The AI Adoption Podcast where cutting-edge artificial intelligence meets real-world relevance. The show offers an accessible, approachable take on some of the most complex topics in AI, making the effects of AI understandable and engaging for everyone, from curious beginners to tech-savvy professionals and business leaders. Each episode features in-depth conversations with leading AI policy makers, researchers, innovators, regulators, ethicists, and thought leaders. You will hear diverse voices, even sceptics, ensuring balanced and lively discussions, exploring the adoption of AI.
The AI Adoption Podcast
Claim This Podcastby Professor Ashley Braganza
5.0(1 reviews)
63 episodes
Updated Daily
Accepts GuestsHas SponsorsLocation 🇬🇧
43
Podcast Authority
BetaFairBased on show quality, social media presence, reviews, charts, and more
Quality60
Social0
YouTube66
Engagement0
Podcast Overview
The AI Adoption Podcast where cutting-edge artificial intelligence meets real-world relevance. The show offers an accessible, approachable take on some of the most complex topics in AI, making the effects of AI understandable and engaging for everyone, from curious beginners to tech-savvy professionals and business leaders. Each episode features in-depth conversations with leading AI policy makers, researchers, innovators, regulators, ethicists, and thought leaders. You will hear diverse voices, even sceptics, ensuring balanced and lively discussions, exploring the adoption of AI.
Language
🇺🇲
Publishing Since
4/10/2025
Unlock The Full Podcast Authority Score Report
See how your podcast performs across key metrics
43
Podcast Authority
BetaFairBased on show quality, social media presence, reviews, charts, and more
Quality60
Social0
YouTube66
Engagement0
8
Excellent Areas
0
Good Performance
11
Growth Opportunities
excellent
Publishing Consistency
Every 7 days
Performing excellently!
poor
Episode Thumbnails
Recommendations available
Unlock the full report to see detailed tips
+16 More Metrics
Unlock comprehensive insights including:
- • YouTube presence analysis
- • Social media reach metrics
- • RSS compliance scoring
- • Podcast 2.0 features
- • Technical standards
What's Included in Your Full Report
Detailed Analytics
- Complete breakdown of all 19 authority metrics
- Personalized recommendations for each metric
- Industry benchmarks and comparisons
- Technical RSS feed analysis and compliance scoring
Growth Strategies
- Step-by-step action plans for improvement
- Quick wins to boost your score immediately
- Pro tips from successful podcasters
Get your free podcast insights report
See how your show performs across every key metric
Instant delivery
No spam
Attract Better Guests
High authority scores make your podcast more attractive to industry leaders and influencers who want to appear on credible shows.
Secure Sponsorships
Sponsors look for podcasts with proven authority and engagement. Your score demonstrates your podcast's value to potential partners.
Grow Your Audience
Understanding your strengths and weaknesses helps you make data-driven decisions to expand your listener base effectively.
Reach the team behind The AI Adoption Podcast
Verified contact details for this show aren't on file yet — sign up to get notified when they land.
Recent Episodes
August 13, 2026
AI Tools Drive New Crimes and Social Behaviours, and Policing Is Behind
<p>Criminals and members of the public are learning and using AI faster than the police can respond. In the parts of policing that handle domestic abuse, non-consensual intimate images and spiking, that gap is not abstract. It shapes what happens when an officer reaches a victim at three in the morning.</p><p>Claire Hammond, temporary Detective Chief Superintendent at the National Centre for Violence Against Women and Girls and Public Protection, argues that AI belongs in these cases precisely because they are the hardest, and that the human must keep every decision.</p><p>The conversation sets out a closed AI agent, named M, embedded in the Centre’s digital toolkit and live across 43 forces. Claire makes the case that M’s value is not speed alone but pattern: an officer treating one crime in isolation can be prompted to consider coercive control, stalking, or a wider history of abuse. She is candid that policing was pushed into AI rather than choosing it, and that senior leaders carry more caution than frontline officers who adopt anything that saves time. She holds one line throughout: AI supports the officer, it does not replace the decision maker.</p><p>Highlights:</p><p>• M is a closed agent, built to answer only from national guidance rather than learn from open data, giving one national response at any hour.</p><p>• Deepfake abuse images are now produced at the touch of a button, where they were once cut from a catalogue and pasted by hand.</p><p>• AI drafts overnight handover summaries, so an oncoming officer inherits the case rather than a two-line email.</p><p>• Disclosure that once meant reading 20 to 30 years of records is condensed for a human to check and decide.</p><p>• “Criminals are using AI at such a speed as well. And they’re learning a lot quicker than we are.”</p><p>For an account of AI adoption where the stakes are highest and the human stays in charge, this conversation is worth your time.