Tech Talks Daily

At Google Cloud Next in Las Vegas, I sat down with Granville Valentine to talk about one of the biggest shifts happening in business technology right now, the move from isolated AI experiments to orchestrated, production-scale agentic systems.

Granville leads Google Cloud's AI Go-to-Market organization across North America, working directly with major enterprises on adopting Gemini, customer experience AI, and multi-agent workflows. That puts him right at the center of how businesses are actually deploying AI in the real world, and where many are still getting stuck.

In this conversation, we explore why so many companies discovered in 2025 that standalone chatbots were failing to deliver measurable ROI, and how orchestration-based AI systems are changing that. Granville explains why the future belongs to multi-agent workflows built around business outcomes rather than technology demos, with different agents collaborating around customer experience, commerce, upselling, support, and personalization.

We also discuss the rise of proactive "digital concierges" that unify search, commerce, maps, personalization, and customer service into a single intelligent journey rather than the fragmented app experiences consumers are used to today. Granville shares practical examples from companies like The Home Depot and explains how businesses are using Gemini Enterprise for Customer Experience to create more natural and effective customer interactions.

Another major theme in this episode is data. We explore how cross-cloud connectivity and universal context engines are helping organizations query data across multiple cloud environments without moving everything into a single platform first, dramatically reducing friction for companies trying to build agentic workforces.

The conversation also touches on generative media, from video and image creation to interactive shopping experiences, and how businesses are using these tools to drive real engagement, customer retention, and revenue growth rather than simply producing flashy content.

Most importantly, this episode cuts through the hype and focuses on execution. Granville explains why businesses need to stop thinking about AI as a standalone feature and start thinking about it as an operating model built around outcomes, experimentation, and continuous learning.

Are businesses finally ready to move from AI experimentation to the agentic enterprise?

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What happens when AI growth collides with the physical limits of power, materials, and global supply chains?

In this episode of Tech Talks Daily, I speak with Matt Kelly, CTO and Vice President of Technology and Standards at the Global Electronics Association, about the growing pressure on AI infrastructure and the supply chains that support it.

Drawing on insights from thousands of member organizations across manufacturing, automotive, and electronics, Matt offers a practical look at what business and technology leaders should really be preparing for in 2026 and beyond.

Our conversation begins with the shift from cost optimization to resilience and system-level performance. Matt explains why the old procurement mindset of chasing the lowest-cost supplier is rapidly being replaced by what he calls confidence-based sourcing. In a world shaped by geopolitical disruption, pandemic aftershocks, and surging demand for AI, organizations are discovering that cheap sourcing means little if critical components fail to arrive on time.

We also discuss why dual sourcing has evolved from a procurement strategy into a business continuity requirement. Matt shares real-world examples of how something as small as a missing capacitor can prevent the delivery of million-dollar AI infrastructure systems. That single point of failure has pushed resilience metrics such as recovery time, geographic diversity, and validated backup suppliers into boardroom discussions. Another major focus of the episode centers on AI infrastructure itself.

While many conversations around AI focus on software models and automation, Matt argues that the true bottleneck may soon become power availability. From server cooling and energy consumption to sustainable hardware design and material shortages, the industry now faces challenges that stretch far beyond compute performance alone. Matt also explains why fully localized supply chains remain unrealistic for the electronics industry. Instead, he advocates for a balanced model that combines trusted global partnerships with strategic regional sourcing for critical components and security-sensitive technologies.

One of the strongest takeaways from this conversation is that AI infrastructure must now be approached as a system problem. Silicon design, packaging, thermal management, power delivery, sustainability, and supply chain strategy cannot be treated as separate conversations.

As organizations race to scale AI capabilities over the next few years, are business leaders truly prepared for the infrastructure realities sitting behind the AI boom, or are we about to discover that resilience and energy matter just as much as innovation itself?

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What happens when the pace of AI innovation collides with the realities of semiconductor development?

In this episode of Tech Talks Daily, I speak with Faraj Aalaei, CEO of Cognichip and a semiconductor industry veteran with more than 25 years of experience spanning engineering, venture capital, and two successful IPOs. Faraj joins me to discuss why the future of artificial intelligence may depend on radically rethinking how chips are designed, manufactured, and scaled.

