizations become increasingly interconnected, are businesses truly prepared for the risks that come with that progress? And could an overlooked supplier become the starting point for the next major cybersecurity crisis?
May 31 · 30 min
How TinyMCE Is Bringing AI Directly Into The Content Creation Workflow
Have you ever stopped to think about the technology powering almost every text box you interact with online? Whether you're applying for a job, drafting a legal contract, publishing content, or updating a website, there's a good chance a rich text editor is quietly working behind the scenes. In this episode of Tech Talks Daily, I caught up with Fredrik Danielsson, Product Manager at TinyMCE, to discuss how one of the internet's most widely used editing platforms is evolving for the AI era. Frédéric shares the remarkable story behind TinyMCE, a tool that traces its roots back to the early days of the web and has played a role in creating much of the internet's human-generated content. From the days of hand-coded websites and Flash applications to today's AI-powered content workflows, we explore how the company has continually adapted to changing developer and user needs. Our conversation focuses on the launch of TinyMCE AI and why the company believes artificial intelligence belongs inside the content creation experience rather than in a separate chatbot window. We discuss the hidden productivity costs of constantly switching between applications, copying and pasting content between AI assistants and business tools, and why bringing AI directly into the editor creates a more natural and efficient workflow. We also examine the growing challenges around AI governance, content ownership, compliance, and accountability. As organizations race to adopt AI tools, how can they maintain visibility into which content was AI-assisted, who made changes, and how information flows through the business? Frédéric explains why features such as revision history, track changes, and audit trails may become increasingly important as regulations and expectations mature. Along the way, we discuss context-aware AI, model flexibility, developer experience, and the future of content creation. Frédéric also shares his thoughts on why AI adoption is becoming more natural for everyday users and what the next phase of AI-powered productivity could look like as these tools become deeply embedded in the software people already use. If AI is changing how we create, edit, review, and collaborate on content, what happens when the editor itself becomes the smartest participant in the room? And how will that reshape the way we work over the next few years?
May 30 · 23 min
Can AI Improve Trust Between Political Campaigns And Voters?
Have you ever wondered why political campaigns can send millions of text messages but still struggle to have meaningful conversations with voters? In this episode of Tech Talks Daily, I sit down with Tom Carroll, Co-Founder of Convos, a startup rethinking how political campaigns communicate through SMS. While political texting has become a standard part of modern campaigning, Tom argues that the industry has spent years solving the problem of message delivery while largely ignoring what happens when voters actually respond. We explore how Convos is building a conversational SMS infrastructure that helps campaigns manage thousands of voter interactions simultaneously. Rather than focusing solely on message volume, the platform analyzes replies, identifies sentiment and alignment, prioritizes urgent conversations, and helps campaigns understand what voters are really talking about. Tom shares how this approach is helping campaigns move beyond one-way broadcasts and toward genuine engagement at scale. During our conversation, we discussed why traditional political texting often breaks down once campaigns begin receiving large volumes of replies, how AI-powered conversational systems can help manage those interactions responsibly, and why transparency remains essential when introducing AI into political communications. Tom also explains how Convos uses campaign-approved knowledge bases and multiple validation checks to reduce misinformation and maintain message consistency. We also examine the broader implications of conversational AI in politics, from voter education and turnout efforts to balancing automation with authenticity. Tom shares examples of how campaigns have used conversational SMS to answer voter questions, provide election information, and create opportunities for meaningful engagement without overwhelming campaign staff. As AI continues to influence how organizations communicate with large audiences, this conversation offers an interesting look at how technology can help people listen at scale rather than talk louder. What role should AI play in political engagement, and where should the line be drawn between helpful voter communication and automated persuasion? Share your thoughts and join the conversation.
