AI adoption in financial and professional services is being sold as a technology story. Olivia Larkin makes the case that it is really a workforce transformation story. In her words, ‘AI transformation is change management and it needs to be managed in that way by a business.’ Olivia leads skills and workforce policy at the City of London Corporation. She works across the UK, not just the Square Mile. She makes an interesting distinction between AI talent, a narrow, deep group that builds, governs, assures, and improves AI. Whereas, AI skills are for the wider workforce, because AI use will spread across all functions in organisations. She argues that one of the biggest AI risks is not investing in upskilling. Only around one in five UK employees currently receive AI training. Time is the everyday blocker, for employers and employees. Protected learning time changes the picture. Regulation also slows momentum. Firms face uncertainty when existing regulatory requirements meet new AI use, with grey areas that create caution and delay. Olivia still lands on a positive position. With responsible governance, AI can lift productivity and improve customer experience. The prize comes with a condition. Focus on redeploying people, not reducing headcount. Build trust, so staff do not see learning as a route to replacement. London, in her view, can become a global reference point for trusted AI in financial and professional services, if workforce investment keeps pace with the technology. Chapters 00:00 The City of London Corporation 03:33 Skills and Workforce Policy in Financial Services 06:18 AI Skills vs. AI Talent 11:01 Challenges and Risks for Companies 17:09 Employee Challenges in AI Adoption 20:06 Regulatory Challenges in Financial Services 23:27 AI's Impact on London's Future 27:47 Successful AI Strategies in Organisations 30:42 Future Directions for AI Adoption

In this episode of The AI Adoption Podcast, I speak with Sumeet Bhatia from Cisco about the changing role of AI in defence and security. The discussion stays close to operational reality rather than abstract theory. We explore how AI now operates at a speed that humans cannot match. That speed allows threats to be detected earlier and systems to respond before damage spreads. At the same time, it creates new risks around trust and control. Sumeet explains that data purity, provenance, and governance are not technical hygiene issues but strategic and operational warfare necessities. Data integrity runs through the entire conversation. Poisoned data can quietly distort AI behaviour, while misinformation can undermine confidence in the information presented to human decision makers. In defence environments, that loss of confidence can be as damaging as the attack itself. Explainability becomes critical when decisions carry serious consequences. Opaque models make it difficult to understand how conclusions are reached. Without clear decision trails, accountability weakens and trust erodes under pressure. We also discuss the rise of multi-vector attacks. Disruption no longer arrives through a single route. Infrastructure, cyber systems, and information channels can all be targeted together. AI helps by recognising patterns across these fronts before instability escalates. The episode also looks at AI in operational contexts. Defence logistics faces challenges similar to large commercial supply chains. AI can support planning, predict failure points, and improve crisis response when conditions change quickly. Lessons from defence extend well beyond the military domain. The need for speed must be balanced with verification and human judgement. Policy continues to struggle to keep pace with technical capability and developments. Human oversight remains essential where lethal decisions are involved. Looking ahead, effective human–AI teaming will depend on new training approaches and a serious investment in skills. Chapters 00:00 The Rise of Autonomous Cyber Warfare 03:00 AI in Defence and Security 05:58 AI's Role in Threat Detection 08:57 Human-AI Collaboration in National Security 11:59 Data Integrity and Misinformation Challenges 14:50 The Explainability Crisis in AI 17:40 Multi-Vector Attacks and Their Implications 20:54 Operational Enhancements Through AI 23:59 Lessons from Defence for the Private Sector 27:02 Policy Considerations for AI in Defence 30:02 The Future of Human-AI Teaming