Cognichip is developing the world's first Artificial Chip Intelligence (ACI®) to reimagine chip design. Founded by experts from Amazon, Google, Apple, Aquantia, Synopsys, and KLA, the company tackles high cost and inaccessibility in chip development, enabling hardware to evolve as quickly as software innovation.

Backed by $93 million in total funding from Seligman Ventures, SBI Investment, Mayfield, Lux Capital, and Candou Ventures, Cognichip's ACI® reduces design cycles by 50%, cuts development costs by 75%, and optimizes power, performance, and efficiency. ACI® accelerates innovation and broadens access to semiconductor technology by making it easier, more affordable, and accessible to a broader range of innovators

Faraj explains how the semiconductor industry now faces a growing bottleneck. While AI software can evolve at remarkable speed, chip development often still takes between three and five years and costs more than $100 million. That mismatch is becoming increasingly difficult to sustain as demand grows for specialized AI hardware, edge computing systems, and next-generation infrastructure.

Our conversation also explores the geopolitical and economic shifts reshaping the semiconductor industry. Faraj shares his perspective on the emerging concept of "Pax Silica," the growing effort by governments to restructure global chip supply chains and reduce reliance on China. While many policymakers see this as a matter of national security and resilience, Faraj warns there may also be unintended consequences, including rising AI infrastructure costs, engineering shortages, and slower innovation cycles.

One of the most interesting parts of our discussion centers on the idea that AI itself may become the missing scaling factor for semiconductor development. Instead of relying solely on larger engineering teams and longer development cycles, Cognichip believes AI-designed chips could dramatically accelerate innovation and make advanced hardware development accessible to far more companies and researchers.

Faraj also reflects on his career journey from entrepreneur to investor and back again, sharing lessons from decades spent helping build the modern semiconductor ecosystem. From supply chain realities to the growing pressure on engineering talent, this episode offers a rare insider perspective on the technologies quietly powering the entire AI economy.

As AI systems continue to demand faster, more specialized hardware, are we reaching the limits of traditional chip development, and could AI itself become the tool that reshapes the future of semiconductors?

What happens when a country moves from cash-only transactions to instant digital payments that work for everyone?

In this episode of Tech Talks Daily, I sit down with Steve Haley, Director of Market Development at The Mojaloop Foundation, to discuss how open and interoperable payment systems are helping reshape financial inclusion across Africa and other emerging markets.

For many listeners in Europe or North America, instant payments and digital banking are often taken for granted. But Steve explains how millions of people around the world still live in economies where cash dominates daily life, and where even those with mobile money accounts remain disconnected from the wider financial system. In some countries, people have even been forced to carry two phones because competing mobile payment providers could not communicate with each other.

Our conversation focuses heavily on Liberia, where the Liberian Inclusive Instant Payments System was deployed in just 73 business days. Built using Mojaloop technology in partnership with the Central Bank of Liberia, ThitsaWorks, and AfricaNenda, the system now allows interoperable mobile money transfers between major operators, including MTN and Orange Liberia.

Steve shares why this matters far beyond convenience. Removing barriers between providers means people no longer need money trapped across separate accounts, merchants can accept digital payments more easily, and governments can distribute payroll and public payments through faster and more transparent systems.

We also discuss how mobile wallets are helping expand account ownership across Liberia, which now exceeds 50 percent according to World Bank data, and why interoperability may become the missing piece that transforms access into meaningful financial participation.

Another fascinating part of our discussion centers on the future of cross-border payments in Africa. Steve explains how many transactions between neighboring African countries still route through systems in the United States, increasing both cost and complexity. He believes interoperable instant payment systems across the continent could dramatically lower those barriers and unlock new levels of regional trade.

This episode offers a thoughtful reminder that digital transformation is not always about the latest AI model or enterprise software platform. Sometimes it is about giving people the ability to send money, pay merchants, receive salaries, and participate in the economy with the same ease many of us already expect every day.

So how different would life feel if digital payments finally became accessible to everyone, regardless of where they live or who they bank with?

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• Learn more about the NordLayer Browser
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How do AI agents safely access the data they need without exposing the business to risk?

In this episode, I speak with Alex Gallego, CEO and founder of Redpanda, about why streaming data is becoming such an important foundation for enterprise AI. Redpanda began as a high-performance streaming data platform, but the company is now building what it calls the Agentic Data Plane, a governed access layer designed to connect AI agents with enterprise data and systems.

