Explorez tous les épisodes du podcast Business Technology Perspectives

What if your bank could recognize that you needed help before you had to ask for it?

In this episode of Business Technology Perspectives, I speak with Michel Jacobs, Chief Strategy Officer at CSI, about how artificial intelligence and customer intelligence are changing the relationship between financial institutions and the people they serve.

Community banks and regional financial institutions have traditionally competed through personal relationships rather than scale. But digital banking, fintech competition, and changing consumer expectations are putting that advantage under pressure. Michel argues that the future of banking will increasingly be defined by interactions rather than transactions.

That means understanding why a customer is contacting the bank, what may be happening in their life, and which service could provide value at that moment. It also means preparing for interactions initiated through APIs, open banking services, and AI agents, rather than assuming every customer journey begins with a person opening a banking app.

Michel explains how CSI’s Customer Intelligence Suite combines transaction information, card activity, merchant category data, and digital behavior to identify signals and changing patterns. According to Michel, these signals can help a financial institution understand when a customer’s circumstances may have changed instead of relying on the demographic category assigned when the account was opened.

This creates opportunities for relevant financial support, but it also introduces serious questions about privacy, consent, accuracy, and customer trust. Inferring that somebody has changed jobs, bought a home, become a parent, or encountered financial difficulty can be useful when the response genuinely helps. The same capability can feel intrusive when it produces poorly timed sales offers or conclusions the customer cannot question.

We discuss how banks can balance personalization with regulatory responsibilities and why younger consumers are less likely to remain loyal when a provider offers little practical value. As Michel puts it, the era of offering everybody the same account and throwing in a free beach ball has probably run its course.

Customer retention is another major part of our conversation. Michel explains how declining digital activity, money leaving an account, late payments, or changes in income can reveal that a relationship is weakening. Used responsibly, this information could allow a bank to offer assistance before missed payments or financial strain become harder to address.

For community banks, the answer is unlikely to be copying every product offered by the largest global institutions. Michel believes they should decide where they can provide distinctive value, then use technology and data to support that position. CSI’s stated aim is to give smaller financial institutions access to customer analytics capabilities that would otherwise require considerable internal investment.

Can AI help banks become useful partners in their customers’ lives without crossing the line from personalization into intrusion? Listen to the conversation and share your thoughts with me.

Why do 88 percent of UK SMB leaders see technology as important to business performance while fewer than half feel highly confident about adopting it effectively?

In this episode of Business Tech Perspectives, I speak with Mark Weait, Chief Revenue Officer at Babble, about the company’s inaugural Technology Performance Index. The research draws on responses from 1,000 UK SMB leaders and C-suite executives and examines a growing technology confidence gap between recognizing what digital tools could achieve and knowing how to identify, implement, and expand them successfully.

Mark describes a pattern many businesses will recognize. A security incident prompts an urgent software purchase. A board request to “do something with AI” leads to a batch of licenses. A new cloud application arrives without a clear business problem, owner, or adoption plan. The company gains another tool, but employees may lack the training, processes, or time needed to turn it into a result.

His analogy is simple: a business can buy a Ferrari, but that does not mean its people know how to drive it. Technology adoption depends on clarity about the desired outcome, the skills needed to deliver it, and the connections between systems, people, security, and data. Mark argues that treating every program as an IT responsibility can overlook the management support and operational change required across the wider business.

The Babble research groups SMBs into Tech Vanguards, Emerging Adopters, and Tech Bystanders. According to figures discussed in the interview, 84 percent of Tech Vanguards report strong processes for technology-led change, compared with 3 percent of Tech Bystanders. The research also reports that 57 percent of Tech Vanguards are receiving measurable results from AI and automation, compared with 21 percent of Tech Bystanders.

Those figures suggest that confidence may build through experience. Companies that begin with a defined problem, equip their people, and measure a deployment can use that success to support the next decision. Those buying technology through fear of missing out risk adding cost, security exposure, and another disconnected application to an already complicated environment.

Mark does not believe smaller businesses have missed their opportunity with AI. He says many companies remain near the beginning, which means an SMB can still catch up without attempting to apply AI everywhere. His recommended approach is to assess readiness, train employees, confirm that networks and data controls are suitable, identify a process where AI can produce a worthwhile result, and expand gradually from there. He also distinguishes AI from established automation, noting that some business problems can still be solved without a generative system.

We also discuss the difference between cyber confidence and cyber resilience. Mark compares it with believing you are a good boxer until you are punched in the face. Security covers identity, email, endpoints, cloud services, and AI, so no single purchase finishes the job. He recommends regular assessments and independent validation to find gaps that a familiar provider or internal team may no longer notice. A company can decide to accept a risk, but that decision should be informed rather than accidental.

For SMB leaders working with limited budgets, Mark suggests reviewing the current technology estate before requesting new money. Duplicate products, unused licenses, old contracts, and disconnected systems can absorb funds that could support better adoption elsewhere. The larger question is whether technology confidence has become a boardroom issue because it affects revenue, customer experience, resilience, and reputation as much as IT performance.

Which of Babble’s three groups best describes your organization today, and what would help it move forward with greater confidence? Listen to the episode and share your thoughts.

What evidence would persuade your board that a successful AI pilot is ready to become part of everyday business operations?

In this episode of Business Technology Perspectives, I speak with Andrew Duncan, CEO of QualityAI, formerly Qualitest. Andrew previously served as CEO of Infosys Consulting and has spent over 30 years advising global organizations across technology and business change.

Andrew believes the AI era differs from previous technology cycles because adoption is moving faster than many organizations can govern it. Fear of missing out is also creating pressure for companies to appear further along than they really are.

This creates a growing gap between AI activity and operational value. A company may have numerous pilots, prototypes, and employee experiments without possessing enough evidence to deploy any of them across the business.

Andrew describes the enterprise AI conversation as moving from “can we build it?” toward “can we trust it?” Answering that question requires companies to assess three areas. Does the technology work? Is it producing the expected business outcome? Will it continue behaving within agreed boundaries as its data, model, users, and environment change?

We discuss the questions boards should ask before approving AI at scale. What business result is the company pursuing? What level of risk is acceptable? Who becomes accountable when the system makes an unexpected decision? Has it been tested under real operating conditions? What evidence demonstrates that people can rely on it?

Andrew explains why a successful pilot should never be confused with production readiness. Controlled tests cannot fully represent real data, human behavior, connected applications, operational processes, or downstream consequences. A system that performs well in isolation may behave very differently once it reaches customers and employees.

This is why Andrew advocates continuous AI assurance. Testing cannot end when an application enters production. Organizations must monitor whether the system continues functioning technically, produces the intended result, and remains within defined guardrails.

Our conversation also addresses AI washing and the growing tendency to measure progress through the number of pilots or features launched. Andrew suggests asking a much simpler question: what has materially improved because AI is involved?

Useful measures could include productivity, revenue, operating costs, cycle times, customer experience, adoption, and the consistency of results. If those outcomes remain unchanged, a collection of impressive demonstrations may amount to activity without meaningful business progress.