</p><p>00:00 Introduction to AI's role in policing and public safety</p><p>02:17 Claire Hammond introduces the NCVPP and her role</p><p>04:41 The NCVPP's work in AI and police training</p><p>06:46 How AI is changing police work and crime detection</p><p>08:14 Detecting AI-enabled crimes like deepfakes and fraud</p><p>09:24 Examples of AI in case file management and disclosures</p><p>11:36 Cultural challenges and trust in AI within police</p><p>13:23 Impact of AI on public understanding and safety</p><p>17:52 Using AI to support decisions in violence against women and girls cases</p><p>20:21 AI's role in identifying coercive control and domestic abuse patterns</p><p>21:12 Future plans for expanding AI use in police disclosures and protective orders</p><p>24:26 Governance and ethical safeguards for AI in policing</p><p>26:50 Building public trust and engagement with AI tools</p>
August 6, 2026
Every professional is an AI manager, whatever their job title
<p>Stillpoint employs only senior experts and hands the rest to agents. There are no junior staff. The productivity this promises still meets a limit set by human beings.</p><p>Chris Donahoe, Co-founder of Stillpoint, a corporate affairs firm built to be AI native, argues that the binding constraint on agentic work is now biological rather than technical.</p><p>Chris explains that building an AI native firm is an exercise in destroying assumptions, not a technology project, and that many companies use AI merely to speed up an operating model that may no longer deserve to exist. He describes inverting the professional services pyramid: senior human talent only, an entirely agentic support layer, and delegation to teams of agents rather than junior colleagues. The gain has a ceiling, because human reading speed, attention, and judgment have not risen since 2022, so the volume agents produce backs up at the last mile of review. Chris also names a management shift, arguing that even a solo operator now runs a team of agents while no orchestration tool yet exists to coordinate them.</p><p>• "It's really an exercise in destroying assumptions": the starting point is questioning why the business works the way it does.</p><p>• The talent pyramid inverted: partner and managing director level humans only, no junior staff, an entirely agentic support layer.</p><p>• The biological bottleneck: agents take work to ninety per cent done, but customer ready output depends on a person's finite hours and attention.</p><p>• "Even solo operators are managers now": scoping, delegation, feedback, and judgment become baseline skills for every professional.</p><p>• A candid tools verdict: Claude is strong at formatting Word, Excel, and PowerPoint, yet in Chris's view a poor copywriter, so he routes drafts through ChatGPT and back.</p><p>Press play for an account of running a firm where the agents never tire and the people set the pace.</p><p>Chapters</p><p>00:00 Building an AI native company: destroying assumptions</p><p>04:30 Encouraging experimentation with AI tools</p><p>07:07 Characteristics of an AI native firm versus traditional</p><p>08:13 Talent structure in AI native firms</p><p>10:28 Challenges of managing a human-AI hybrid organisation</p><p>12:54 The need for orchestration tools in AI workflows</p><p>13:54 Skills for managing in an AI native environment</p><p>17:03 Management and coordination of AI agents</p><p>19:35 Managing interdependencies and orchestration</p><p>23:43 Human biological bottleneck and work volume</p><p>27:40 Implications of human speed limits in AI workflows</p><p>34:04 Recruiting and developing talent for AI native organisations</p><p>37:28 AI native firms and future challenges</p>
July 30, 2026
Middle Management Has No Place in the Agentic AI Economy
<p>Ten years in the same sales role now predicts AI resistance. Leo Rogers has seen the pattern often enough to name the mechanism: representatives who hit their number quarter after quarter were never questioned on their method, so the method was never examined. His verdict is that AI adoption is a people problem as much as a technology problem.</p><p>Leo Rogers, co-founder and CEO of Curvo, which builds a real-time execution layer for sales teams, argues that knowledge has become a commodity and that the need for generalists is on the rise.</p><p>He makes the case for skill stacking, holding roughly 30 per cent of several disciplines, enough to set strategy and to judge an output, with agents supplying the depth. He sets a limit on his own argument: a non-designer who commissions a prototype from an agent still cannot say whether the design system is robust. This means prior exposure remains the gate on quality. He describes orchestration as a generalised agent sitting above specialised agents, deciding which to mobilise and reconciling what they report back, and treats it as the change that makes materially more complex work possible. He also predicts an inversion of the labour market in which agents appoint humans for the last mile, on the grounds that an agent in a sandbox cannot shake a hand or fix a chair.