Tech Talks Daily

How many bad customer experiences does it take before someone walks away for good? In my conversation with Amitha Pulijala, we explore why the answer might be fewer than most businesses are prepared for, and what that means for anyone investing in AI-powered customer experience.
New research from Cyara reveals a stark reality. Twenty-eight percent of consumers will abandon a brand after just one poor interaction, and nearly half will do the same after only two or three. That leaves very little room for error at a time when more organizations are introducing AI into customer journeys, often at speed and at scale.
Amitha, who leads product strategy in the AI and CX space, brings a grounded perspective shaped by years of working with large enterprises and complex contact center environments. What stood out in our discussion is how the real challenge is no longer about whether AI can handle customer interactions. In many cases, it already can. The issue is whether customers trust it enough to let it try.
We unpack the growing perception gap: 73 percent of consumers still believe human agents resolve issues faster, even though AI systems can deliver near-instant responses. That disconnect often comes down to past experiences, from bots that fail to understand context to systems that trap users in frustrating loops with no clear way out.
There is also a clear line that customers draw around where AI belongs.
Routine, high-volume tasks such as password resets or appointment confirmations are widely accepted. But when conversations shift toward financial security, healthcare, or legal advice, expectations change. People want human judgment involved and reassurance that the outcome is reliable.
What makes this conversation particularly relevant is the generational divide shaping expectations. Younger users are far more open to AI-led interactions, provided they work seamlessly. Older generations remain more cautious, often preferring the certainty of speaking with a human. That creates a design challenge for businesses trying to serve everyone without alienating anyone.
Throughout the episode, Amitha emphasizes that trust is built through experience, not intention. That means testing AI systems in real-world conditions, monitoring how they perform over time, and ensuring that when things do go wrong, the transition to a human feels smooth and informed rather than abrupt and frustrating.
This is not a conversation about replacing humans with machines. It is about understanding where AI can add speed and efficiency, where it should support human agents, and where it should step back entirely. The organizations getting this balance right are not the ones deploying AI the fastest, but the ones validating it most carefully before customers ever see it.
As businesses race to embed AI at every touchpoint, a bigger question emerges. Are we building systems that customers actually trust, or are we creating new points of friction that push them away?
 
Useful Links
Connect with Amitha on LinkedIn
Survey Data
Cyara Website
Follow Cyara on LinkedIn

What does it really take to move AI from endless experimentation into something that creates real business value? In this episode, I sat down with Tom Alexander, Head of Innovation and Transformation at CrossCountry Consulting, to talk about why so many organizations still struggle to turn AI ambition into meaningful outcomes.
Tom works closely with executive and CFO teams that are either unsure where to begin or frustrated that early AI efforts have not delivered what they hoped for. We talked about why this is rarely just a technology issue. In many cases, the real blockers are ownership, change management, weak alignment across the business, and a failure to connect AI initiatives to the problems that matter most.
One of the big themes in our conversation was the need to treat AI as an enterprise-wide program rather than a collection of isolated tools. Tom shared how leaders can focus on business processes first, identify where automation can genuinely improve performance, and avoid getting distracted by hype. We also unpacked the growing accountability challenge around AI, including who should own it, how stakeholders can align, and why strong foundations in data, governance, and training matter so much.
This episode is packed with practical takeaways for anyone trying to make sense of AI adoption inside a business. If you are trying to figure out where to start, how to scale, or how to avoid another stalled initiative, there is a lot in here for you. After listening, I would love to hear your thoughts. How is your organization approaching AI, and where do you think most businesses are still getting it wrong?
Useful Links
CrossCountry website
Connect with Tom Alexander on LinkedIn
Field Notes podcast

Is the endpoint still just a device, or has it quietly become one of the most important control points in modern enterprise security?
Recording live from IGEL Now And Next in Miami, I sat down once again with Darren Fields for what has become an annual check-in on how fast the industry is really changing. And this time, the conversation feels very different.
Over the last 12 months, the discussion has moved well beyond traditional endpoint management. From global supply chain pressure driven by AI demand to rising hardware costs and unpredictable refresh cycles, the assumptions that once shaped endpoint strategy are starting to fall apart. Darren shares how organizations are now being forced into difficult decisions, absorb rising costs, delay investment, or rethink the model entirely.
We also explore how that shift is changing the conversation at the leadership level. What was once seen as a procurement decision is increasingly being reframed as a resilience strategy. Extending hardware life, reducing dependency on supply chains, and maintaining operational continuity are becoming just as important as performance and cost.
Security, of course, sits at the center of it all. With the majority of breaches still originating at the endpoint, Darren highlights how organizations are starting to rethink where they focus their efforts. Rather than focusing solely on data centers and cloud environments, there is growing recognition that control, visibility, and enforcement must occur at the edge.
The conversation also touches on the reality of modern cyber threats. From constant attack attempts to incidents that leave organizations offline for weeks, the challenge is no longer just restoring systems but restoring access. And that shift has major implications for how recovery and continuity are designed moving forward.
We also look at the growing convergence of IT and OT, the role of contextual access, and the balancing act between stronger security and user experience. With organizations at very different stages of their journey, there is no single path forward, but there is a clear sense that change is already underway.
So as the pace of technology, risk, and demand continues to accelerate, one question remains. Are organizations adapting fast enough, or are they still relying on models that no longer reflect the world they are operating in?
What do you think, are we finally seeing a shift toward treating the endpoint as a strategic priority, or is there still a gap between awareness and action?