Alex shares the story behind Redpanda's journey, from solving a personal engineering frustration to powering mission-grade systems for some of the world's largest organizations. We discuss why many enterprises are racing toward agentic AI while still lacking the permissions, controls, context, and observability needed to make agents safe in production.

One of the standout moments in our conversation is Alex's comparison between hiring AI agents and forgetting to onboard them. Businesses are deploying accounting agents, coding agents, customer success agents, and security agents, yet many still lack a reliable way to decide what those agents can access, what actions they can take, and how to prove what happened when something goes wrong.

We also talk about explainability, agent transcripts, and why enterprises need a full record of agent behavior across complex chains of activity. Alex explains how this matters in regulated sectors such as banking, where organizations may need to prove that an AI agent is acting helpfully and responsibly, and in manufacturing, where a faulty agent action could affect months of production.

Alex also shares Redpanda's work with NVIDIA Vera, where benchmarks showed 5.5 times lower latency and 73% higher throughput. For business leaders, that means faster systems, lower costs, better customer experiences, and the ability to monitor agent behavior in real time.

This conversation is a practical look at what enterprise AI needs next.

Speed matters, but governance, trust, and control may decide which companies can move AI agents from experiments into real operations. So, are we ready to give AI agents access to the enterprise, or do we first need to learn how to manage them like part of the workforce?

Please check the partners of the Tech Tech Talks Network

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• Visit Denodo.com

What happens when AI moves beyond experimentation and becomes part of the creative process itself?

At Google Cloud Next in Las Vegas, I sat down with Albert Lai to explore how AI is transforming the media and entertainment industry from content creation and production to personalization, localization, and audience engagement.

Albert works across Google Cloud, Google, and the wider Alphabet ecosystem to help media organizations rethink how they create and distribute content using cloud infrastructure, multimodal AI, and agentic workflows. And one thing became very clear in this conversation, the industry has moved beyond asking "What if?" and is now firmly focused on production-scale execution and measurable business outcomes.

We discuss why media companies are fighting a growing battle for audience attention, and how AI is helping them create content more efficiently while also unlocking the value hidden inside vast archives of existing material. Albert explains why the conversation has shifted from simply producing more content to maximizing what already exists, and how AI is helping organizations rediscover and reimagine decades of footage, audio, and intellectual property.

The conversation also explores one of the biggest themes emerging at both Google Cloud Next and NAB Show, the rise of agentic AI workflows. Albert shares how media companies are using orchestrated AI systems to streamline complex production processes, support editors and creators inside existing workflows, and improve everything from localization and dubbing to monetization and personalization.

We also dive into real-world examples, including how companies like Avid Technology are integrating Google AI directly into production environments, and how Indonesian media company MTech used Google Cloud AI tools to create and distribute a 26-episode animated series with measurable improvements in production speed, cost efficiency, and audience engagement.

This is not a conversation about replacing creativity. It is about augmenting it.

If you work in media, content, streaming, sports, publishing, or simply want to understand how AI is changing storytelling itself, this episode is packed with practical insight and real-world examples.

How will AI change the stories we create, and the way audiences experience them?

Useful Links

• Connect with Albert, Lai
• Google Cloud Next 26

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What does real ROI from AI and analytics actually look like in the fast-food industry?

At SAS Innovate, I sat down with David Gardner, Senior Director of Analytics at Boddie-Noell Enterprises, the largest franchise operator of Hardee's in the United States, to explore how a 60-year-old family business is transforming itself through data, forecasting, and AI. This is a company processing around 40 million transactional records every single day across more than 300 restaurants, where even shaving a few seconds off a drive-thru experience can have a measurable impact on customer satisfaction and revenue.

What makes this conversation so interesting is how grounded it is in operational reality. David shares how the company moved from relying on spreadsheets, summarized reports, and gut instinct toward real-time analytics powered by SAS. One of the standout stories involves extending breakfast hours. Operational teams initially resisted the idea, convinced it would create chaos in the kitchen. But once David dug into the transactional data, the numbers told a very different story. Breakfast sales during the extended hours were growing dramatically, proving the demand was real and helping the business make a decision based on evidence rather than instinct.

We also discuss how analytics is helping optimize labor scheduling, forecasting, payroll, inventory planning, and customer throughput at scale. David explains how his team can now analyze profitability hour by hour for every restaurant in the business, helping local managers make faster and more informed decisions. With forecasting accuracy improving to within fractions of a percentage point, the business can plan more effectively in an industry facing inflation, labor pressures, delivery app disruption, and shifting customer habits.