May 29 · 24 min
Adobe Summit: Why Context Is the Missing Ingredient in Enterprise AI
How do you move beyond AI experimentation and start building systems that can genuinely reason, act, and create value across an enterprise? Recorded at Adobe Summit in Las Vegas, this episode features Daniel Sheinberg, who leads cross-portfolio product initiatives for Adobe's Customer Experience Orchestration business. Daniel is at the center of Adobe's AI and agentic strategy, helping shape how some of the world's largest organizations think about the next generation of customer experiences. During our conversation, Daniel cuts through the hype surrounding agentic AI and explains what actually separates an AI assistant from an AI agent. We explore how advances in reasoning, memory, context awareness, and tool usage are enabling systems that can move beyond generating content to actively helping organizations achieve business goals. Daniel shares practical examples of how enterprises are using these capabilities to personalize customer journeys at a level that would have been impossible with traditional workflows. We also discuss the rise of AI-powered brand concierges, including how are using agentic experiences to create more meaningful customer interactions. Daniel explains why context is becoming one of the most valuable assets in enterprise AI, how businesses can prepare their data and systems for agentic workflows, and why governance, trust, and brand intelligence will play such an important role in successful deployments. If you're trying to understand where AI is heading next, what customer experience orchestration really means, and how businesses can safely deploy agentic AI at scale, this conversation offers a valuable look at both the opportunities and the challenges ahead.
May 28 · 22 min
AI, Analytics, And Conservation: The Nature Conservancy's Data Transformation Story
What does better analytics actually mean when your mission is protecting the planet? At SAS Innovate, I sat down with John Blackwell, Director of Strategic Analytics at The Nature Conservancy, to explore how data, AI, and marketing intelligence are helping one of the world's largest conservation organizations raise more money, operate more efficiently, and ultimately direct more resources toward protecting land, water, and ecosystems across more than 80 countries. In this episode, John explains how analytics has become a critical part of modern conservation strategy. With fundraising supporting everything from habitat protection to climate resilience projects, improving donor retention and increasing fundraising efficiency directly impacts how much work The Nature Conservancy can do around the world. John shares how the organization improved donor retention by 10 percent and increased year-over-year giving by 30 percent by moving away from siloed systems and toward a more connected, data-driven approach. We discuss how analytics helps identify long-term donor potential, personalize supporter journeys, optimize fundraising asks, and create a clearer 360-degree view of donor engagement across email, direct mail, telemarketing, and digital channels. John also explains why personalization in the nonprofit world requires a very different balance than in commercial marketing. Trust and authenticity matter just as much as performance metrics. The conversation also explores how AI is quietly changing the way nonprofit analytics teams operate. From speeding up model development to improving feature selection and identifying rare high-value donor opportunities through synthetic data generation, John shares where he sees AI creating immediate practical value without compromising the human voice of the organization. What stood out most to me is how this is ultimately a story about efficiency creating impact. The more effective The Nature Conservancy becomes at fundraising and donor engagement, the more money can go directly toward conservation rather than operational overhead. And in a world where every nonprofit is competing for attention, funding, and trust, analytics may quietly become one of the most important tools available for protecting the future of our planet. So, as organizations continue investing in AI and analytics, are they focusing enough on the real-world outcomes those technologies can help create?
May 27 · 37 min
How Navan is Simplifying Business Travel & Expense Management With AI
What happens when one of the world's fastest-growing travel platforms decides the future of business travel will be built around AI from the ground up? In this episode of Tech Talks Daily, I sat down with Navan co-founder and CTO Ilan Twig to discuss how the company is reshaping travel, payments, and expense management through AI-native systems designed for the real world, not just polished demos. What immediately stood out during our conversation was Ilan's mix of technical obsession and relentless focus on user experience. This is someone who isolated himself for months to truly understand the mechanics of large language models before most companies had even worked out what ChatGPT meant for their business. That curiosity now powers Navan's AI strategy, where conversational interfaces are replacing what Ilan calls the old "forms and tables" model of software interaction. We explored how Navan's AI assistant, Ava, is already handling thousands of real-world travel support conversations every day, with customer satisfaction scores that rival those of human agents. During major disruption