Cash transactions are disappearing fast in the UK, but five million people still rely on cash payments. That tension sits at the heart of this episode. In my conversation with John Howells, Chief Executive of LINK, we explore the sharp fall in cash use, from six in ten payments a decade ago to fewer than one in ten today, and the consequences that follow. For most people, digital payments bring convenience and choice. For others, the elderly and those less comfortable with technology for instance, the pace of change creates real risk. John explains that cash infrastructure declines faster than people adapt. As usage falls by around ten per cent a year, ATMs, branches and cash accepting shops disappear unevenly. Banking hubs emerge as a practical response, shared branches on the high street that protect face to face access when the last local bank branch closes. We also look ahead to digital money. Stablecoins, tokenised bank deposits and central bank digital currencies point to a future where payments carry richer data and support smarter services. That future brings opportunity, including reduced fraud and more flexible support for vulnerable users, but only if inclusion is designed in. A striking argument in this episode is about responsibility. John suggests that banks should not carry the cost alone. Large technology firms such as Amazon, Meta and Google also benefit from the shift to digital payments and should contribute to sustaining the system that underpins it. This episode is a reminder that payment systems are part of the social infrastructure and community fabric, not just technology. Chapters 00:00 The Cash Dilemma: Understanding the Need for Cash in a Digital World 03:00 The Evolution of Payments: From Cash to Digital 06:07 The Vulnerable Population: Who Are the 5 Million Cash Users? 08:45 The Role of Technology: Bridging the Gap for Cash Users 11:58 Banking Hubs: A Solution for Access to Cash 14:52 The Future of Payments: Trends and Predictions 17:55 The Impact of Digital Payments on Society 20:49 The Role of AI in Financial Inclusion 23:50 The Multi-Money Approach: Stablecoins and Digital Currency 26:42 Preparing for the Future: What Companies Should Do

In this episode of The AI Adoption Podcast, I speak with Sydney MacGregor from HSBC Innovation Banking about a critically important aspect of AI adoption: funding, risk, and scale. Sydney works with more than 250 enterprise software companies, most of them building AI into their core products. She shares a clear view of the UK AI market, from the surge in early-stage activity to the harder reality of scaling beyond Series A. We discuss the rise of AI agents over chatbots, investor expectations shaped by rapid revenue growth, and the pressure founders face when competing with businesses scaling from zero to tens of millions in months. Sydney explains why later stage funding remains a structural weakness in the UK, even with strong research, talent, and early capital. The conversation moved onto venture debt, an area that often feels opaque to founders. Sydney explained how banks assess risk in AI businesses that can be cash-burning, the importance of investor syndicates, and the need to avoid over-leveraging while still enabling growth. We explored the role banks play supporting their AI businesses beyond capital, including global expansion, sector expertise, and trusted relationships. We close with a forward look at workflow automation, AI governance, and the conditions needed for UK AI companies to scale and stay in the UK. This episode is a rich discussion about growth, discipline, and realism in the AI economy. Chapters 00:00 The Future of AI in Corporate Workflows 03:05 Current State of AI Companies in the UK 07:08 Government Support and Investor Appetite 09:46 Investment Trends in AI Sub-sectors 12:10 Regional Investment Expansion Beyond London 14:16 Ensuring the UK Remains an AI Hub 15:58 Supporting AI Startups Beyond Capital 22:18 The Lifecycle of AI Startups 27:32 Key Trends and Future Opportunities in AI

