Tech Talks Daily Podcast

When we talk about the future of IT services, the conversation often revolves around the potential of AI and automation. But what does that really mean when applied at scale, across legacy infrastructure, evolving customer expectations, and real-world operational challenges?

In todays episode, I sat down with Manish Tandon, CEO of Zensar Technologies, to explore that very question. What emerged was a refreshingly pragmatic take on a space often overwhelmed by buzzwords.

Manish leads a global organisation that's helping some of the UKs biggest businesses not just integrate AI, but rethink the foundation of their IT strategies. We discussed how Zensar is combining automation with a philosophy they call experience-led everything, a human-centric approach that puts users, not systems, at the centre of transformation. Through this lens, he explained how seemingly simple shifts like applying AI to reduce technical debt or drive internal engagement can lead to significant performance gains and improved outcomes across entire organisations.

What I found particularly powerful was how Manish challenges the language around AI. He sees todays wave of generative and agentic AI as an evolution of long-standing automation principles, not a reinvention. That mindset is helping clients cut through the noise and focus on impact, such as faster delivery cycles, measurable productivity boosts, and tools that empower rather than replace human potential.

We also touched on the ethical implications of AI, the nuances of implementation across different geographies, and the value of responsible AI governance at the application level, not just in principle. If your business is looking to adopt AI in a way that scales sensibly while delivering lasting value, this episode offers insights you wont want to miss.

So how are you preparing to balance automation with empathy in your IT strategy, and are you building for systems or for people?

What happens when automation grows and learns to think, reason, and adapt? That is precisely what I explored in today's episode with Kumar Bennet, Executive Vice President and Global Head of Business Process Services at Hexaware Technologies. As the enterprise world braces for rapid AI-driven change, Bennet joined me to unpack how agentic AI quietly transforms customer experience from the ground up.

Bennet explains how agentic AI is fundamentally different from earlier forms of automation. We go beyond the buzzwords to explore how these intelligent systems retain business context, plan and execute tasks with autonomy, and collaborate with other agents to deliver meaningful outcomes. This isn't just a new toolset for organizations focused on ROI, customer satisfaction, and operational efficiency. It is a new way of working.

One of the most compelling parts of our conversation centered around AI-powered voice translation. Bennet clearly shows what happens when language ceases to be a barrier. Service agents are no longer required to be fluent in dozens of languages. Instead, they can focus on empathy, listening, and resolution while AI handles translation in real time. We also explore how these technologies reduce stress on customer service staff, giving them more meaningful roles and the tools to thrive.

Of course, no digital transformation is complete without understanding the people behind it. Bennet shares thoughtful insights on change management, addressing customer trust and employee concerns. We discuss how AI can empower rather than replace, and why organizations must be intentional about communication, leadership development, and cultural shift.

From multilingual support to hyper-personalized customer journeys, and AI assistants to back-end process orchestration, agentic AI is no longer a future concept. It is already here. But are enterprises prepared for a world where customers and AI agents interact seamlessly, at scale, daily?

What does the rise of intelligent agents mean for your business?

What happens when access to advanced AI models is no longer the real differentiator, and the true advantage lies in how businesses leverage their own data?

At the AWS Summit in London, I sat down with Rahul Pathak, Vice President of Data and AI Go-to-Market at AWS, to unpack this question and explore how organisations are moving beyond experimentation and into large-scale generative AI adoption.

Recorded live on the show floor, this conversation explores how AWS is supporting customers at every layer of their AI journey. From custom silicon innovations like Trainium and Inferentia to scalable services like Bedrock, Q Developer, and SageMaker, AWS is giving businesses the infrastructure, tools, and flexibility to innovate with confidence.

Rahul shared how leading organisations such as BT Group, SAP, and Lonely Planet are already applying these tools to reduce costs, speed up development cycles, and deliver tailored experiences that would have been unthinkable just a few years ago.

A key theme that emerged in our discussion is that data, not just models, is the true foundation of effective AI. Rahul explained why unifying data across silos is critical and how AWS is helping companies create more intelligent applications by connecting what they uniquely know about their business to powerful AI capabilities.

We also addressed the operational realities of AI deployment. From moving proof-of-concept projects into production to meeting the growing demand for responsible AI, the challenges are shifting. Organisations are now focused on trust, security, transparency, and measurable value.

If you're leading digital transformation and wondering how to scale AI solutions that deliver on business outcomes, this episode provides practical insight from someone at the center of the industry. How will your business stand out in a world where every company has access to AI models, but only a few know how to apply them with purpose?

In todays episode of Tech Talks Daily, I sit down with Christian Reilly, Field CTO for EMEA at Cloudflare, the Connectivity Cloud company, to examine the latest findings from their cybersecurity research and what they reveal about how prepared different industries really are.

While sectors like IT, gaming, and financial services have seen a higher volume of cyberattacks, they also report greater readiness and resilience.

In contrast, industries like education and healthcare, although less frequently targeted, remain far less prepared to defend against growing threats. This gap raises important questions about how organizations approach security depending on their legacy systems, revenue models, and digital maturity.

Christian brings years of frontline experience to the discussion and shares actionable insights into how companies can build cybersecurity strategies that not only protect but also improve performance.

From the shift toward zero trust architecture to the critical role of board-level engagement, we explore how forward-thinking organizations are rethinking the role of cybersecurity in modern digital operations. He explains why simplicity often beats complexity, and how reducing friction for end users is key to long-term resilience.

We also look ahead to some of the key trends shaping the future of security. Christian dives into the challenges posed by emerging technologies such as quantum computing, AI, and the explosion of data generated by IoT and smart infrastructure. He stresses the importance of preparing now for scenarios like Harvest Now, Decrypt Later, and why organizations need to begin thinking seriously about post-quantum cryptography.

On the human side, Christian outlines what effective training looks like today and how to shift employee culture from compliance to awareness.

If you're wondering how to stay one step ahead of evolving threats, this conversation offers a wealth of insight from the heart of the Connectivity Cloud. How is your organization preparing for whats coming next?

In today's episode of Tech Talks Daily, I reconnect with Abnormal AI's CIO, Mike Britton, to explore one of the most pressing topics in the tech world—AI regulation and cybersecurity.

 Speaking from his base near Dallas, Mike brings a pragmatic perspective shaped by decades of experience at the intersection of enterprise technology and security. As the debate around artificial intelligence evolves, we examine the growing divide between the United States and Europe on regulatory approaches and what business leaders can learn from each side.

While Europe takes a more cohesive, application-based approach, the US remains fragmented, relying on state-by-state policies and sector-specific laws. Mike unpacks why this patchwork complicates global alignment and what an effective risk-based, standardized framework might look like. He argues that regulation must focus on how AI is applied, not just its scale, especially as the technology becomes embedded in everything from healthcare to email automation.

We also touch on the unintended consequences of overregulation, including the risk of pushing innovation into regions with fewer safeguards. As Abnormal Security works with some of the world's largest brands, Mike offers a frontline view into how threat actors are already leveraging AI to outpace traditional defenses. His insights reinforce the need for transparency, human oversight, and "kill switches" to ensure AI remains a tool for good, not a liability.

From real-world examples to strategic recommendations, Mike outlines what CIOs and CISOs need to know now. His advice is clear, grounded, and actionable, whether embracing regulatory sandboxes, staying alert to geopolitical nuances in AI models, or maintaining continuous learning in a fast-moving space.

So, how do we keep innovation ethical and secure in a world where AI is moving faster than ever? And what steps should technology leaders take to avoid falling behind or losing control of the tools meant to drive progress?