Impact of AI:Explored

Behind compared to who? Is AI FOMO real, or are we creating it ourselves?There’s a new AI tool, model or feature every week, and plenty of people feel they’re falling behind. Charlie Hills (https://www.linkedin.com/in/charlie-hills/) reviews AI releases for his large LinkedIn following, and even he feels the pressure. In this episode, James O’Regan and Gerjon Kunst ask him where AI FOMO comes from, who people think they’re behind, and what you actually need to keep up.Charlie explains why you should pick one model and get good at it instead of switching every week, why handing your credit card to the latest AI agent is a bad idea, and why the Obsidian second-brain graph is mostly hype. He also walks through his own setup: Claude Code, a folder per platform, and self-scoring loops that keep improving an output until it meets his rubric.They also discuss why marketing teams should be using GitHub, the coming “dead internet,” and the part of his work Charlie will never hand over to AI.⏱️ Chapters00:00 Is Charlie part of the AI FOMO problem?01:06 From marketing manager to full-time AI creator03:18 Quitting the 9-to-504:37 Why growing on LinkedIn is harder now06:39 Starting over: embrace the cringe and post daily08:43 Behind compared to who? Where AI FOMO comes from11:46 Privacy risks and is anyone genuinely late to AI?14:50 Charlie’s content system: one folder per platform18:04 What is an AI loop? Rubrics and self-scoring19:57 MCP in practice22:37 How to decide which AI tools to ignore26:49 Getting Claude to test new features for you29:52 Let AI watch the YouTube videos for you31:23 Second brains: skip the Obsidian graph hype33:52 Why marketing teams should use GitHub39:07 Two hours a week? Learn Claude Code40:18 The AI bubble and the Dunning-Kruger effect43:15 One thing you can do this week44:38 Prediction: the dead internet theory comes true47:09 What Charlie won’t hand over to AI🔗 Connect with Charlie HillsLinkedIn: https://www.linkedin.com/in/charlie-hills/Substack: https://charliehills.substack.com/YouTube: https://www.youtube.com/@CharlieHillsAIWebsite: https://charliehills.ai/📚 Mentioned in this episodeCharlie’s Claude skills library: https://github.com/charlie947/social-media-skillsCharlie’s Claude Motion prompts and house-style file: https://charliehills.substack.com/p/claude-motion-graphicsDead internet theory explained: https://tech.co/news/what-is-dead-internet-theory#AI #ArtificialIntelligence #ClaudeCode #AIFOMO #ContentCreation #LinkedIn #AIAgents #FutureOfWork #PodcastSupport the show

What happens when a consultant starts training AI to replace his own business?If AI can give advice, what's left for the people who give advice for a living? Dan Boyles of Hello AI is deliberately building AI that can do his job. In this episode, James O'Regan and Gerjon Kunst ask him what that means for consulting, and why he thinks the real value is shifting to experience, mistakes made and human connection rather than knowledge.They talk about why most businesses are less ready for AI than they think (but more ready than they're scared of), why handing AI to your IT team is a recipe for failure, and why "the demo isn't adoption." Dan shares his biggest mistake since launching, how a company was spending six figures a month on Claude for the wrong reasons, and why productivity is the floor while client experience is the ceiling.They also discuss how to build a company-wide second brain and how the traditional consulting model is breaking down.⏱️ Chapters 00:00 How Hello AI went global in under two years 02:27 Why 90% of businesses still run on Microsoft 05:28 Hiring Arsenal's stadium: the Hello AI Summit 08:40 How ready are businesses really for AI? 20:47 The biggest AI myths: "It's an IT project" 25:00 Dan's biggest mistake: leading with technology 29:12 Productivity is the floor, client experience is the ceiling 31:40 Building a second brain for your business 32:48 Could Hello AI exist without AI? 42:16 The future of consulting and human intelligence 48:47 Where to find Dan🔗 Connect with Dan Boyles LinkedIn: https://www.linkedin.com/in/danhelloai/ Website: https://danboyles.ai#AI #ArtificialIntelligence #Copilot #Microsoft365 #AIAdoption #Consulting #FutureOfWork #PodcastSupport the show