events like Storm Fern and the Heathrow airport fire, Ava scaled instantly, resolving huge volumes of customer requests without the delays and staffing nightmares that traditionally overwhelm travel providers. But this conversation goes much deeper than travel. Ilan shared his thoughts on why the software industry is moving toward conversational, context-aware interfaces, why most businesses still misunderstand what agentic AI actually means, and how Navan is building proprietary models trained on its own travel data to outperform larger, generic frontier models. We also discussed trust, hallucinations, AI supervision layers, and why companies must stop treating AI as a magic trick and start measuring it against hard business outcomes. There is also a fascinating human side to this episode. From building a company through market turbulence, investor skepticism, and geopolitical uncertainty, to challenging accepted thinking since his school days, Ilan's story reflects the mindset of someone who genuinely believes technology should solve real problems rather than create headlines. If you have been wondering where AI moves beyond hype and starts delivering measurable operational value, this conversation offers a rare look behind the curtain from someone building these systems at scale every single day. Useful Links Connect with Ilan Twig Learn more about Navan Check out blog posts by Navan Follow Navan on LinkedIn Visit our Sponsors Check out the Nordlayer Browser Learn more about Denodo Data Products
May 26 · 35 min
Denodo and The AI Trust Gap: The Enterprise Data Crisis Behind AI Adoption
What happens when AI systems stop acting like assistants and start acting like autonomous decision-makers inside your business? And if those systems are pulling information from fragmented, inconsistent, and poorly governed data environments, how much trust can organizations really place in the outcomes? In today's episode, I'm joined by Terry Dorsey for a fascinating conversation about the growing gap between AI ambition and enterprise reality. Terry brings decades of experience spanning enterprise architecture, business intelligence, operations, healthcare, utilities, manufacturing, and defense. Long before AI became the headline topic dominating every boardroom conversation, he was already working deeply in semantic modeling, natural language systems, and the architectural foundations that modern AI now depends on. At the center of our discussion is the new AI Trust Gap report from Denodo, which reveals why so many organizations are struggling to move AI projects from experimentation into reliable production environments. We explore why live data matters so much in an agentic AI world, why "more data" often creates more confusion instead of clarity, and how inconsistent business meaning across systems quietly undermines AI trust inside large organizations. Terry explains why many enterprises are still operating on architectures originally designed for historical reporting and analytics, while now expecting those same environments to support autonomous AI systems making real-time operational decisions. From semantic sprawl and duplicated business logic to governance failures and fragmented security models, we unpack the hidden technical debt that AI is now exposing at scale. The conversation also takes a deeper philosophical turn as we discuss why enterprise meaning itself may become the future control plane for AI. Terry shares why provenance, explainability, and semantic consistency are no longer optional concerns reserved for compliance teams, they are becoming foundational requirements for trustworthy AI systems capable of operating autonomously. We also discuss why governance cannot be bolted on after deployment, how logical data management helps organizations reduce duplication and maintain operational trust, and why the companies that succeed with agentic AI will not necessarily be the fastest movers, but the ones building stable and reusable architectural foundations beneath the surface. If your organization is rushing toward AI adoption while wrestling with siloed systems, disconnected data, and growing governance concerns, this episode offers a much-needed reality check. Because, as Terry explains, the future competitive advantage may have less to do with the AI model itself and far more to do with the architecture, meaning, and trust frameworks supporting it. Useful Links Terry Dorsey LinkedIn Denodo LinkedIn Denodo Website The AI Trust Gap Report — global survey of 850 executives that explores why organizations are investing heavily in AI, but many still can't fully trust the data behind it. O'Reilly's The Rise of Logical Data Management, by Christopher Gardner — explains what's necessary to enable true self-service data access and 24/7 AI-ready data. The Enterprise AI and Data Management Glossary — glossary that helps ensure both technical and non-technical professionals can make informed decisions, optimize strategies, and align on best practices for digital transformation. The ROI of Using the Denodo Platform alongside the Modern Data Lakehouse — Drawing on interviews with numerous global enterprises and applying a comprehensive ROI methodology, this study, conducted by independent analyst Veqtor8, found that by using Denodo alongside their data lakehouse, they realized considerable benefits. Agentic AI Manifesto — a blueprint for credible autonomy at enterprise scale. Denodo's standard for the next era of trusted, autonomous enterprise AI.