Could continuous assurance give businesses the confidence to scale AI faster, or will many companies remain trapped between promising pilots and production risk? Listen to the episode and share your thoughts with me.

Could your company produce a complete inventory of every AI tool, model, agent and embedded feature operating across the business today?

In this episode of Business Tech Perspectives, I speak with Russ Fradin, founder and CEO of Larridin, and Michael Levine, partner at Hunton Andrews Kurth, about the enterprise AI visibility gap and the growing legal, financial and insurance consequences for companies that cannot identify their AI systems.

Russ has experienced several major periods of technology adoption across digital advertising, mobile and workforce communication. He launched Larridin after recognizing that standard measurement systems could not account for the speed and variety of AI tools entering businesses. The company helps enterprises understand which AI systems employees use, what they cost, which models they rely on and where adoption is taking place.

The scale of the problem can be surprising. Russ describes an early customer that expected to find approximately 70 AI tools operating across the company but discovered 220. Most were benign, including five separate AI meeting assistants, but the discovery revealed unnecessary spending and fragmented adoption.

Another customer found an AI agent built by a former employee that continued running at a cost of $1,800 each month. Nobody remaining at the company understood what the agent did. The example shows why an enterprise AI inventory concerns business spending and accountability alongside security and compliance.

Mike explains how embedded AI can expose a company to legal action without leaders realizing that AI was involved. He discusses a class action concerning an HR screening tool that allegedly used AI-assisted lie detection without the required disclosure.

We also examine the growing patchwork of US AI regulation. Mike discusses the Texas Responsible Artificial Intelligence Governance Act and the Colorado AI Act, along with the difficulties faced by businesses operating across several states. A web-based company may need to comply with a state law because it serves residents there, even when the company is based elsewhere.

Board accountability is another focus. Russ says boards increasingly want to know which tools and models are being used, what employees use them for, what data agreements apply and how much the company is spending. Mike adds that inaccurate statements about AI capabilities can create directors and officers exposure through shareholder litigation.

Insurance adds further complexity. Mike explains why traditional cyber coverage may not apply to many AI claims because they do not involve a data breach or loss of protected information. Insurers are beginning to introduce AI-related exclusions across several forms of commercial coverage, making the wording and definition of AI increasingly important during renewal.

Russ and Mike close with practical guidance for companies building a verified AI inventory. IT, finance, legal, HR, operations, risk teams and board members must contribute because no single department has a complete view of AI use across the business.

Could your leadership team identify every AI system, its owner, its cost, the information it touches and the insurance protection available if something goes wrong? Please share your thoughts with me.

Why do companies spend millions on AI and digital transformation while overlooking the people expected to make those investments successful?

In this episode of Business Technology Perspectives, I speak with Elena Varo, founder of Elevatio Tech & Culture, about why the biggest barriers to technology adoption are often human rather than technical, what leaders misunderstand about organizational change, and why companies need to invest in people as seriously as they invest in technology.

Elena brings more than a decade of experience across the technology industry, including work with Microsoft, Red Hat, CyberArk, and WSO2. Having worked across Spain, Ireland, and the UK, she has seen how leadership, workplace culture, communication, and organizational structures influence whether technology investments produce meaningful business outcomes.

A major theme throughout our conversation is the gap between buying technology and preparing a company to use it effectively. Elena argues that many businesses begin with the wrong question. They focus on which AI platform, cybersecurity product, or cloud provider to purchase before identifying the problem they need to solve and understanding whether employees have the skills, training, information, and support required to adopt new technology.

We discuss why AI is creating a leadership challenge that may be harder to solve than the technology itself. Employees want answers to practical questions about training, skills, changing roles, and expectations. When companies fail to communicate clearly or listen to their workforce, uncertainty grows, experienced employees leave, and technology adoption becomes harder.

Talent retention is another major part of the conversation. The technology industry frequently talks about skills shortages and recruiting new employees while paying far less attention to why talented people leave. Elena explains why salary alone rarely solves problems caused by unclear responsibilities, poor communication, limited career development, internal competition, and workplaces where employees do not feel safe speaking openly.

We also examine the relationship between employee well-being and long-term business performance. Constant technology change, economic uncertainty, demanding targets, and pressure to do more with fewer resources affect employees and managers alike. Companies that want people to collaborate, share knowledge, question assumptions, and develop new ideas need to create working environments where people feel supported and heard.

The conversation also addresses diversity in technology and why attracting more women and people from different backgrounds is only part of the challenge. Companies need to improve retention, promotion processes, sponsorship, access to leadership positions, and opportunities for people with different experiences to influence decisions.

Elena also shares why she founded Elevatio Tech & Culture and her plans for a technology congress in Córdoba that brings business leaders, technologists, universities, public institutions, and other participants together to discuss technology adoption, organizational culture, talent, leadership, and employee well-being.

For CEOs, CIOs, HR leaders, technology executives, and anyone responsible for AI adoption or digital transformation, this conversation provides practical lessons about preparing employees for change, retaining experienced talent, improving communication, supporting psychological safety, and creating workplaces where technology investments can produce better outcomes.

Elena’s advice to business leaders is clear: invest in people as seriously as you invest in technology. Technology can be purchased, but building a workplace where people trust their leaders, develop new skills, share knowledge, and want to contribute requires sustained attention.

What happens when AI can write software in seconds but lacks the context to understand whether the code it creates is built on secure foundations?

In this episode of Business Tech Perspectives, I speak with Brian Fox, Co-Founder and CTO of Sonatype, about the growing pressure facing software teams as AI accelerates development while cyber threats continue to evolve. Brian brings a unique perspective from his work overseeing Maven Central and helping organizations understand the risks hidden inside modern software supply chains.

Our conversation begins with a challenge that many organizations may not fully appreciate. While AI coding assistants are becoming increasingly capable, the information they rely on can already be months old. Brian explains why that matters when selecting open source dependencies and how outdated recommendations can leave security risks buried inside applications long after they are deployed.

We also discuss the role open source software now plays in almost every application. Developers can build products faster than ever by using existing components, but that speed comes with responsibility. Brian shares why understanding what is inside your software has become a business issue as much as a technical one.

Another major topic is the expected surge in vulnerability discoveries driven by new AI capabilities. Brian warns that both attackers and security researchers now have access to tools that can identify weaknesses at unprecedented speed. The result could be a flood of vulnerability reports that challenges maintainers, vendors, and security teams alike.

The discussion also covers the changing state of vulnerability intelligence. With NIST narrowing its focus and public resources under strain, organizations may need to rethink how they gather information, assess risk, and prioritize remediation efforts.

Throughout our conversation, Brian offers practical advice for leaders who want to prepare their organizations for what comes next. From understanding software bills of materials to improving patch management processes, he explains why preparation today could make all the difference tomorrow.

Despite the challenges, Brian remains optimistic about the future. He believes AI will help developers create software faster and help the industry address years of accumulated security issues. The question is whether organizations can adapt quickly enough to keep pace with the changes already underway.