This episode with Chris Blatchford, CTO at Kingfisher, quickly became a conversation about leadership mindset and AI technology. Kingfisher is best known through its brands such as B&Q and Screwfix. Chris described an organisation that treats AI as a board-level capability. Foundations first, so teams can build safely and repeatedly rather than improvising. Kingfisher’s data lake, Nucleus, and its AI framework, Athena, sit underneath everything. That choice signals discipline and intent. AI becomes an operating model, not a sequence of use case pilots. From there, the focus shifts to customer focused innovations, personalisation and value, not superficial novelty. Customer-facing AI stays anchored in a simple outcome: customers reach the right product fast. Chris spoke about moving beyond keyword search towards conversational and semantic search, then using context such as prior searches, purchases and loyalty behaviour to sharpen relevance. He shared a hard-edged commercial marker too. Recommender systems contributed around 10% of e-commerce sales last year, with ambition to grow that through 2026. For boards, the supply chain segment will resonate. Chris described near real-time visibility at SKU level, including fulfilment timing and shipment progress, supporting faster decisions on replenishment and stock gaps. It is operational clarity in a world full of noise. Chris declared that ensuring Kingfisher rolled-out AI responsibly as one of the areas, alongside cybersecurity, that genuinely keeps him awake. Again, this reflects the depth of commitment to good AI governance, bias checks, explainability, controlled customer rollouts, plus tech-literate executives who press on risk as well as upside. Innovation is encouraged, within a bounded context with rules. His view on AI’s impact on jobs and skills was measured and human-centric. AI tools support colleagues rather than remove them, freeing time for higher value work. Roles evolve through better prompting, stronger curation of information, and sharper critical thinking, with data-savviness becoming essential. This episode is for boards and senior teams who want to scale AI adoption that holds up under scrutiny, delivers value, and earns trust. Chapters 00:00 AI in Retail 02:57 Kingfisher's AI Strategy and Innovations 06:08 Enhancing Customer Experience with AI 08:47 Dynamic Pricing and Its Implications 11:49 Supply Chain Visibility through AI 14:45 Responsible AI Implementation 17:55 Impact of AI on Jobs and Workforce 20:47 The Effects of AI on Retail Jobs 23:49 Skills for the Future Workforce 26:56 Supporting SMEs in AI Adoption 29:41 Advice for Large Organisations on AI Adoption

Jonathon Palmer from LinkedIn and I spoke about creativity emerging as a serious competitive advantage in AI-driven business. Jonathon made a striking point: AI makes execution easier, so the advantage shifts to the human ability to originate ideas, reframe problems, and stay curious. The discussion also challenged a common assumption in B2B ecosystems. Emotion carries more weight than logic in real decisions. People engage Brands that help people feel confident in their choice will stand out in a world shaped by AI abundance, endless options, and fast decisions. We covered the changing landscape of work. A shift is underway from job title-based hiring to skills-based hiring. Jonathon shared LinkedIn data suggesting professionals entering work today will hold twice as many jobs as someone starting 15 years earlier. As AI adoption expands, careers adaptability and lifelong learning move from a nice-to-have to a baseline expectation. A theme running through the conversation was shared responsibility. Creativity no longer sits in a single department. It becomes everyone’s work, supported by psychological safety, rigorous experimentation, and high standards. This episode brings together creativity, emotional intelligence, confidence in brand decisions, skills-first careers, and the real tactics people can use to stay visible and employable as AI reshapes work and workplaces. Chapters 00:00 The Importance of Creativity in Business 09:54The New Marketing Landscape 20:05 The Evolution of Brand Identity 29:59 Adapting to the Future of Work

AI adoption often looks rational on paper while feeling human in practice. That insight sat at the centre of my conversation with Ian Smith from Baseline, and it informed the tone of our discussion. Ian spoke about reaching a point in his career where technology no longer carried the whole story. Lived experience moved to the forefront. People bring anticipation, uncertainty, curiosity and concern to AI programmes. These emotions shape AI adoption as much as any technical roadmap. Efficiency continues to matter, yet it arrives with consequences. Organisations gain speed and clarity, yet roles evolve, responsibilities shift, and expectations change. Vision sets direction, yet lived experiences determines whether progress becomes real or remains notional. Ian shared his views around personal agency. AI now gives individuals the ability to build, learn and create with a freedom that previous technologies didn’t allow. AI systems offer new routes into capability development and new forms of contribution that feel empowering. That momentum brings a parallel challenge. As personalised, agentic systems expand, boundaries around trust and control begin to stretch. Organisations face new questions about governance, oversight and responsibility when capability sits outside the structures that once shaped it. Trust carries real weight in this moment. Trust in systems, trust in data, trust in human judgement. The balance between them influences decisions, interactions and outcomes. Automating trust remains far more complex than automating efficiency. Ian finished by returning to something firmly human. Augmentation has always been part of the human story. The deeper fulfilment still comes from connection, shared presence and the moments that remind us we remain social beings even as digital intelligence becomes more present in our lives. This episode offers a steady, balanced view of AI adoption. It acknowledges the trade-offs while recognising the possibilities, and it invites listeners to consider both with clarity and care. Key messages • The lived experience around technology is crucial for organisations. • Leadership should focus on accountability and adoption, not just vision. • AI adoption is as much about people as it is about systems. • Trust and ethics are paramount in the deployment of AI. • The consumer-centric approach is reshaping technology services. • AI can empower individuals to customise their own solutions. • There is a paradox in AI replacing human jobs while creating new opportunities. • Human diversity must be preserved in the age of AI. • Ethical governance is essential for AI systems. • Maintaining human connection is vital in a technology-driven world. Chapters 00:00 The Human Experience in Technology 03:03 Leadership and Accountability in Technology Adoption 05:37 The Paradox of AI and Human Displacement 08:43 Consumer-Centric Technology and Customisation 11:26 Trust, Ethics, and Governance in AI 14:17 The Future of Work and Individual Agency 16:52 Balancing Technology and Human Connection 21:14 Tacit Knowledge and AI 24:09 Governance and Shadow IT 27:50 Augmenting Knowledge 32:07 Retaining A Sense of Humanity