Unswappable: Why AI Can't Fake Being You on LinkedIn | Impact of AI: Explored EP51"If you could swap your name for anyone else's, it's probably not a good post."Magali De Reu - Founder of the obvious yes (https://www.linkedin.com/in/magalidereu/) went viral with a screenshot showing that LinkedIn is basically all Claude now. Then hundreds of people copied it without credit, with her name still on it, proving her point twice.In this episode, we sit down with Magali, a personal branding strategist who helps people build a business on LinkedIn by showing who they are, not just what they do. We talk about why expertise has become table stakes in the age of AI, how she built her own AI operating system without losing her voice, and why human judgment is the one thing she will never hand over to a model.In this episode:- The story behind the viral "LinkedIn is all Claude" post- Why AI is commoditising expertise, and what that means for standing out- Personality first: why your brand should repel the wrong crowd on purpose- Building an AI system with named agents, and pushing back on its output- The "unswappable" test for every post you write- LinkedIn's AI writing tools, AI-written comments and the algorithm black box- AI agents, vibe coding and why human-in-the-loop still matters- AI fatigue: why the human element is about to get more valuable, not less- One thing to fix on your LinkedIn profile today01:02 Magali's viral LinkedIn post and its impact03:03 Magali's experience with AI and personal branding06:33 Getting started on LinkedIn and building a presence09:18 Lessons learned from early LinkedIn mistakes12:38 The personality-driven AI operating system15:18 The role of human judgment in AI content19:01 The importance of human touch in AI-assisted posts22:33 LinkedIn's AI features and content authenticity24:51 The future of AI and human collaboration in social mediayou can find Magali here: https://www.theobviousy.es/ or on Linkedin offcourse :-)Support the show

We hit 50 episodes and we marked it by bringing together four experts for our biggest conversation yet. When the labs racing to build the world's most powerful AI systems start warning that the race is moving too fast, should we believe them? Is this genuine caution, a legal defense being built in real time, or something else entirely?Over the next hour, our panel dismantles the "should AI slow down" debate from every angle: economic incentives, geopolitics, liability, governance, and what "slowing down" would even mean in practice. It gets candid, it gets a little chaotic, and it does not land on easy answers  which is exactly why it's worth 50 episodes' worth of getting here.🎙️ This episode's panel:Paul Slater — AI Enablement Advisor, Adobe (https://www.linkedin.com/in/paul-slater/)Louise Humpington — PGDL, LPC, AI Governance Consultant (https://www.linkedin.com/in/louisehumpington/)Dan Boyles — Founder, Hello AI Collective (https://www.linkedin.com/in/danhelloai/)Femke Cornelissen — Chief AI Transformation Officer, Wortell (https://www.linkedin.com/in/femcornelissen/)Gerjon Kunst — AI Lead, Interstellar Group (co-host) (https://www.linkedin.com/in/gerjonkunst/)James O'Regan — Lead Product Marketing Manager, Liquidware (co-host) (https://www.linkedin.com/in/jamesoreganeuc/)🔑 KeywordsAI development, AI governance, responsible AI, AI regulation, global cooperation, AI ethics, AI risk, AI innovation, AI slowdown, AI standards📌 Key topics* The race to develop powerful AI systems — and the case for caution* Global cooperation and governance frameworks* Risks of unregulated AI development* Ethics and safety standards in AI deployment* AI's real impact on organizations, society, and individual workers* The risk of AI amplifying human bias and "stupidity"* Why diverse expertise matters in AI governance* The debate over pausing AI — and what would actually justify it⏱️ Chapters00:00 Introduction to AI development race and risks01:47 The debate on slowing AI progress and safety concerns04:08 Legal and ethical considerations in AI governance05:57 The role of global cooperation and shared standards07:50 Economic implications of AI slowdown and innovation09:57 Understanding what 'slowing down' means in practice12:01 The importance of testing, benchmarks, and accountability13:58 The influence of geopolitics and international relations16:06 The real impact of AI on society and business17:49 The importance of human expertise and judgment in AI19:49 Risks of homogenized AI outputs and loss of diversity22:07 Media influence, misinformation, and public perception23:47 Historical parallels: arms trade and nuclear treaties25:53 The need for transparency, oversight, and collaboration27:46 The challenge of responsible AI deployment in organizations30:00 The future of AI regulation and ethical standards32:07 The role of AI in organizational strategy and growth33:58 Balancing innovation with safety and societal impact36:08 The importance of diverse expertise and multidisciplinary approaches37:54 The risk of AI amplifying human flaws and biases39:56 The democratization of AI and its implications42:01 Legal and ethical challenges in AI applications43:59 Humor and human oversight in AI-generated content46:01 The cultural and societal impact of AI47:57 The importance of responsible innovation and leadership49:59 The future outlook: collaboration, regulation, and innovation52:05 Final thoughts and call for responsible AI developmentSupport the show