How confident are you that your organization could identify, assess, and respond to a major software supply chain issue today, and are your teams prepared for the increase in vulnerabilities that AI may soon uncover?

What happens when the biggest barrier to AI success isn't the technology itself, but the way organizations are structured to adopt it? In this episode, I sit down with Milan Cooper, Head of Product at TWG AI, a company working alongside Palantir to help enterprises rebuild core business processes around AI. With previous leadership roles at JPMorgan Chase and Accenture, Milan brings a rare perspective from the intersection of AI, risk, governance, and large-scale transformation.

Our conversation moves beyond chatbots, pilots, and proofs of concept to examine what it actually takes to make AI part of mission-critical operations. Milan explains why so many organizations remain stuck in what he calls "AI theater," measuring success through use cases rather than business value. He shares how TWG AI approaches enterprise adoption by focusing on entire value streams, helping organizations move from isolated experiments to AI-native operations that directly influence revenue, efficiency, and decision-making.

We also discuss the growing challenge of AI concentration risk, why switching between AI models could become the equivalent of performing brain surgery on an enterprise, and how organizations can avoid locking themselves into a single provider. Milan offers insights from projects with companies including Guggenheim Investments, where AI is being embedded into investment workflows to increase deal throughput and remove operational bottlenecks.

Along the way, we tackle governance, compliance, AI accountability, the future of SaaS, and why leadership conviction may be the single biggest factor determining whether an AI transformation succeeds or stalls. Milan also shares why trust remains the missing ingredient in enterprise AI adoption and what organizations need to do before employees are comfortable using AI with their most sensitive information.

If you've ever wondered why some companies are turning AI into measurable business outcomes while others remain trapped in endless experimentation, this conversation offers a candid look at what separates the two. What do you think is holding back AI adoption in your organization, technology, culture, or leadership? Share your thoughts with me.

What if the most valuable AI asset your organization already owns is sitting untouched inside years of video, audio, and unstructured content?

In this episode, I sit down with Sean King from Veritone to explore how organizations are transforming massive archives of content into searchable, licensable, and revenue-generating assets for the AI economy. As the executive leading Veritone’s commercial business, Sean works directly with major organizations, including the NCAA and ESPN, to help unlock value hidden inside decades of multimedia data.

We discuss why the next phase of AI will be defined by multimodal data rather than text alone, and why businesses are dramatically underestimating the value locked inside their video, audio, and image archives. Sean explains how AI is turning what was once treated as a passive storage problem into an active business asset, making unstructured content searchable, contextual, and commercially valuable at scale.

The conversation also looks at how organizations can modernize decades-old archives without becoming overwhelmed by the sheer volume of data involved. Sean shares how companies can approach AI transformation by first building scalable workflows for incoming content before tackling historical archives. From sports media and broadcasting to enterprise knowledge management, we explore how searchable multimedia data is creating entirely new opportunities for storytelling, fan engagement, licensing, and monetization.

We also get into the growing debate around intellectual property and AI training data. Sean offers a thoughtful perspective on why trust, transparency, and rights-cleared content are becoming increasingly important as AI models evolve. He explains why sustainable AI ecosystems will depend on respecting creators, fairly compensating rights holders, and ensuring enterprises know exactly where their training data originates.

The discussion then shifts toward the emerging “agentic web,” where AI systems move beyond research and begin handling tasks, workflows, and decisions autonomously. Sean argues that future competitive advantage will belong to organizations with access to the highest-quality licensed data, because the difference between an average AI agent and a truly effective one will come down to the quality, structure, and accessibility of the information they can use.

We also talk about the human side of AI adoption. Sean shares why he believes AI should be viewed as a tool that amplifies human potential rather than replacing it, comparing today’s AI shift to the arrival of the internet itself. From personalized AI experiences to machine-driven workflows and new business models around licensed content, this conversation offers a fascinating look at how the AI economy is beginning to reshape media, enterprise technology, and digital experiences in real time.

How can businesses make smart AI bets when they cannot even see the full picture of what is already happening inside their own organization?

In this episode of Business Tech Perspectives, I sit down with Russ Fradin, CEO of Larridin, for a conversation about one of the biggest blind spots in enterprise AI right now. While many leaders are focused on adoption, experimentation, and speed, Russ argues that a more fundamental issue is being overlooked. Companies are investing in AI at scale, but many still lack a clear view of which tools are being used, who is using them, and whether any of it is delivering measurable value.

What made this conversation so timely for me was Russ’s perspective as someone who has lived through several major waves of technology change. From digital advertising and mobile to cloud and now AI, he has seen what happens when innovation moves faster than the systems designed to manage it. In this case, the challenge is what he calls the AI visibility gap, where tools are spreading across teams faster than IT, finance, and leadership can track. That creates questions around governance and cost, but it also raises a more practical business issue. If you do not know what is being used, how do you know what is working?

We also get into why Russ believes experimentation is not the problem. In fact, he makes a strong case that organizations should be trying lots of tools right now. The issue is when those experiments happen without measurement, without accountability, and without a framework for understanding productivity and return on investment. I particularly liked his point that this is not about shutting innovation down. It is about building the right measurement, governance, and data foundations so businesses can experiment with confidence instead of chaos.

Another part of the conversation that stayed with me was the idea of identifying the people inside an organization who are already becoming dramatically more productive with AI. Russ talks about how some employees are already figuring out what great looks like, while others are still staring at a blank prompt box unsure where to begin. That creates an opportunity for leaders to stop treating AI adoption as a vague aspiration and start turning real employee behavior into repeatable playbooks that can help the wider workforce improve.

This episode is really about the gap between AI excitement and AI accountability. If AI is now moving into every corner of the enterprise, leaders need more than enthusiasm. They need visibility, they need measurement, and they need a way to connect spending with outcomes in real time. So as AI use continues to spread across your own business, do you actually know what is happening under the surface, and what do you think companies should be measuring first? Share your thoughts.

The link Russ mentioned during the podcast can be found here:

What if enterprise AI could move beyond answering questions and start explaining why things are happening in your business?

In this episode of Business Tech Perspectives, I sat down with Alberto Pan, Chief Technology Officer at Denodo, to explore how AI is shifting from surface-level responses to deeper, reasoning-driven insights. As organizations wrestle with fragmented data, governance challenges, and growing expectations around AI, this conversation gets to the heart of what meaningful progress actually looks like.

At the center of our discussion is Denodo’s DeepQuery, an AI reasoning agent designed to perform complex, open-ended research across an organization’s data landscape. Alberto explains how it goes far beyond traditional approaches like retrieval augmented generation by creating research plans, analyzing patterns, and even refining its own process along the way. The result is not just faster answers, but a more complete understanding of what is really happening beneath the surface.

We also unpack what this means for business intelligence teams. Rather than manually building dashboards and reports, analysts are stepping into a new role as guides, working alongside AI systems that can gather, analyze, and present insights in minutes. It raises an interesting question about how skills, roles, and expectations will evolve as these tools become more widely adopted.