May 25 · 23 min
Cisco's AI Transformation Journey From Fragmented Systems To Smarter Workflows
What does AI transformation actually look like inside one of the world's largest engineering organizations? At Team '26 in Anaheim, I recently sat down with Jason Andrews to unpack how Cisco transformed decades of fragmented tooling, disconnected workflows, and spreadsheet-driven operations into a unified system of work built around Jira, Confluence, Jira Service Management, automation, and AI-ready workflows. And honestly, this conversation felt refreshingly practical. Jason oversees engineering operations across Cisco Networking, a business unit with around 22,000 engineers and product managers representing roughly $40 billion in annual revenue. So when he talks about transformation, this isn't theory. This is operational change happening at enterprise scale. We discuss how Cisco consolidated more than 85 Jira instances, reduced tooling spend by 54%, and accelerated reporting by 40x while creating a far more scalable engineering organization. But as Jason explains throughout the conversation, the real challenge was never the technology itself. It was getting teams to rethink how they wanted to work moving forward rather than simply migrating years of technical debt into modern systems. One of the strongest themes in this episode is the difference between transformation and migration. Jason explains why organizations often fail when they focus only on moving systems rather than changing workflows, behaviors, and operational culture at the same time. We also dive deep into AI adoption inside engineering organizations. Jason shares how Cisco is already seeing significant productivity gains from AI-assisted development, why organizational context matters so much for enterprise AI success, and why he believes the industry is still massively underestimating how much structured data and workflow consistency AI systems actually require. Along the way, we unpack scenario planning in the AI era, why annual planning cycles are becoming increasingly fragile, and how leaders can move from rigid long-term roadmaps toward more agile operational playbooks capable of adapting to constant disruption. There's also a fascinating discussion around the so-called "SaaS apocalypse," the limits of AI-generated software, and why Jason believes humans will remain central to enterprise operations for years to come, especially in organizations managing millions of lines of legacy code and decades of accumulated institutional knowledge. If your organization is currently navigating modernization, operational complexity, AI adoption, or large-scale systems transformation, this episode is packed with lessons learned from the front lines of enterprise change. And perhaps most importantly, Jason offers a reminder that AI alone is not the strategy. The real opportunity comes from reducing friction, improving context, and helping teams spend more time solving meaningful problems instead of manually stitching systems together.
May 24 · 28 min
From Olympic Trials Swimmer To AI Founder, Kaitlyn Albertoli's Mission To Protect Critical Infrastructure
What Happens When AI Starts Protecting the Power Grid Before Humans Even Spot the Problem? In this episode of Tech Talks Daily, I speak with Kaitlyn Albertoli, co-founder and CEO of Buzz Solutions, about how AI, drones, and computer vision are changing the way utilities inspect and maintain power infrastructure. As weather events become more frequent and energy demand continues to rise from EV adoption, renewable energy growth, and AI-driven data centers, utilities are under growing pressure to modernize systems that were built decades ago. Kaitlyn explains how utilities once relied on crews walking transmission lines with binoculars and handwritten notes before moving toward helicopter inspections and aerial imaging. Today, autonomous drones and aircraft can capture hundreds of thousands of inspection images every year. The real challenge now is turning that mountain of visual data into useful action before damaged equipment leads to outages, fires, or safety risks. We discuss how Buzz Solutions processes enormous image datasets in hours instead of weeks, helping utilities identify damaged insulators, corrosion, vegetation risks, and failing components before they become larger problems. We also talk about the people behind the infrastructure. Kaitlyn shares why AI should support frontline workers rather than replace them, especially as utilities face an estimated shortage of thousands of skilled linemen over the next several years. The conversation covers balancing false positives with missed detections, reducing operational data silos, and why partnerships with companies like Skydio and Esri are helping utilities connect inspection workflows more effectively. Kaitlyn also shares how Buzz Solutions is expanding into solar inspections, where AI can detect damaged or underperforming panels before warranties expire and energy production quietly drops over time. Alongside the technology discussion, she reflects on how competing in the 2012 U.S. Olympic Trials shaped the resilience and mindset she now brings to building a fast-growing AI company. From wildfire prevention and storm recovery to renewable energy operations and autonomous inspections, this episode looks at how AI is quietly becoming part of the infrastructure keeping modern society running. As utilities modernize aging systems under growing environmental and operational pressure, can AI help prevent the next major outage before it happens?