In this episode we sit down with Lee Crossley - Consultant CTO | Overshow Co-Founder (https://www.linkedin.com/in/leecrossley/). Lee shares insights on the future of local AI models, their applications, and the evolving landscape of AI technology, emphasizing the importance of local models for privacy, security, and efficiency.Key topics* The evolution of local AI models and their applications* The importance of model routing and hybrid AI strategies* The role of hardware and device capabilities in AI deployment* Industry trends and the impact of major players like Apple, Google, and Microsoft* Security, privacy, and compliance considerations in local AILinks & resources mentionedOllama – run local LLMs on your machine – https://ollama.comGoogle Gemma – open-weight models for local use – https://ai.google.dev/gemmaPerplexity – hybrid/local model routing with PII handling – https://www.perplexity.ai/hub/products/portable-computerAnthropic Claude & Claude Code – https://www.anthropic.comAzure IoT Edge & on‑prem AI options – https://learn.microsoft.com/azure/iot-edgeApple Intelligence – on-device AI strategy – https://www.apple.com/apple-intelligence/Support the show

In this episode, James sits down with Steve Wilson - Leading in AI and Cybersecurity - Exabeam, OWASP, O’Reilly (https://www.linkedin.com/in/wilsonsd/), who is stepping in for Gerjon while he's on holiday.Steve discusses the recent AI security incidents, the risks of AI agents escaping sandbox environments, and practical strategies for cybersecurity in the age of AI. He emphasizes the importance of basic security principles, understanding AI components, and fostering ongoing education to manage AI risks effectively.They cover:* The Hugging Face / “Steve” agent incident and what it reveals about AI risk* Why prompt injection is now treated as “inevitable as death and taxes” and how to design systems that survive it* Treating AI agents like digital employees: identities, job descriptions, least‑privilege access, and monitoring* AI FOMO vs. FUD: how business pressure and vendor fear‑mongering drive bad security decisions* Practical next steps for CISOs and security teams over the next 12 monthsKey takeaways* Stop trying to prevent prompt injection; instead, limit blast radius with tight permissions, unique identities, and clear “job descriptions” for agents.* Use existing identity and monitoring tools first; don’t wait for perfect “non‑human identity” products before you start governing agents.* Build an insider‑threat mindset for AI: malfunctioning, misaligned, and subverted bots are all variants of the same problem.Resources mentioned* OWASP Top 10 for Large Language Models (latest version) (https://genai.owasp.org/resource/owasp-genai-llm-top-10-2026/)* Steve’s open‑source agent security scanner: Prax2n (https://github.com/open-agent-ai-security/praxen)* Exabeam’s open‑source agent logging library: Observra(https://open-agent-ai-security.github.io/observra/)Nick Bostrom, Superintelligence (paperclip optimizer thought experiment)(https://cepr.org/voxeu/columns/ai-and-paperclip-problem)and the website of Nick Bostrom (https://nickbostrom.com/)Connect with Steve WilsonLinkedIn: https://www.linkedin.com/in/wilsonsd/If you’re responsible for AI, cloud, or security in your organization, this is the “back to basics” episode you need before you deploy your next agentChapters00:00 AI agents escape sandbox to cheat on benchmarks03:10 The importance of paying attention to AI security risks05:01 Tools and strategies for securing AI applications06:24 Monitoring AI agents and giving them clear job descriptions07:20 The current state of AI monitoring in organizations08:48 Prompt injection vulnerabilities and defenses10:54 Building systems resilient to prompt injection12:15 Controlling AI boundaries with role-based access14:06 Using existing identity management for AI agents15:09 Balancing FOMO and FUD in AI adoption16:24 The need for cybersecurity education on AI components17:22 Evaluating new cybersecurity tools for AI security19:31 Lessons from cloud migration applied to AI security23:00 The risks of experiments with dangerous AI models24:23 The goal-seeking nature of AI and its risks26:08 AI goal focus and the risk of unintended outcomes27:27 The metaphor of releasing the genie and AI risks28:22 The importance of basic security controls and education41:26 The role of open source and transparency in AI security45:01 The importance of internal discussions on AI risk managementSupport the show