A big part of the conversation focuses on data itself. Alberto shares how Denodo’s logical data layer allows organizations to access and govern data across multiple systems in real time, without creating new silos. That foundation becomes even more important as AI adoption accelerates, especially when accuracy, context, and explainability are all under increasing scrutiny.

We also touch on the growing importance of transparency in AI. With concerns around black box decision making continuing to rise, Alberto explains how DeepQuery provides full traceability, showing exactly how insights are generated and where the underlying data comes from. It is a practical step toward building trust in AI systems at scale.

Looking ahead, this episode offers a clear view into how research-driven AI could reshape decision making across industries. From finance to healthcare, the ability to move from static reports to dynamic, AI-assisted investigation has the potential to change how organizations operate on a daily basis.

So as AI becomes more embedded in business workflows, are you still asking your data what happened, or are you ready to understand why it happened and what to do next?

Useful Links

• Connect with Alberto Pan on LinkedIn
• Learn more about Denodo
• Stories of Your Life and Others book that Alberto shared for our Amazon list
• O’Reilly’s The Rise of Logical Data Management book
• Follow on LinkedIn, and Twitter

What if one of the most influential functions in your business is also the one you understand the least?

In this episode of Business Tech Perspectives, I sat down with Anders Lillevik, Founder and CEO of Focal Point, to unpack the hidden complexity of procurement and why it has quietly become one of the most critical levers in modern enterprise strategy. With more than two decades of experience leading procurement at organizations like Fannie Mae and QBE Insurance, Anders brings a rare perspective shaped by real-world scale, regulatory pressure, and the shifting expectations placed on global businesses.

Our conversation explores how procurement has evolved from a cost-saving function into something far more expansive. Today, it sits at the center of spend, risk, compliance, supplier relationships, and ESG accountability. Yet despite that growing responsibility, many teams are still relying on spreadsheets, email chains, and disconnected systems that create inefficiencies and expose organizations to unnecessary risk. Anders explains how this fragmented approach slows decision-making, increases manual effort, and often leaves leadership without a clear view of what is really happening across their supplier ecosystem.

We also get into the role AI is beginning to play in bringing structure and visibility to procurement. Rather than replacing people, Anders shares how automation can remove repetitive tasks, validate supplier data in real time, and streamline processes that once took hours into seconds. But he is equally clear on where expectations are running ahead of reality. The real value, he argues, comes from applying AI to repeatable, auditable workflows rather than chasing novelty or treating it like a conversational tool.

One of the most interesting parts of the discussion centers on orchestration. Anders describes how Focal Point is designed to sit across existing systems, connecting data, workflows, and stakeholders into a single, unified view. Instead of forcing organizations into disruptive rip-and-replace transformations, this approach allows companies to start small, prove value quickly, and scale change without breaking what already works. It is a pragmatic take on digital transformation that feels grounded in how enterprises actually operate.

Looking ahead, Anders paints a picture of procurement as a strategic capability rather than a back-office function. The organizations that get this right will not only manage cost and risk more effectively, they will also unlock new sources of innovation, improve supplier collaboration, and even influence working capital in ways many leaders overlook.

So how should businesses rethink procurement in a world shaped by AI, rising compliance demands, and increasing operational complexity, and what opportunities are being missed by those who still treat it as an afterthought?

What happens when companies rush into AI without fixing the fundamentals that actually make data useful?

In this episode of Business Tech Perspectives, I sit down with Rajan Sethuraman, CEO of LatentView Analytics, which is a global data engineering and analytics company that helps businesses excel in the digital world by harnessing the power of data. I learn more about their refreshingly pragmatic approach to AI adoption that many organizations are overlooking.

Rajan brings a rare blend of leadership experience to the table. Before becoming CEO, he spent more than two decades at Accenture, including a role leading talent and people strategy. He later joined LatentView, eventually guiding the company through its IPO and its first acquisition while expanding its work with more than 50 Fortune 500 clients.

Our conversation begins with an idea Rajan describes as AI minimalism. At a time when many executives feel pressure to experiment with every new generative AI capability, Rajan argues that the real challenge is not adopting more technology. Instead, organizations need to simplify their data ecosystems and create trusted foundations before scaling AI initiatives. Without that clarity, companies often end up with multiple data pipelines, conflicting metrics, and competing versions of the truth.

We also talk about the hidden friction inside many AI projects. Rajan explains that technology is rarely the real barrier. Culture and clarity often determine whether a transformation succeeds. If organizations cannot agree on how key metrics are defined or where their source of truth lives, even the most advanced AI models will struggle to deliver meaningful results.

Rajan also shares what he has learned working with global enterprises across industries such as financial services, retail, healthcare, and technology. From governance and data lineage to embedding analytics into everyday decision making, he outlines the patterns that separate organizations that claim to be data driven from those that actually operate that way.

One of the most valuable moments in the conversation comes when Rajan offers practical advice for CEOs under pressure to accelerate AI adoption. His recommendation is surprisingly simple. Start by defining the metrics that matter most to the business. Then work backwards from those metrics to identify the data, systems, and decision processes that influence them. Only after that foundation exists should organizations decide which AI capabilities to deploy.

We also explore how LatentView is helping enterprises apply emerging technologies such as generative and agentic AI to improve efficiency, effectiveness, and speed across business operations. Rajan explains why partnerships, experimentation, and ecosystem collaboration are becoming essential as the AI landscape evolves.

If you are trying to cut through the noise surrounding AI and focus on what actually drives measurable outcomes, this episode offers a thoughtful and practical perspective. Are organizations moving too fast in the race to adopt AI, and could a simpler, more disciplined approach actually create stronger results?

What does it actually take to turn AI from an experiment into measurable growth?

In this episode, I caught up with Jason Riback, President of MediaMint, to unpack what “agentic growth services” really mean in practice. MediaMint works with leading organizations across media, entertainment, retail, and technology to scale front-office operations across marketing, sales, media, and data. But this conversation was less about buzzwords and more about execution.

Jason shared his journey from engineering at the University of Michigan to McKinsey, and then into the heart of the San Francisco startup ecosystem. That blend of operational rigor and startup agility clearly shapes how he thinks about growth today. For him, AI is only valuable when it produces definable improvements in real workflows. That means fewer manual handoffs, fewer errors, faster cycle times, and better output quality. Otherwise, it is just another system sitting on the shelf.

We spent time breaking down the gap between data-driven marketing in theory and decision-making in reality. Reporting is always retrospective, Jason reminded me. The real challenge is using insights in near real time to influence spend allocation, targeting, and optimization before a campaign ends. That requires governance, clean data, and clear accountability. Without those foundations, organizations risk operational exposure and opaque decision logic that no one can confidently explain.

One of the most thoughtful parts of our discussion centered on human oversight. Jason was clear that while AI can technically retrain models and adjust guardrails on its own, handing over full autonomy creates a black box problem. Enterprises need the right governance layer, where recommended changes are reviewed and approved against clear outcomes. Automation should feel invisible within the workflow, not like another dashboard demanding attention.