May 23 · 28 min
Kiteworks on the AI Security Lessons From RSA 2026
What happens when the cybersecurity industry stops debating whether agentic AI is a future problem and starts treating it as a present-day reality? In this episode of Tech Talks Daily, I sit down with Tim Freestone to unpack the biggest shift coming out of this year's RSA Conference. After attending RSA for more than two decades, Tim describes 2026 as the year the energy returned to the cybersecurity world, driven by one unavoidable topic: agentic AI. We explore why the conversation has rapidly evolved from curiosity to urgency, and why organizations are suddenly confronting an uncomfortable truth. AI agents are already operating inside businesses, often without visibility, governance, or control. Tim explains how shadow AI is spreading faster than many leadership teams realize, with employees experimenting with autonomous tools that connect directly to company data and external AI models. Our conversation also looks at the growing gap between visibility and control. Security teams may be discovering agents across their networks, but stopping risky behavior is an entirely different challenge. Tim argues that companies focusing purely on infrastructure are already falling behind, and that the real battleground is now the data layer itself. We discuss why data governance, audit trails, and access controls are becoming central to the future of cybersecurity strategy. Tim also shares his thoughts on state-sponsored AI threats, the rise of autonomous espionage operations, and why open-source AI models present a completely new level of risk for defenders. At the same time, he offers practical advice for IT and security leaders trying to figure out where to start amid the noise, complexity, and endless flood of new tools entering the market. If your organization is trying to understand how AI changes cybersecurity, governance, compliance, and risk management, this conversation offers a clear look at what security leaders are actually worried about right now, and why the next 12 months may redefine how companies think about protecting data altogether. Useful Links Connect with Tim Freestone Learn More About Kiteworks Data Security and Risk Report Kiteworks Substack Kiteworks LinkedIn Newsletter Please check the partners of the Tech Tech Talks Network Learn more about the NordLayer Browser Visit Denodo.com
May 22 · 29 min
How The International Rescue Committee (IRC) Is Scaling Humanitarian Support With AI
What if some of the most important applications of AI today have nothing to do with productivity, marketing, or enterprise automation, and everything to do with helping people survive crisis, displacement, and uncertainty? In this episode, recorded at, I sit down with André Heller Pérache to explore how technology originally designed for customer service has evolved into humanitarian infrastructure supporting refugees and displaced communities around the world. André shares the story behind Signpost, a global digital initiative from the International Rescue Committee that now operates across roughly 30 countries and 25 languages, helping register more than 20 million users while supporting over 500,000 digital social work consultations. But this conversation goes much deeper than technology. We discuss what happens when trusted information becomes as important as food, shelter, or medical support during times of crisis. André explains how Signpost was born from the realization that vulnerable communities were already living digitally through smartphones, WhatsApp, Facebook, and social platforms while much of the humanitarian sector still relied on traditional offline systems. We also explore the responsible use of AI in high-stakes environments where mistakes can have real-world consequences for refugees, families, and vulnerable populations. André shares why the IRC sees AI as one of the humanitarian sector's biggest bets at a time when armed conflict, climate disasters, and shrinking budgets are putting enormous pressure on aid organizations globally. From misinformation and trust to reducing cognitive burden and scaling empathy through technology, this episode offers a powerful reminder that behind every AI conversation are ultimately human beings searching for dignity, safety, clarity, and hope.