What does it really take to move from talking about Zero Trust… to actually making it work in the real world?
Recording live from IGEL Now And Next in Miami, I caught up with John Walsh for what has now become something of a tradition, our third conversation together, and one that reflects just how much has changed in the last 12 months.
When we last spoke, the focus was on securing the edge and rethinking security through a preventative lens. This time, the conversation has expanded from IT to OT, from devices to platforms, and from theory to real-world implementation across manufacturing floors, healthcare environments, and government organizations.
John shared how IGEL is increasingly being adopted as a global standard across both IT and operational environments, bringing new challenges and new insights. From kiosks and signage on factory floors to shared workstations in hospitals, the need for persona-based and now context-aware access is becoming far more than a technical concept. It is shaping how organizations think about identity, risk, and control at scale.
We also explored how the idea of the "adaptive secure desktop" is evolving beyond traditional VDI thinking. Instead of static devices, the focus is shifting toward environments that respond dynamically to the user, their role, their location, and the level of risk in that moment. It raises an important question. How do you deliver that level of control without introducing friction for the user?
AI inevitably entered the conversation, but not in the way many might expect. Rather than focusing on features, John highlighted the acceleration of threat velocity. The time between vulnerability discovery and exploitation is shrinking rapidly, and with AI amplifying that speed, traditional detection and response models are struggling to keep up. The implication is clear. Security strategies need to shift toward prevention and control, not just reaction.
We also touched on emerging challenges around agentic AI, non-human identities, and the need to apply Zero Trust principles beyond people to machines. As organizations begin to explore these new models, questions around identity, access, and guardrails are becoming more complex and more urgent.
And throughout the conversation, one theme kept coming back and reducing complexity while increasing control. Whether it is through immutable operating systems, centralized policy enforcement, or contextual access, the goal is to simplify the environment while strengthening security outcomes.
As organizations continue their journey toward modernization, one question remains: Are we still layering new technology onto old models, or are we ready to rethink how access, identity, and control are delivered from the ground up?
What do you think, is Zero Trust finally becoming real at the endpoint, or is there still a gap between strategy and execution?

How long would it actually take your organization to recover every endpoint after a major cyber incident?
Recording live from IGEL Now And Next in Miami, I sat down with James Millington to explore a question that most businesses think they've answered, but rarely have. Because when you move beyond theory and start mapping out the real process, the numbers tell a very different story.
James shared examples from real organizations that tried to calculate recovery at scale. One estimated it would take over 5,000 person-hours to rebuild their estate. Another believed they could recover quickly, until they realized the scale of their environment made that assumption unrealistic. It raises a deeper question. Are we focusing too much on recovery and not enough on resilience? 
The conversation quickly moved into what James calls the "endpoint recovery gap." While most organizations have invested heavily in data center resilience, failover environments, and backup strategies, far fewer have a clear plan for reconnecting users when endpoints are compromised. And without a working endpoint, even the most advanced infrastructure becomes inaccessible. 
We also explored why so many organizations continue to rely on reimaging devices as a primary recovery strategy, despite the time, complexity, and operational disruption it creates. In many cases, it's not just slow. It's impractical at scale. And perhaps more concerning, some organizations still admit to having no defined plan at all.
One of the most memorable moments in the conversation came through a simple analogy. For years, we've been carrying the weight of outdated endpoint strategies, even though the solution has been sitting in front of us. Just like it took thousands of years to put wheels on a suitcase, the shift toward simpler, more resilient models often requires a moment of realization before change actually happens.
As application delivery continues to move toward SaaS, DaaS, and cloud environments, the role of the endpoint is also being redefined. Analysts are now calling for a move toward immutable, non-persistent endpoints that reduce attack surface and enable faster recovery. But as James points out, the real challenge is not awareness. It's an action.
As organizations continue to invest in security, infrastructure, and AI, one question remains: Are we still planning for recovery from failure, or are we finally designing systems that avoid it in the first place?
What do you think, are businesses ready to rethink endpoint strategy, or are we still carrying the baggage of the past?