We also explored MediaMint’s Intelligent Assistant platform, MIA. What stood out to me was the pragmatic approach. Rather than offering a one-size-fits-all tool, MediaMint customizes AI agents around each client’s tech stack, data connectors, and workflow steps. That flexibility is essential because no two marketing organizations operate the same way. The goal is applied agentic execution embedded into daily workloads, not theoretical AI capability.

Finally, we turned to the people side of transformation. As automation becomes embedded in front-office operations, roles will inevitably shift. Jason believes teams will move away from repetitive execution and toward managing, interpreting, and optimizing AI-driven processes. That shift demands AI literacy, cross-functional alignment between marketing, tech, and finance, and shared agreement on what good looks like. Accountability does not disappear simply because an agent executes a step.

If you are wrestling with how to apply AI inside marketing and revenue operations without creating new risks or unnecessary complexity, this episode offers a grounded perspective. It is a conversation about discipline, governance, and measurable outcomes, not hype.

What would change in your organization if automation genuinely reduced cycle times by 50 percent while improving quality and transparency at the same time?

What does it really take to build profitable technology companies without outside funding, and why does that mindset matter even more as AI reshapes every industry?

In this episode of Business Tech Perspectives, I sat down with James Benham, a lifelong technologist, serial founder, and unapologetic bootstrapper who has spent more than two decades building enterprise software businesses on his own terms. Broadcasting from Texas, with stories that stretch from Louisiana to Argentina to the UK, James brings a rare mix of candor, humor, and hard-earned perspective on what it means to survive and grow in technology when there is no safety net.

James shares his journey from writing code as a teenager to running an early dial-up internet service provider, before going on to co-found JBKnowledge and later launching Terra, a modern core system transforming workers’ compensation and insurance operations. We talk openly about why he chose bootstrapping over venture capital, how that decision shaped his leadership style, and why cash discipline still separates companies that endure from those that quietly disappear.

The conversation also explores why insurance, often dismissed as dull from the outside, becomes endlessly fascinating once you understand how deeply it touches everyday life. James explains how risk, data, and claims connect everything from football matches to flight safety, and how working inside the industry fundamentally changes how you see the world around you. It is a reminder that some of the most meaningful innovation happens in places that do not shout for attention.

We spend time unpacking lessons from his book, Be Your Own VC, including why survival matters more than growth headlines and how many founders underestimate the emotional toll of building companies over decades. James does not shy away from discussing the hard days, the moments of doubt, or the reality that technology leaders are always one misstep away from trouble.

As expected, AI enters the discussion, not as a buzzword but as a genuine shift in how fast software can be built and how quickly businesses can fall behind. James offers a clear-eyed view on why speed to market, trust, and execution now matter more than ever, especially in regulated industries like insurance where legacy processes still dominate.

We close on a deeply human note, talking about creativity, music, flying, and the role of art in staying grounded while leading global teams. It is a reminder that the best business leaders rarely draw their energy from work alone.

So as automation accelerates and building software becomes easier than ever, how do you design a career and a company that can still last for decades, and what would you do differently if you truly had to bet on yourself?

Useful links

• James Benham’s personal site
• JBKnowledge:
• Terra Workers’ Compensation Platform:
• Be Your Own VC book:
• InsureTech Geek Podcast:
• James Benham on LinkedIn:

Thanks to our sponsors, Alcor, for supporting the show.

What if the biggest barrier holding entrepreneurs back was never a lack of ideas, but the friction created by tools, platforms, and infrastructure that were never designed for speed?

In this episode of Business Technology Perspectives, I sit down with Sachin Puri, CEO of Bluehost, to explore how AI-native platforms are reshaping what is possible for entrepreneurs and small businesses. Sachin brings a long-term view from the heart of the web, sharing how the shift toward AI-assisted creation is lowering barriers, accelerating experimentation, and enabling a new wave of solo-scale founders to build brands, storefronts, and full customer journeys in days rather than months.

Our conversation looks beyond AI hype and focuses on where real value is showing up. Sachin explains how customer expectations are evolving in an AI-driven marketplace, where instant performance, personalization, and seamless experiences are no longer differentiators but baseline expectations. We also discuss why infrastructure alone is no longer the advantage it once was, and why speed of innovation, adaptability, and integrated experiences now determine which businesses scale and which struggle to keep up.

We also dig into an important milestone for an open, AI-ready web, with Sachin sharing why collaboration across the ecosystem matters. From Bluehost’s work with Yoast on brand insights and generative engine optimization to broader partnerships with companies like Microsoft, this episode highlights how the next phase of the web will be shaped by platforms that help entrepreneurs get discovered not just by search engines, but by AI systems as well.

Sachin offers practical insight into what happens when success arrives faster than expected, why virality can become a crisis without the right foundations, and why hosting has quietly evolved into a strategic performance layer rather than a background utility. As we look toward 2026, we explore the rise of intelligent, living websites, the return of owned web real estate, and why the future belongs to builders who move quickly while staying grounded in reliability, security, and trust.

If AI is giving entrepreneurs access to capabilities once reserved for the biggest players, how will you use that advantage to build something that lasts?

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How do you transform an industry that most people still assume runs on clipboards, manual checks, and fragmented updates? And what happens when reality capture and AI finally combine to give construction teams a clear and measurable picture of progress on every site? In this episode of Business Tech Perspectives, I sit down with Chaitanya NK, the co-founder and CEO of Track3D, to explore how reality intelligence is reshaping the way major projects are built and managed.

NK shares how three founders with no construction background stepped into one of the most complex environments in the world and uncovered a problem that had been hiding in plain sight. Field data was inconsistent, incomplete, and nearly impossible to verify at scale. The result was delays, rework, and avoidable cost overruns. Track3D tackles this head-on by unifying drones, 360 cameras, scanners, mobile devices, and even robots into one clear view of what has been installed, when it happened, and whether it meets the plan. Through practical examples, NK explains how automated measurement brings immediate clarity, how deviations are caught early before they snowball, and how objective data changes coordination across trades, schedules, and budgets.

This is a conversation for anyone interested in the real business value of AI in physical environments. NK talks openly about trust, data governance, security, and the balance between automated insight and human judgment. He also shares his vision for 2026, where AI agents act as partners to schedulers, coordinators, and field teams. If you want to understand how technology is reshaping one of the world’s largest and most demanding industries, you will find real insight here.

Listeners who want to learn more about Track3D or connect with the team can visit track3d.ai or reach out on LinkedIn at Track3D. Where would you like to explore this conversation further in your own work?

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What does it take to lead one of the fastest growing regions in enterprise security while spending your year hopping between Sydney, Tokyo, Singapore, and London? At IGEL’s Now & Next event in Frankfurt, I caught up with Darren Fields, Senior Vice President for UK and Asia Pacific, to find out.

From rebuilding the partner ecosystem across continents to forging new alliances with industry giants like Lenovo, Palo Alto Networks, and CrowdStrike, Darren has been at the center of IGEL’s global expansion. He shared how regional differences shape technology adoption, why prevention first security is resonating with customers everywhere, and how business continuity has shifted from being a safety net to a core design principle for modern IT.