May 21 · 28 min
Zendesk Relate 2026: The Shift From AI Assistants To Autonomous Systems
What if the future of AI is not one all-knowing assistant, but an entire workforce of specialized agents working together behind the scenes? Recorded st Zendesk Relate, this episode features a fascinating conversation with Shashi Upadhyay about where enterprise AI is really heading, and why many businesses are still underestimating the scale of operational change required to make agentic AI work. Shashi explains why Zendesk views AI agents as a new form of digital labor rather than simply another software feature. Instead of building one giant general-purpose assistant, Zendesk is developing coordinated networks of specialized agents designed for specific business functions such as billing, collections, refunds, returns, employee service, and industry-specific workflows across sectors like healthcare, banking, and e-commerce. We also go behind the curtain inside Zendesk itself. Shashi shares how the company has transformed internally from a traditional seat-based SaaS business into an organization focused on measurable outcomes such as automation rates, customer satisfaction, and successful resolutions. He also discusses how AI is changing software development itself, enabling smaller engineering teams to move dramatically faster while reshaping how products are designed and built. The conversation explores some of the biggest themes emerging across the AI industry right now, including outcome-based pricing, AI trust and guardrails, resolution learning loops, embedded AI, and the growing shift toward agent-to-agent interactions where personal AI assistants may eventually negotiate directly with enterprise AI systems on behalf of consumers. We also discuss the fears many people have around jobs and automation. Rather than predicting catastrophic job loss, Shashi argues there is still enormous unmet demand for better service experiences, and that AI may ultimately allow businesses to finally deliver the level of customer experience people have wanted for years. If you're trying to understand where enterprise AI moves next after copilots and chatbots, this conversation offers a clear and thought-provoking look at the systems, workflows, and cultural shifts already reshaping the future of work.
May 20 · 39 min
Cybersecurity Upside Down With Benny Czarny, founder and CEO of OPSWAT
What if the cybersecurity industry has spent decades fighting the wrong battle? In this episode of Tech Talks Daily, I sat down with Benny Czarny, founder and CEO of OPSWAT, to discuss why he believes the traditional "detect and respond" model is no longer enough in a world where AI is accelerating cyber threats faster than security teams can react. Benny joined me to discuss his new book, Cybersecurity Upside Down, which combines personal stories from building OPSWAT with a bold argument for rethinking how organizations approach cyber defense altogether. His central belief is simple but provocative: detection-based security has trapped the industry in a losing cycle in which attackers need to succeed only once, while defenders are forced into a constant state of reaction. During our conversation, Benny explained how his thinking evolved after realizing that even layering dozens of antivirus engines and sandboxing technologies still failed to stop malicious files reliably. That realization ultimately pushed him toward a prevention-first philosophy built around Deep Content Disarm and Reconstruction, or CDR. Rather than trying to determine whether a file is malicious, the approach assumes files may already be dangerous and regenerates clean, safe versions before they ever reach users or systems. We also explored how generative AI is changing the cybersecurity landscape in ways many organizations still underestimate. Benny shared why AI is dramatically reducing the time required to create malware, weaponize exploits, and scale attacks, effectively giving even inexperienced attackers capabilities once reserved for nation states or advanced cybercriminal groups. He also raised concerns that AI data lakes could become contaminated with malicious content, creating entirely new risks for organizations rushing to deploy large language models without securing the data feeding them. One of the most fascinating aspects of the discussion was the psychology and culture within cybersecurity teams. Benny argued that the industry often celebrates visible incident response activity while undervaluing quiet prevention. In a world dominated by alerts, dashboards, and SOC metrics, truly preventing attacks can almost appear invisible, despite potentially delivering far greater security outcomes. We also talked about the sectors Benny believes are most exposed today, including energy, manufacturing, and critical infrastructure operators that still rely heavily on reactive security models while facing growing operational and regulatory complexity. He explained why some industries are advancing faster than others and why compliance mandates could become a major catalyst for broader prevention-first adoption. Beyond cybersecurity itself, this episode also offered a fascinating look into Benny's entrepreneurial journey, what he learned building OPSWAT over two decades, how AI helped him research and structure his book, and why he is now even producing a cybersecurity-focused TV series called Into the Breach, designed to make complex security concepts easier for wider audiences to understand. This conversation challenges many of the assumptions the cybersecurity industry has normalized for years. Whether you work in security, IT leadership, compliance, or want to understand how AI is reshaping digital risk, this episode offers a very different perspective on what modern cyber resilience could look like in practice.