In this episode, Gerjon sits down with Jim Moyle (Principal Product Manager for Windows Cloud (https://www.linkedin.com/in/jimmoyle/), stepping in for James while he's on holiday to unpack how combining a "second brain" with agentic AI has completely reshaped his day-to-day work over the past three months. Gerjon Mentions Chris Brear but that should be Dave Brear our guest from episode 40 (https://youtu.be/ZtI8kIfYTpY)The conversation covers:Windows 365 for Agents — a new flavor of Windows 365 built for AI agents (not humans) to log into and operate, complete with its own Entra ID identity, governance, auditability, and a real-time WebRTC observability feed so you can watch — and step into — what an agent is doing.Why "computer use" beats MCP sometimes — Jim explains when driving mouse, keyboard, and the accessibility tree directly is more practical than hunting for (or trusting) an MCP server, especially for one-off tasks or legacy apps with unreliable APIs.Consumption-based pricing — a pay-per-hour model for agent VMs, plus a real demo: 3,500 lines of legacy PowerShell for app packaging replaced by a 12-line agent instruction set, with better resilience to change than a brittle script.The Second Brain workflow — how getting context, audience, and constraints right up front (before going agentic) drastically cuts hallucination, and why Jim treats it as the essential foundation before automating anything.What it actually costs — Jim breaks down his own token usage (216 million tokens/month, ~95% cached) to land on a real-world estimate of roughly £80–90/month.Why EUC teams are made for this moment — Jim's case for why end-user computing professionals already have the security, compliance, and workflow skills to own the agentic AI wave inside their organizations, and how to get started.00:00 Introduction to Jim Moyle and AI Workflow Revolution01:19 Jim's Journey into AI and Workflow Transformation02:33 How Windows 365 for Agents Works03:38 Scaling and Security in AI Workflows05:34 Controlling and Observing AI Agents in Action06:29 Unlocking Applications Without APIs07:47 Error Handling and Human-in-the-Loop09:37 Identity and Security for AI Agents11:23 Error Reporting and Troubleshooting12:49 Scaling and Cost Models for AI Agents14:01 Getting Started with AI and Second Brain15:29 Integrating Second Brain with Agentic Workflow19:35 Enhancing Focus and Productivity with AI22:58 Cost of Maintaining a Second Brain26:09 The Role of EUC Professionals in AI Era29:28 Adoption and Use Cases of Windows 365 for Agents31:21 Automating App Packaging with AI32:04 Resilience and Fault Handling in AI Workflows33:21 Testing and Scaling AI Instructions34:12 Getting Started with AI for IT Professionals36:22 Final Thoughts and Future Outlook resourcesWindows 365 for Agents - https://www.microsoft.com/en-us/security/business/endpoint/endpoint-managerStarting with windows 365 for agents: https://www.microsoft.com/en-us/windows-365/agents#Get-startedplaying around with Windows 365 agents: https://learn.microsoft.com/en-us/microsoft-copilot-studio/use-cloud-pc-poolSecond Brain Methodology - https://fortelabs.co/blog/second-brain/ or https://www.gerjon.com/?p=1819Support the show