</p><p>● The laggard profile: decades of steady growth on the SaaS wave, leadership motivation moving from growth to preservation of the founders’ / managements’ wealth, then private equity arrive with two or three years ‘to squeeze the lemon’.</p><p>● Resistance mapped to tenure: one year, three years, five years, and at ten years AI adoption becomes much more challenging, with reps coasting on their black books rather than the CRM.</p><p>● Robotics without the humanoid: a bricklaying machine with no legs working at the rate of five bricklayers, set against a humanoid taking half an hour to place a mug in a dishwasher.</p><p>● On jobs: Meta and other large technology firms cutting headcount, Leo’s view that organisations carry cost centres agents make redundant, and his warning that universal income becomes a real possibility if AI adaptation fails.</p><p>● On executives: checks and balances survive because agents lack empathy and their judgement is geared to be entirely commercial. Middle management, on his account, does not survive.</p><p>Leo’s central claim is testable inside a week. Pick one function, ask whether the people in it hold 30 per cent of the disciplines their work touches, and the answer will tell you how ready the organisation is.</p><p>Chapters</p><p>00:00 AI's Impact on Headcount and Organisational Fat</p><p>00:30 Skill Stacking and Cross-Functional Value</p><p>00:59 Training Programmes and Upskilling in Large Organisations</p><p>02:26 Orchestration of Specialised AI Agents</p><p>05:00 AI Adoption in the UK and Change Management</p><p>06:10 Resistance to AI Adoption and Entrenched Roles</p><p>08:00 Restructuring and Talent Shifts for AI Integration</p><p>09:20 AI's Effect on Jobs and Cost Rationalisation</p><p>10:46 Future Skills: Broader, Generalist Roles</p><p>12:16 Becoming a Human-AI Hybrid: Skills and Exposure</p><p>14:23 Critical Thinking and Human Oversight of Agents</p><p>16:56 Acquiring Experience in Large Organisations</p><p>17:56 Self-Directed Learning and Side Projects</p><p>20:12 Characteristics of Lagging Organisations</p><p>23:23 Robots and Robotics in Value Creation</p><p>25:45 Orchestration of Agentic AI and Marketplaces</p><p>28:02 The Human Role in a Future AI-Driven Workplace</p><p>30:44 Organisational Transformation and Change Management</p>
63 total episodes available
Recent guests on The AI Adoption Podcast
Guests from recent episodes — sign up to see every guest that has ever appeared on this show.
Olivia Larkin
Guest
Sumeet Bhatia
Guest
John Howells
Guest
Sydney MacGregor
Guest
Chris Blatchford
Guest
Jonathon Palmer
Guest
Ian Smith
Guest
Paul O’Sullivan
Guest
Heather Black
Guest
Ben Johnson
Guest
Janine McKelvey
Guest
Right Reverend Steven Croft
Guest
Similar Podcasts
Discover related shows you might enjoy
Using AI at Work
Chris Daigle
The AI Breakdown: Daily Artificial Intelligence News and Discussions
Nathaniel Whittemore
Rob Beckett and Josh Widdicombe's Parenting Hell
Keep It Light Media / Spotify Studios
The Rest Is Entertainment
Goalhanger
Desert Island Discs
BBC Radio 4
The Rest Is Politics
Goalhanger
Chatabix
Big Oval Plate
The Rest Is Politics: US
Goalhanger
The Rest Is History
Goalhanger
Deep-dive analytics for The AI Adoption Podcast
Frequently asked questions
Have a different question and can't find the answer you're looking for? Reach out to our support team by sending us an email and we'll get back to you as soon as we can.
- What is The AI Adoption Podcast?
- How often does this podcast release new episodes?
This podcast updates daily.
- Where can I listen to this podcast?
This podcast is available on 4 platforms including Apple Podcasts, Spotify, and more. You can also use the RSS feed directly.
- Does this podcast accept guests?
Yes, this podcast regularly features guests.
Legal Disclaimer
Pod Engine is not affiliated with, endorsed by, or officially connected with any of the podcasts displayed on this platform. We operate independently as a podcast discovery and analytics service.
All podcast artwork, thumbnails, and content displayed on this page are the property of their respective owners and are protected by applicable copyright laws. This includes, but is not limited to, podcast cover art, episode artwork, show descriptions, episode titles, transcripts, audio snippets, and any other content originating from the podcast creators or their licensors.
We display this content under fair use principles and/or implied license for the purpose of podcast discovery, information, and commentary. We make no claim of ownership over any podcast content, artwork, or related materials shown on this platform. All trademarks, service marks, and trade names are the property of their respective owners.
While we strive to ensure all content usage is properly authorized, if you are a rights holder and believe your content is being used inappropriately or without proper authorization, please contact us immediately at hey@podengine.ai for prompt review and appropriate action, which may include content removal or proper attribution.
By accessing and using this platform, you acknowledge and agree to respect all applicable copyright laws and intellectual property rights of content owners. Any unauthorized reproduction, distribution, or commercial use of the content displayed on this platform is strictly prohibited.