May 19 · 26 min
Zendesk CEO Tom Eggemeier On Building The Autonomous Service Workforce
What happens when customer service stops being a department and starts becoming an autonomous operational system? Recorded live at, this conversation with Tom Eggemeier goes far beyond chatbots, copilots, and AI hype cycles. Instead, we explore why Zendesk believes the future of enterprise service will be built around what it calls an "autonomous service workforce," where AI agents, human experts, workflows, analytics, governance, and orchestration layers all work together as one continuously learning system. Tom shares how Zendesk transformed its own internal operations using AI, achieving more than 60% autonomous resolution rates while simultaneously increasing customer satisfaction. We also discuss why the company is shifting away from measuring ticket deflection and toward measuring actual resolutions, what the Forethought acquisition means for Zendesk's long-term AI strategy, and why governance, permissions, and operational trust may become more important than the AI models themselves. But this episode is about much more than software. Tom explains why he believes the next phase of enterprise AI will fundamentally reshape workflows, organizational structures, and even the role humans play inside modern businesses. We unpack the rise of specialized AI agents, why AI-to-AI interactions could soon outnumber human interactions, and why many organizations are underestimating the operational redesign required to make agentic AI work at scale. We also discuss the hidden risks of fragmented AI systems, why disconnected tools continue to drain businesses, and how companies can balance autonomy with human oversight and empathy. If you've been wondering where enterprise AI is really heading beyond the headlines, this conversation offers a fascinating look at how one of the biggest players in customer experience is attempting to redefine service itself.
May 18 · 35 min
Atlassian's Sherif Mansour On Why Context Will Define The Future Of AI
What happens when AI intelligence becomes commoditized? That is the question sitting at the heart of this episode recorded live at Team '26 in Anaheim, where I sat down with Sherif Mansour to unpack one of the biggest shifts happening in enterprise technology right now. For years, the AI conversation has focused on models, prompts, and raw capability. But according to Sherif, the real competitive advantage may no longer come from the intelligence itself. It comes from context. The workflows, relationships, decisions, knowledge, and operational history that exist inside an organization. In this conversation, Sherif takes me deep inside Atlassian's biggest AI announcements around Rovo, Teamwork Graph, AI-powered workflows, and the company's broader vision for what happens when AI moves beyond isolated copilots and starts operating across the flow of work itself. We explore why Atlassian believes organizational context is becoming the defining moat in enterprise AI, why the company is opening Teamwork Graph through MCP and external integrations, and how the industry is rapidly shifting from AI experimentation toward real operational execution. Sherif also myth busts some of the biggest misconceptions surrounding AI adoption today. We discuss the difference between automation and orchestration, why humans still remain central to decision-making, and how enterprises can avoid adding complexity while still moving quickly in the AI era. Along the way, we discuss real-world examples ranging from Formula One race strategy and procurement workflows through to AI-powered onboarding, engineering productivity, and the growing role of agentic systems inside large organizations. One of the most fascinating parts of the discussion centers around the evolution of enterprise software itself. Atlassian no longer sees AI as a standalone assistant sitting in a chat window. Instead, the vision is for AI to become deeply embedded into workflows, helping teams coordinate work, surface insights, and accelerate decision-making in real time. Sherif also shares why he believes the next major platform battle will not be over who owns the smartest AI model, but over who owns the operational context surrounding that intelligence. If you're trying to separate real enterprise AI progress from the hype cycle, this episode offers a thoughtful and refreshingly honest look at where things may actually be heading next. As always, I'd love to hear your thoughts. Is organizational context becoming the real competitive advantage in AI? And how prepared is your business for a future where humans and AI agents increasingly work side by side? Please check the partners of the Tech Tech Talks Network Learn more about the NordLayer Browser Visit Denodo.com
May 17 · 20 min
Why AI Is Still Blind to the Physical World and How Flexible Chips Could Change Everything