In our conversation, Darren explained how the endpoint has become the new control point for everything from zero trust to AI driven automation, and why so many organizations are rethinking old assumptions about bring your own strategies. He also opened up about the mindset shift he’s witnessing among IT leaders, one that moves from reacting to threats toward proactively preventing them.

We also discussed how cultural differences influence the pace of digital transformation, with regions like Japan preferring careful evaluation, while Australia and New Zealand have embraced rapid innovation. Darren’s global perspective highlighted how security maturity looks different around the world, yet the ultimate goal remains the same: empowering organizations to build trust, resilience, and operational continuity.

As we approach another year defined by AI, cybersecurity, and digital resilience, Darren’s reflections offer a rare window into how global teams are turning complexity into simplicity and scaling trust in every region. What does a truly prevention first future look like, and how can enterprises across the world prepare for it?

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Sales enablement has come a long way from slide decks and one-size-fits-all training. In this episode of Business Technology Perspectives, I’m joined by Bill Dwoinen, Chief Revenue Officer at Mural, to explore how AI and visual collaboration are changing the way teams sell, learn, and align around outcomes.

Bill brings a wealth of experience from Salesforce and LinkedIn, but what makes this conversation special is how openly he shares the lessons Mural has learned from its own transformation. Once known purely as a visual collaboration tool, Mural is now evolving into a platform that helps organizations accelerate deal velocity, strengthen customer retention, and align teams through what he calls “collaborative selling.” For Bill, the goal is simple: help people spend less time managing tools and more time solving real customer problems.

He talks about the growing disconnect between sales strategy and enablement, explaining that many teams today have lost touch with foundational skills such as discovery and negotiation. The solution, he says, lies in a three-part framework of training, enablement, and execution, each powered by technology and reinforced through timing and alignment with the business strategy. This isn’t about piling on new software but understanding what problem each tool actually solves and how it supports human performance.

We also explore how AI is reshaping the sales process in ways that are both practical and profound. From generating account insights in minutes to surfacing hidden “Trojan horse” contacts, AI is helping sales teams work smarter without replacing the human element. Bill shares how simple AI prompts have turned Mural’s own teams into experts on their target accounts, driving consistency, efficiency, and confidence across the field.

Our discussion also touches on the cultural side of enablement, breaking down silos, moving back to more synchronous communication, and bringing inclusivity into decision-making. As Bill puts it, great enablement mirrors great product design: if you build it without the user’s feedback, it doesn’t matter how good it looks.

By the end of this episode, it’s clear that Mural’s next chapter isn’t about whiteboards or sticky notes. It’s about empowering teams to think together, act faster, and use AI to bring clarity to the chaos of modern sales.

Listen now to hear how Bill and his team are redefining enablement in an AI-driven world and why sometimes, the smartest sales strategy starts with asking better questions.

AI conversations often center on coders, designers, and office-based teams, but what about the people who keep goods moving, shelves stocked, patients cared for, and factories running? They make up almost 80 percent of the global workforce, yet much of the technology talk overlooks them. In this episode of Business Technology Perspectives, I sit down with Tom Bianculli, Chief Technology Officer at Zebra Technologies, to explore how AI is being designed for the shop floor, the warehouse aisle, and the hospital corridor.

Tom outlines Zebra’s long-standing mission to “deliver productivity at the point of activity,” and explains how AI fits into that vision. The company’s approach is not about replacing people but augmenting their capabilities, reducing repetitive tasks, and enabling faster, more accurate decision-making. We discuss Zebra Companion, the company’s AI-powered assistant for frontline teams, which features four dedicated agents for knowledge, sales, merchandising, and device support. Early pilots have shown strong adoption, with workers reporting greater empowerment and employers seeing reduced attrition.

We also dive into the role of machine vision, 3D scanning, and RFID in driving efficiency across retail, logistics, and manufacturing. Tom shares examples ranging from automated shelf checks to high-speed industrial inspection, and from wearable cameras that guide item picking to omniscient store concepts that combine real-time inventory awareness with operational intelligence.

The conversation goes beyond features and functions to focus on human-centered automation — the belief that AI works best when it collaborates with people, adapts to their experience level, and integrates seamlessly into their daily tools. For business leaders seeking ROI, we talk about where AI delivers measurable impact today, the infrastructure needed to support it, and the opportunities on the horizon for physical workplaces.

If you’ve been wondering what AI can really do for the teams who keep everything moving, this episode offers a clear and practical perspective.

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This week, I sat down with Craig Burnham, Vice President of Product Marketing for Cisco’s Collaboration business, to go beyond the headlines and unpack what Cisco’s AI evolution actually means for business leaders.

Recorded live at Cisco Live, this episode dives into how Cisco is unifying employee and customer experiences across voice, video, and virtual agents, while keeping humans in the loop where it matters most.

Craig and I explore:

• The rise of Webex AI Agent and Webex AI Assistant, and how they’re reducing agent burnout, shortening call resolution times, and delivering truly autonomous voice and text experiences
• Why Cisco is uniquely positioned to bring cloud-based AI to on-prem environments and hybrid deployments without forcing disruptive migrations
• How Control Hub is evolving into a single pane of glass for AI visibility, governance, and ROI tracking
• What the move toward agentic AI means for IT leaders, and why the long-term impact may be greater than we expect
• How Cisco’s cinematic camera tech and AI-powered meeting features are quietly redefining hybrid work, one room at a time

We also discuss the shifting expectations around AI, from productivity hype to measurable business value, and how Cisco’s platform-first approach enables it to scale new features across contact center, meetings, calling, and more.

For more than 160 years, the Red Cross emblem has protected humanitarian organizations in times of war. But as conflict increasingly moves into cyberspace, new protections are needed for digital infrastructure.

In this episode of Business Technology Perspectives, I speak with Samit D'Cunha, legal advisor at the International Committee of the Red Cross (ICRC), about the groundbreaking Digital Emblem Project.

Samit explains how this modern emblem uses cryptographic certificates and DNS protocols to designate digital assets as protected under international humanitarian law. We explore the rise in cyberattacks on hospitals and humanitarian networks during armed conflict, and why creating a recognized, trustworthy signal of digital neutrality is now a moral and legal imperative.

We discuss:

• How the Digital Emblem mirrors the protections of its physical counterpart
• The technical infrastructure behind the project and how it ensures global applicability
• Legal, political, and diplomatic challenges in gaining global adoption
• The need for collaboration across governments, tech companies, and humanitarian actors
• What comes next as cyberwarfare becomes a greater threat to humanitarian operations

As the nature of conflict evolves, so too must the symbols that protect those who help others. This conversation is essential listening for anyone working at the intersection of cybersecurity, ethics, and international law.

In this episode of Business Technology Perspectives, host Neil C. Hughes speaks with Bulent Cinarkaya, General Manager of Field Service Management at ServiceNow, to explore how AI is transforming one of the most overlooked but essential areas of enterprise operations: field service.