Another major theme is accessibility. David talks about the importance of data democratization and making analytics understandable for non-technical teams. Restaurant managers are not data scientists, and they should not need to be. The goal is to put insights directly into their hands in a way that is simple, actionable, and easy to understand. AI is now becoming part of that journey too, acting as what David describes as a mentor for newer managers, helping them identify opportunities, improve operations, and get up to speed faster.

We also explore how customer behavior has changed dramatically with the rise of delivery platforms like DoorDash and Uber Eats, creating entirely different purchasing patterns compared to traditional in-store diners. Through analytics, the company can better understand those differences and optimize everything from promotions to staffing and menu strategy.

What stood out most to me is that this is not a story about flashy AI demos or abstract transformation projects. It is about using analytics to solve practical business problems in real time while quietly improving the customer experience behind the scenes.

Because at the end of the day, customers do not care about dashboards or machine learning models. They care about getting good food quickly, accurately, and consistently. The technology only matters if it helps deliver that outcome.

So as businesses continue chasing AI opportunities, are they focusing on the use cases that actually move the needle, or getting distracted by the hype?

Useful Links

• Connect with David Gardner
• Learn More About Boddie-Noell Ent.
• Catchup With What You Missed at Google Cloud Next

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• Denodo
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What happens when the excitement around AI collides with the reality of deploying it inside a business?

At SAS Innovate, that question came up repeatedly, and in this episode, I sit down with Manisha Khanna, global product marketing lead for AI at SAS, to unpack why so many organizations are still struggling to move from AI pilots to meaningful business outcomes. While headlines continue to celebrate the rapid rise of generative AI and agentic systems, Manisha brings a far more practical perspective shaped by working directly with enterprises trying to operationalize AI at scale.

One of the most striking parts of our conversation centers on why AI projects continue to stall. According to Manisha, the biggest problems are not weak models or lack of ambition. Instead, organizations are running into unpredictable inference costs, operational complexity, governance challenges, and internal resistance to change. She explains why many companies still approach AI as a technology purchase rather than a transformation strategy, and why governance built in from the beginning can actually accelerate adoption rather than slow it down.

We also spend time exploring what agentic AI really means beyond the hype. Manisha shares why SAS chose supply chain as the launch point for its first industry-packaged agent and how agentic systems differ from copilots by acting more like coworkers than assistants. Rather than simply providing recommendations, these systems can actively participate in business workflows, helping organizations move from monthly optimization cycles to near real-time decision-making.

Another major theme is the growing importance of governance and accountability. As organizations deploy AI into regulated industries and customer-facing environments, the focus is shifting away from "whose model is best" toward "who is deploying the best use cases responsibly." Manisha explains why governing the use case itself matters more than obsessing over model benchmarks, and why companies that bolt governance on afterward create friction for themselves later.

The conversation also touches on where AI is already delivering measurable value today. From customer complaint management in banking to aircraft maintenance support systems powered by retrieval-augmented generation, we discuss how organizations are seeing success when AI augments existing workflows rather than attempting wholesale disruption overnight.

What stood out most for me is how often the human side of AI came back into focus. Manisha repeatedly emphasized that leadership communication, employee trust, and organizational readiness are just as important as the technology itself. If leaders position AI purely as a cost-cutting tool, fear and resistance follow. But when AI is framed as a way to empower people and improve outcomes, adoption becomes much easier.

As organizations continue to implement AI and agentic systems, the biggest question is no longer whether the technology works, but whether businesses are ready to lay the foundations needed to make it succeed.

Useful Links

• Connect with Manisha Khanna
• SAS Blog
• SAS Innovate

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• Denodo

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What happens when cybercrime becomes as easy to access as a subscription service, and what does that mean for every business connected to the internet today?

In this episode, I sit down with SentinelOne AI and Cloud Security Evangelist Chris Hosking to unpack a shift that feels both inevitable and deeply unsettling. The rise of what Chris describes as an AI threat market is changing the rules of engagement.

Cybercrime is no longer limited to highly skilled operators working in isolation. Instead, it has evolved into a thriving ecosystem where tools, services, and even AI-powered attack kits are bought and sold with alarming ease. As Chris explains during our conversation, "cyber crime is quite an ecosystem… the dark web has always been a place for cyber criminals to meet and to sell their wares."