Is AI Overhyped or Underestimated? Examining the Reality and Potential of Artificial IntelligenceIn this episode, we explore the gap between AI hype and reality, highlighting both the risks of overhyped claims and the genuine benefits AI offers across sectors. Join us as we discuss real-world failures, success stories, emerging trends, and practical principles to harness AI responsibly and effectively.Key Topics:The exaggerated promises and pitfalls of AI deployments in companiesCase studies of AI failures: data mishaps, security breaches, and unintended consequencesThe impact of AI on sectors like weather forecasting, healthcare, and cybersecurityThe importance of guardrails, governance, and ongoing oversight in AI projectsCost considerations: public versus private AI and the shift towards consumption-based modelsThe role of AI as a workspace interface and the evolution of agent-driven workflowsThe skills gap and human readiness for AI adoption in organizationsFuture predictions: multimodal AI, reasoning systems, and new AI interface paradigmsPractical principles for integrating AI into business securely, sustainably, and responsibly Timestamps:03:08 - How AI is perceived as overhyped and underhyped simultaneously04:19 - The challenge of ROI and AI deployment in enterprise environments05:14 - Case studys of AI getting it wrong12:15 - Positive impacts of AI in weather forecasting, drug discovery, and energy grid optimization16:56 - Private AI versus public AI: benefits and considerations23:25 - Microsoft’s AI agent ecosystem and governance tools like Agent 36528:35 - Realistic productivity gains: time savings vs. business value36:20 - The talent war in AI and the skills gap in organizations37:34 - The exponential growth of AI episodes and content knowledge base39:10 - Analyzing top insights from over 40 episodes, summarized via AI51:00 - Reflecting on AI predictions for 2025: what was accurate, what missed the 56:00 - Key insights for AI going forwardResources & Links:Podcast website: https://impactofaiexplored.com/Presentation from Expertslive: https://impactofaiexplored.com/wp-content/uploads/2026/07/Expertslive-2026-AI-Hype-vs.-Reality.pdfAgents 365: https://www.microsoft.com/en-us/microsoft-agent-365MCP server: http://mcp.impactofaiexplored.com/mcp Support the show

In this episode we sit down with Matt Neil - Founder @ Artificia1 (https://www.linkedin.com/in/mnealaipro/) to talk about why AI isn’t really a tech project, but a business problem that most SMEs are still struggling to frame correctly. We dig into real‑world adoption stories, how to prove ROI with things like LLM leaderboards and management metrics, and why so many AI and agent projects are destined to be rolled back if they ignore fundamentals like training and change management. Along the way we get into Copilot, OpenAI/OpenClaw vs. Microsoft Scout, token costs, EU AI Act training requirements, and why “train the team and bring them on the journey” is still the most underrated AI strategyKey  topics* The importance of training and adoption in AI projects* Challenges faced by SMEs in AI adoption* ROI measurement and cost management in AI initiatives* The role of leadership and mindset in AI successresourcesMatt Neil - LinkedIn - https://www.linkedin.com/in/mattneil/Matt's Company - https://artificia1.com/Open Claw Video - Stripe CTO - https://www.youtube.com/watch?v=l9wzs_QIyp0Microsoft Copilot - https://www.microsoft.com/en-us/microsoft-365/copilotGartner AI Market Report - https://www.gartner.com/en/articles/strategic-predictions-for-2026EU AI Act - https://eur-lex.europa.eu/legal-content/EN/TXT/?uri=CELEX%3A52021PC0206Support the show

In this interesting episode of Impact of AI: Explored, Gerjon and James talk with Rich  Gibbons  - Head of FinOps, GreenOps, and Microsoft Intelligence at Synyega (https://www.linkedin.com/in/rich-gibbons-microsoft-licensing/). Rich discusses Microsoft's new consumption-based AI licensing models, including CoPilot, CoWork, and Scout, and explores their implications for organizations. We delve into cost forecasting, management challenges, and strategic considerations for adopting AI at scale.Key  topics* Microsoft's shift to consumption-based AI licensing* Implications of Co-Pilot, Co-Work, and Scout for organizations* Cost forecasting and management challenges with AI* Strategies for controlling AI-related expenses* The impact of AI on enterprise software costsChapters00:42 Introduction to Microsoft's New Licensing Model03:24 Understanding Co-Pilot and Co-Work06:04 The Shift to Consumption-Based Billing08:40 Cost Implications for Organizations11:24 Evaluating ROI and Financial Discussions13:50 The Future of AI in Organizations16:54 Managing Costs and User Quotas22:04 Navigating Credit Usage and Cost Management26:12 The Complexity of Consumption-Based Models29:47 The Evolution of SaaS Pricing Models33:46 Understanding AI Cost Efficiency Claims37:47 Strategizing AI Implementation in OrganizationsResourcesRich's Blog: https://cloudywithachanceoflicensing.com/Microsoft Co-Pilot - https://www.microsoft.com/en-us/microsoft-365/copilotMicrosoft Co-Work - https://www.microsoft.com/en-us/microsoft-365/copilotMicrosoft Scout - https://blogs.microsoft.com/blog/2023/05/26/introducing-microsoft-365-copilot-scott/Support the show