What if the biggest limitation holding AI back isn't the model, the data center, or the algorithm, but the fact that most physical objects in the world still cannot communicate digitally? In this episode of Tech Talks Daily, I sat down with Richard Price, CTO and co-founder of Pragmatic Semiconductor, to explore why AI systems remain "half blind" to the physical world and what happens when everyday objects finally become intelligent, connected, and verifiable data sources. Richard shared how Pragmatic Semiconductor is taking a radically different approach to chip design by creating flexible, ultra-thin semiconductors built specifically for item-level intelligence. Rather than competing directly with traditional silicon, Pragmatic is designing lightweight, low-cost electronics that can integrate directly into packaging, labels, healthcare patches, wearable devices, and products that conventional chips cannot support economically or physically. During our conversation, we unpacked why the long-promised "Internet of Everything" has remained frustratingly out of reach for so many years. Richard explained that while silicon has powered decades of incredible innovation, scaling connectivity to billions or even trillions of everyday objects introduces major cost, energy, and sustainability challenges. Pragmatic's flexible semiconductor technology aims to solve that by reducing manufacturing complexity, lowering environmental impact, and enabling intelligence directly at the edge. We also discussed how embedding intelligence at the item level could reshape supply chains, sustainability initiatives, healthcare systems, and even consumer trust. From reducing food waste through smarter logistics to enabling wearable healthcare sensors with entirely new form factors, Richard painted a picture of a future where physical products can actively communicate their identity, condition, and history in real time. One of the most fascinating parts of the conversation centered on how businesses should prepare for this shift. As edge intelligence grows, organizations may need to rethink traditional cloud-heavy architectures and start designing systems in which decisions occur closer to the object itself. Richard explained how this could reduce latency, lower energy usage, and unlock entirely new categories of connected products. We also explored the sustainability side of semiconductor manufacturing at a time when AI infrastructure and hyperscale data centers are drawing increasing scrutiny for their energy and environmental impact. Richard shared how Pragmatic's thin-film manufacturing approach uses fewer chemicals, less water, and lower-temperature processes, while opening the door to more environmentally conscious digital infrastructure. Toward the end of the episode, Richard offered insight into some of the most exciting real-world applications already emerging, including healthcare patches, wearable sensing technologies, AR and VR devices, and electronics that could eventually conform to the human body itself. It is the kind of conversation that makes you rethink what a semiconductor can actually be. If you've ever wondered what comes after smartphones and smart devices, this episode offers a fascinating look at how flexible electronics could quietly become the foundation for the next generation of connected intelligence. Useful Links Connect with Richard Price Learn More About Pragmatic Semiconductor Please check the partners of the Tech Tech Talks Network Learn more about the NordLayer Browser Visit Denodo.com
May 16 · 31 min
How Quantum-Inspired Computing Is Solving Aerospace's Biggest Challenges
What happens when an Air Force engineer with experience in intelligence, venture capital, and deep tech startups starts applying quantum-inspired computing to some of the hardest problems in aerospace and defense? In this episode of Tech Talks Daily, I sat down with Nathan Mason, VP of Strategic Growth at BQP, to unpack how quantum-inspired software is already helping organizations solve massive computational challenges without waiting years for fully mature quantum hardware. Nathan shared his fascinating career journey from military service after 9/11 through the intelligence community, business school, venture investing, and ultimately into the world of advanced simulation and optimization. He emphasized how data-driven thinking shaped his approach to high-stakes decision making and why gut instinct alone no longer suffices in an era driven by AI, complex systems, and operational risk. His insights provide valuable guidance for those interested in careers at the intersection of tech and aerospace. We also explored a question many business leaders are asking right now: what does "quantum in practice" actually look like today? Nathan explained how BQP is applying quantum-inspired approaches on existing CPUs and GPUs to improve simulation accuracy, accelerate modeling workloads, and help aerospace organizations make faster, smarter engineering decisions without simply throwing more hardware at the problem. This shows the tangible progress already happening, inspiring the audience with real-world impact. The discussion also tackled the commercial realities behind deep tech innovation. Nathan spoke candidly about the funding challenges facing startups working in quantum and defense technologies, emphasizing that moving beyond theory into operational deployment is difficult but achievable. This perspective encourages the audience to see obstacles as opportunities for innovation and persistence. Toward the end of the episode, Nathan shared thoughtful advice for students, engineers, and professionals looking to build careers in AI, aerospace, quantum, and defense. His message was simple but powerful: stay curious, keep learning, and never underestimate how a single conversation can completely change your career trajectory. If you've ever wondered how quantum computing moves from science fiction headlines into real-world business value, this episode offers a practical and honest perspective on how quantum-inspired software is already making a difference in aerospace and defense industries today. Useful Links Connect with Nathan Mason on LinkedIn Learn More about BQP Please check the partners of the Tech Tech Talks Network Learn more about the NordLayer Browser Visit Denodo.com