Bulent shares how technologies like agentic and generative AI are reshaping frontline work in real time, giving technicians the tools to anticipate what they’ll need before arriving on site, surface answers during complex tasks, and close out jobs faster with intelligent automation. These innovations are no longer on the horizon. They are already being used to improve scheduling accuracy, reduce mean time to resolution, and capture decades of expert knowledge before it disappears.

Drawing on real examples from companies like Bell Canada, Coursera, and British Telecom, Bulent breaks down how ServiceNow is helping field teams not only boost productivity but also improve job satisfaction and customer loyalty. He also highlights how unified platforms, data-driven workflows, and strong change management are critical to scaling these gains sustainably.

If your organization still sees AI as a back-office tool, this conversation is a wake-up call. AI is now embedded in the physical world of work, helping solve operational bottlenecks while empowering people to do their best work under pressure.

Whether you're leading a service team or looking to bridge the gap between digital innovation and human impact, this episode offers a clear look at the future of field service.

In this episode of Business Technology Perspectives, I sit down with Anoop Joshi, Chief Trust Officer at Trustpilot, to explore how the fight against fake reviews is changing in an AI-driven world.

We discuss the impact of new rules like the FTC’s ban on fake reviews, which makes trust a boardroom topic rather than just a marketing concern. Anoop explains how Trustpilot combines machine learning, deep metadata checks and human moderation to protect review integrity across a community of millions.

He shares how his background as an IP lawyer shapes his view of today’s intellectual property debates in AI, why pattern detection beats content checks, and how Trustpilot has won multiple legal cases against bad actors in the past two years.

We also look ahead at trends that will test businesses, from deepfakes to crypto scams, and why human oversight still matters alongside smarter technology. Anoop’s insights offer a candid look at what it really takes to keep online reviews trustworthy at scale.

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Mobile gaming isn’t just entertainment. It’s quickly becoming one of the most valuable and overlooked channels for digital advertisers. In this episode, Cerisse Velasco, Director of Brand Partnerships at Zynga, joins Neil to lift the lid on how the gaming giant is helping brands connect with highly engaged, predominantly female audiences through in-game experiences that balance fun, relevance, and performance.

• Why the stereotypical “gamer” image is outdated, and how Zynga’s audience trends toward Gen Z and millennial women
• How brands are using rewarded video, custom playable, and deep integrations to build emotional connections with players
• What made partnerships like the Real Housewives collaboration such a perfect fit, and how authenticity drives engagement
• Why mobile gaming is outperforming other digital channels in attention and conversion
• How Zynga is adapting to a privacy-first future through persona-based planning and contextual targeting

She also gives us a glimpse into what’s next for mobile gaming as a marketing platform, from value exchange experiences to retail media integration and gamified brand storytelling.

If your brand still views gaming as a niche space, this conversation will provide you with a completely different perspective.

In this episode, Dr. Chris Austin, Senior Vice President of Research Technologies at GSK, joins Neil to share how artificial intelligence, genetics, and vast clinical datasets are radically reshaping the pharmaceutical landscape. A neurologist by training with experience across the NIH, biotech startups, and now GSK, Chris explains how drug development is finally moving beyond trial-and-error toward predictive, precision-based approaches.

He reveals how GSK is:

• Using AI and genomics to map disease “circuits” and prioritize drug targets with greater accuracy
• Designing novel molecules like oligonucleotides to reach previously “undruggable” targets
• Streamlining clinical trials through deep phenotyping and biomarker-based patient selection
• Leveraging generative AI to model disease biology, simulate clinical outcomes, and accelerate antibody design by 90 percent

Chris also reflects on the journey from the Human Genome Project to today’s AI-powered medicine and why he believes GSK has the right mix of data generation, scientific expertise, and computing infrastructure to lead the next wave of medical breakthroughs.

If you’ve ever wondered how AI is moving from hype to real-world health impact, this conversation offers a rare inside look at the front lines of biopharma innovation.

Listen now to discover how technology is not just speeding up drug discovery, it’s rewriting the rules entirely.

In this episode of Business Technology Perspectives, I sit down with Somit Goyal, CEO of IBS Software, to talk about something every traveler has experienced: outdated systems that make booking, checking in, or simply managing a trip more frustrating than it should be.

Somit brings a wealth of experience from his time at Microsoft to now leading one of the biggest names in travel tech. He shares why real transformation in this space isn't just about upgrading software. It's about rethinking how travel businesses operate, how they engage with customers, and how they build for the future.

We talk about the dangers of treating digital transformation as just another IT project and why companies stuck on legacy systems are holding themselves back. Somit explains how IBS Software is working as a true partner to airlines, hotels, and cruise lines, not just another vendor pushing tools. He also shares how listening to customers, rather than rushing into tech solutions, is one of the most underrated skills in this industry.

We explore how AI and data are shaping smarter travel experiences, what it takes to overhaul loyalty programs, and why a long-term strategic mindset beats short-term patch jobs every time.

So if you've ever wondered why your last flight check-in felt like it was designed in 2005 or why your hotel app crashed again, this episode offers a look behind the curtain at what's really happening in the travel tech world.

I hope you'll join me for this conversation and let me know what you think. How is your organization approaching change? And what does modern travel tech mean to you?

Search Tech Talks Network to discover more shows like this one, or drop me a message. I always love hearing from you.

How can global brands cut through the hype and use emerging technologies to solve real business challenges? In this episode of Business Technology Perspectives, I speak with Sarah Salter, Global Head of Innovation and Platforms at Wavemaker, about how brands can unlock the true potential of innovation without losing sight of measurable outcomes.

With over 15 years of experience across industries including health, retail, and finance, Sarah brings a rich and grounded perspective to digital transformation. She shares how Wavemaker helps clients move beyond trend-chasing to deliver experiences that are meaningful, accessible, and effective. From leading AI-powered personalization strategies to shaping immersive brand moments in gaming and the metaverse, her approach is practical, human, and rooted in results.

We explore how Sarah and her team set clear KPIs for innovation, use tools like AR and VR to drive cultural relevance, and run rapid experimentation that bridges the gap between idea and impact. Sarah reflects on high-pressure public sector projects such as the NHS COVID-19 WhatsApp response, as well as creative campaigns for brands like L’Oréal and Dove that combine technology with purpose.

The conversation also explores how emerging media environments are driving a shift from passive advertising to participatory engagement. As attention becomes the ultimate currency, Sarah explains how brand storytelling is evolving through platforms like Roblox, Apple Vision Pro, and generative AI tools. She shares why gaming is becoming a vital channel for modern marketing and how experiential design is changing the way consumers connect with brands.

Sarah also discusses her commitment to diversity in tech leadership. She highlights how inclusive teams drive better innovation, the systemic changes still needed in the industry, and the importance of supporting initiatives that bring more women into tech. Whether mentoring future leaders or driving responsible AI adoption, her message is clear—technology should serve people, not the other way around.

What does it take to lead through the most human shift in technology history? In this episode of Business Technology Perspectives, I’m joined by Chet Kapoor, CEO of DataStax and former Google executive, whose tech journey began two decades ago as an intern at NeXT, just steps away from Steve Jobs. From there, Chet went on to navigate four major waves in enterprise tech: client-server, web, mobile, and cloud. Now, he believes we are entering the fifth and most transformative chapter yet—the AI era.