In this episode I speak with Paul O’Sullivan, SVP of Solution Engineering for the UKI and Chief Technology Officer for the UK, from Salesforce. Paul traces 75 years of AI development, from early machine intelligence ideas to the breakthroughs that brought us to today’s agentic AI era. Paul explains the shift from traditional workflows to digital workers operating alongside people. AI-enabled reasoning, automation and data-driven decisions now open space for employees to focus on meaningful tasks rather than repetitive activity. Paul outlines the elements senior managers must consider when forming an AI strategy. These include ethics, workforce readiness, data quality, resilience and long-term sustainability. He stresses that many AI pilots collapse because they lose focus on business value or fail to carry teams with them. Data chaos is common in many organisations and progress is possible by concentrating on workflows rather than attempting a huge enterprise-wide data project. Paul explores the dark side of AI, including malicious code, deepfakes, identity theft and large-scale misinformation. Boards need clear oversight and consistent guardrails. Paul discusses the build–buy–hybrid debate. The rapid cycle of AI development, model updates and new controls means few organisations can produce everything alone. Choice of partners becomes critical. We end the conversation with Paul’s view of near-term AI advances: robotics with touch-sensing algorithms, multimodal models, self-adjusting systems and strong growth in sectors such as logistics, healthcare and financial services. In two years from now, will the landscape be almost unrecognisable? Chapters 00:00 The Transformative Power of AI 04:53 Reimagining Workflows with Agentic AI 08:14 Building a Strong AI Strategy 12:55 Data Management Challenges 18:23 The Dark Side of AI 21:50 Build, Buy, or Hybrid: AI Solutions 27:23 The Future of AI Technologies

In this episode of The AI Adoption Podcast, I speak with Heather Black, CEO of Supermums, about reskilling for the rapid changes brought by AI. We discuss changes in job roles and skills such as project management, business analysis, change management. Heather explains that AI literacy is essential, yet people are fearful when approaching new technology. Ways of overcoming this include community learning and knowing your preferred learning style, which can help people stay confident and productive. Heather explains the growing demand for AI-related roles, the rise of AI agents, and that organisations need strong leadership and structured change management to introduce these tools well. She talks about the responsibility individuals now have for their own learning, and what governments can do to ensure people are not left behind as AI transforms the workplace. Find out why Heather says "fear of AI is holding back more careers than AI itself". Chapters 00:00 Empowering Women in Tech 04:07 Adapting to Changing Job Landscapes 07:01 Upskilling for the Future 11:21 AI in the Workplace 14:42 The Importance of Change Management 18:21 Continuous Learning as a Core Competence 21:23 Learning Styles and Personal Responsibility 26:05 The Role of Leadership in AI Adoption 31:30 Government Policies for AI Workforce Development