We explore how AI has accelerated this shift, lowering the barrier to entry to the point where attacks can be launched for as little as £35. That democratization of cybercrime is already having real-world consequences.

Chris shares how individuals without deep technical expertise are now able to orchestrate sophisticated attacks using AI assistance, and why that surge in accessibility is driving both the volume and impact of cyber incidents. It also reframes a common misconception. Smaller businesses are not flying under the radar.

In fact, many are being targeted precisely because of weaker defenses, with attacks increasingly automated and opportunistic. The conversation also moves into more complex territory, where organized cybercrime and nation-state activity begin to overlap.

Chris highlights how governments and criminal groups are drawing from the same AI marketplaces, blurring the lines between financial motivation and geopolitical intent. The implications stretch far beyond corporate risk, touching on critical infrastructure and everyday services that people rely on. It raises a difficult question about preparedness in a world where attacks are faster, more frequent, and harder to predict.

At the same time, there is a practical thread running through this discussion. Chris challenges the instinct to immediately invest in more tools and instead encourages leaders to look inward first.

From improving basic security hygiene to using AI to reduce manual workload and noise, there are tangible steps organizations can take right now. The goal is not perfection, but resilience in an environment where, as Chris points out, incidents are becoming a regular occurrence rather than a rare event.

This episode offers a clear-eyed look at where cybersecurity is heading, without the hype or fear-driven narratives. It is a conversation about scale, speed, and the uncomfortable reality that the threat landscape has changed in ways many organizations are still catching up with.

So as AI continues to reshape both innovation and risk, how prepared is your organization for a world where anyone can launch an attack with a few prompts and a subscription?

Useful Links

• SentinalOne Blog
• Connect with Chris Hosking

Please check the partners of the Tech Tech Talks Network

• Denodo

• Learn more about the NordLayer Browser

What happens when cybercrime becomes as easy to access as a subscription service, and what does that mean for every business connected to the internet today?

In this episode, I sit down with SentinelOne AI and Cloud Security Evangelist Chris Hosking to unpack a shift that feels both inevitable and deeply unsettling. The rise of what Chris describes as an AI threat market is changing the rules of engagement.

Cybercrime is no longer limited to highly skilled operators working in isolation. Instead, it has evolved into a thriving ecosystem where tools, services, and even AI-powered attack kits are bought and sold with alarming ease. As Chris explains during our conversation, "cyber crime is quite an ecosystem… the dark web has always been a place for cyber criminals to meet and to sell their wares."

We explore how AI has accelerated this shift, lowering the barrier to entry to the point where attacks can be launched for as little as £35. That democratization of cybercrime is already having real-world consequences.

Chris shares how individuals without deep technical expertise are now able to orchestrate sophisticated attacks using AI assistance, and why that surge in accessibility is driving both the volume and impact of cyber incidents. It also reframes a common misconception. Smaller businesses are not flying under the radar.

In fact, many are being targeted precisely because of weaker defenses, with attacks increasingly automated and opportunistic. The conversation also moves into more complex territory, where organized cybercrime and nation-state activity begin to overlap.

Chris highlights how governments and criminal groups are drawing from the same AI marketplaces, blurring the lines between financial motivation and geopolitical intent. The implications stretch far beyond corporate risk, touching on critical infrastructure and everyday services that people rely on. It raises a difficult question about preparedness in a world where attacks are faster, more frequent, and harder to predict.

At the same time, there is a practical thread running through this discussion. Chris challenges the instinct to immediately invest in more tools and instead encourages leaders to look inward first.

From improving basic security hygiene to using AI to reduce manual workload and noise, there are tangible steps organizations can take right now. The goal is not perfection, but resilience in an environment where, as Chris points out, incidents are becoming a regular occurrence rather than a rare event.

This episode offers a clear-eyed look at where cybersecurity is heading, without the hype or fear-driven narratives. It is a conversation about scale, speed, and the uncomfortable reality that the threat landscape has changed in ways many organizations are still catching up with.

So as AI continues to reshape both innovation and risk, how prepared is your organization for a world where anyone can launch an attack with a few prompts and a subscription?

Useful Links

• SentinalOne Blog
• Connect with Chris Hosking

Please check the partners of the Tech Tech Talks Network

• Denodo

• Learn more about the NordLayer Browser