In our conversation, Chet draws a powerful distinction between digital transformation and what he calls “agentification.” This shift isn't just about making things faster. It is about creating autonomous AI agents that act with purpose, work alongside people, and drive effectiveness at scale. Chet walks us through real-world use cases, from personalized healthcare platforms to AI-powered education, that show how this technology is already reshaping the world.

We also explore the importance of human leadership in this new era. Chet outlines his approach to what he calls "inspired execution," a leadership model built on belief, emotional connection, and bold experimentation. For leaders looking to integrate AI meaningfully, he shares actionable advice: start with mission-critical goals, validate outcomes quickly, and scale what works.

From his recent experience at Davos to the innovation happening at DataStax, Chet offers a global perspective on where AI is headed and why businesses must act now. The conversation covers the risks of blind trust in automation, the urgency of thoughtful governance, and the need to balance technical skills with empathy and instinct.

AI is no longer a theoretical trend. It is already embedded in workflows, tools, and expectations. As we discuss how to future-proof strategy, build AI-ready cultures, and define success beyond efficiency, one question becomes clear.

Are you prepared to lead in the age of AI, or will you wait to catch up?

What happens when the world’s most essential industries—from public safety and utilities to agriculture and construction—encounter staffing shortages, outdated tools, and rising expectations from a new generation of workers? In this episode of Business Perspectives, we explore how Panasonic Connect is equipping mission-critical workforces with technology that doesn’t just meet the moment, but helps them lead through it.

Dominick Passanante, Vice President of Mobility at Panasonic Connect North America, joins the show to reveal how rugged devices like the Toughbook and AI-powered applications are transforming operations across high-stakes environments. From streamlining reporting with speech-to-text tools to using predictive analytics for wildfire response and officer safety, Dominick shares real-world examples of how modern technology is reducing admin time and boosting effectiveness in the field.

We examine how AI is helping law enforcement make smarter, faster decisions with video analysis, while utility companies are using mobile computing to detect power grid issues and manage infrastructure health. And in a workforce where expectations are rising, we discuss the role of cutting-edge technology in attracting and retaining top talent by enabling flexible, connected, and efficient ways of working.

This conversation also tackles common myths about AI—such as the fear of job replacement—and explores how human oversight remains central to successful tech integration. Dominick highlights how Panasonic’s long-standing innovation culture, combined with customer-driven development and strategic partnerships, is shaping the future of work for some of the most demanding industries.

If you're curious about how essential industries can modernize without compromising safety or service, this episode offers insights, strategies, and a glimpse into what’s next. Are today’s mission-critical workers equipped with the tools they need to serve their communities at full potential? Listen in and decide for yourself.

What does the future of work look like when the focus shifts from where people work to how they work? In this episode of Business Technology Perspectives, Neil C. Hughes is joined by James Campanini, Head of B2B Europe at Logitech, to explore how workplace technology is evolving to empower productivity, foster inclusivity, and rethink collaboration across every environment.

For over 45 years, Logitech has been connecting humans to the digital world, from the earliest mice and keyboards to today's AI-powered video conferencing solutions. James shares how the company’s philosophy has always been rooted in enabling individuals to work effectively—whether they are in the office, at home, or on the move. He explains why organizations that focus on empowering people, rather than mandating location, are seeing greater engagement, reduced burnout, and stronger productivity.

The conversation also explores how AI is already deeply embedded in Logitech’s technology, from intelligent camera systems that adjust to lighting conditions to noise-canceling audio solutions that ensure remote participants are heard as clearly as those in the room. Rather than replacing human decision-making, AI is positioned as a tool for optimizing workflows and making collaboration more inclusive and seamless for everyone.

James also addresses the controversial topic of workplace surveillance. Rather than policing employees, he advocates for a presence-based model that uses workplace insights to create better, more comfortable spaces where people can thrive. From real estate shifts to the redesign of office spaces, the future of work is about flexible, multi-purpose environments that promote collaboration without forcing outdated attendance models.

As businesses continue to balance economic pressures with employee expectations and AI reshapes the world of work, how can organizations create environments that are both productive and people-centered? Tune in to learn how Logitech is helping businesses redefine the workplace experience for a hybrid, AI-powered future.

What does it take to build a future where devices can transact with each other, where AI systems learn directly from the physical world, and where the idea of a metaverse becomes something practical rather than abstract?

In this episode of Business Technology Perspectives, we explore these questions with David Palmer, Chief Product Officer at PeerPoint by Vodafone. David recently authored The Business of Metaverse, a thought-provoking book that unpacks the convergence of Web3, IoT, and AI technologies. His insights come not only from deep research but also from his hands-on work developing what could become the world’s first Web3 IoT platform.

PeerPoint is positioning itself at the intersection of emerging technologies, giving digital identities to devices and enabling secure, autonomous interactions. From in-car payments to the orchestration of device-to-device data sharing, the platform opens doors for new forms of enterprise automation and business model innovation. These use cases may appear futuristic, but according to David, they are closer to mainstream adoption than many might think.

We also explore how the metaverse is unfolding in phases. Rather than a sudden leap into virtual reality, David outlines a step-by-step evolution beginning with embedded digital experiences and leading to full convergence. Along the way, AI agents and generative tools are expected to play a major role in enabling interoperability, creating marketplaces, and transforming the way businesses access training data.

Throughout the discussion, we examine how these technologies could remove traditional boundaries around time and place, unlocking new global opportunities. From education and real estate to finance and the creator economy, David shares how a connected world of intelligent devices may help spark innovation across sectors.

If you're interested in how next-generation infrastructure is forming the foundation for digital business, this episode offers grounded insights into what comes next.

In this episode of Business Technology Perspectives, I’m joined by Sandeep Bhattarai, Utilities Value Advisor at SAP UKI, to unpack the growing challenges facing the sector, and whether digital transformation can offer a sustainable way forward.

Recorded remotely but rooted in shared local ties—we discovered we’re both based in the West Midlands—this discussion covers the real pressures weighing on the water industry right now. From cost increases and regulatory demands to a public that’s watching more closely than ever, the sector is under intense scrutiny.

SAP’s recent research paints a stark picture: 94 percent of industry leaders believe that investment will need to increase significantly in the years ahead to meet growing demand. Sandeep shares what’s driving these pressures and highlights how gaps in digital infrastructure are making it harder to meet expectations. Together, we explore how technologies such as real-time data analytics, AI, automation, and IoT could help modernize aging water networks, enhance operational visibility, and improve regulatory compliance.

With AMP 8 set to reshape the industry from 2025 to 2030, we also ask whether digital transformation is a genuine route to progress—or whether deeper structural changes must come first.

Is the sector ready to embrace the investment needed to futureproof its operations? And can lessons from global utilities help drive smarter strategies in the UK?

Tune in to find out—and let me know: Do you believe technology is the path forward, or just one piece of a much larger puzzle?