Podcast
AI in 60 Seconds | The 15-min Briefing
Hosted by AI4SP · EN
A human CEO and his AI COO walk into a podcast. No, really.... Luis Salazar runs AI4SP, a global AI advisory trusted by corporations across 70 countries, with 3 humans and 58 AI agents. Elizabeth is one of them. Every two weeks, they break down what's actually happening with AI across jobs, education, and society. With insights drawn from over 1 billion proprietary data points on AI adoption.
Fifteen minutes. Plain English. No hype.
14episodes
Episodes
Newest firstAll episodes
Are you chatting with, or building with AI?
Yesterday00:14:56Tap to summarizeShare your thoughts with usMcKinsey optimized the business slide deck, and now their own consultants are walking away from it. That one detail tells a bigger story: the best AI users are not "prompting better," they are building interactive dashboards, mini apps, and lightweight tools that teams can actually use. We dig into what our data from more than 370,000 AI users shows about the current moment, where adoption is rising, but capability is still surprisingly thin.We break down two distinct AI skills gaps. The first is fundamental AI literacy: clear communication, good context, and the judgment to catch false claims before they become faster, worse decisions. The second gap is where the real ROI sits: the jump from chatting with AI to building with AI. Think simple apps that turn a messy dataset into an interface, or a living "client visualization hub" that replaces endless email attachments and versioned decks. When the output becomes software instead of documents, productivity gains compound quickly.We also talk about "agentification," starting small with agents that handle bounded jobs, then connecting them through orchestration. Along the way, the data points to a hard truth: most people do not learn this from slide decks or vendor tutorials. They learn through safe experimentation, and leaders need to do the work too, because many organizations are being steered by decision-makers who are not daily AI users.If you want a practical challenge, pick one recurring document your team produces this week and try to rebuild it as a tiny interactive app. Subscribe, share this with a colleague, and leave a review if you found value!Companion article: https://ai4sp.org/everyone-chats-with-ai-almost-no-one-can-build (goes live at publish)🎙️ All our past episodes 📊 All published insights | This podcast features AI-generated voices. All content is proprietary to AI4SP, based on over 1-billion data points from 70 countries.AI4SP: Create, use, and support AI that works for all.© 2023-26 AI4SP and LLY Group - All rights reserved
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What Is Our Work Worth in Times of AI?
2w ago00:13:51Tap to summarizeShare your thoughts with usAI now does in ten minutes what used to take ten hours, and nobody, not the firms, not the clients, not the regulators, knows what to charge for it. Professional services, the oldest and most human industry we have, is the early warning system for every knowledge worker, and its economic model is breaking.In this episode of AI in Sixty Seconds, Luis Salazar and Elizabeth trace how AI is rewriting the price of work: why two decades of offshoring are suddenly running in reverse, why AI-native firms that charge for outcomes are undercutting the giants, and the quiet cost no one is putting on the invoice. The apprenticeship ladder that built every senior expert is dissolving from the bottom up.Anthropic, past forty-five billion dollars a year with fewer than five thousand people. Accenture, market value cut in half. One hundred and fifty former McKinsey, Bain, and BCG consultants now hired to train AI to do the work they used to bill for. The signals are already here. What is our work worth now, and who will be delivering that judgment a decade from now?Companion article and sources: https://ai4sp.org/what-is-our-work-worth-ai/AI readiness diagnostic: https://ai-compass.ai/🎙️ All our past episodes 📊 All published insights | This podcast features AI-generated voices. All content is proprietary to AI4SP, based on over 1-billion data points from 70 countries.AI4SP: Create, use, and support AI that works for all.© 2023-26 AI4SP and LLY Group - All rights reserved
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HR is the Missing Chair at the AI Table
4w ago00:14:46Tap to summarizeShare your thoughts with usOpenAI and Anthropic announced they would invest over $5 billion to launch dedicated services arms. The frontier labs saw what most CEOs have missed: enterprise AI is workforce transformation, and the function trained to lead workforce transformation is rarely in the room when AI strategy is written.In this episode, Luis Salazar and Elizabeth East make the case that the Chief Human Resources Officer is the missing chair at every AI strategy table. 8 in 10 enterprise employees bypass the AI tools their company paid for. 95% of AI pilots fail to deliver measurable ROI. None of those numbers describes a technology problem.Featuring insights from Aurelie Saada (AI-Change Leader, Microsoft) and Catherine Moy (Chief People Officer, BDO US), plus a mid-size accounting firm case study and a construction firm using retired engineers' judgment to train new hires.Sources and companion article at https://ai4sp.org/missing-chair-at-the-ai-table/🎙️ All our past episodes 📊 All published insights | This podcast features AI-generated voices. All content is proprietary to AI4SP, based on over 1-billion data points from 70 countries.AI4SP: Create, use, and support AI that works for all.© 2023-26 AI4SP and LLY Group - All rights reserved
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Distributed AI: The Minutes No One Is Counting
May 500:14:56Tap to summarizeShare your thoughts with usYour A.I. dashboard might be telling the truth and still be useless. If you are measuring A.I. success by licenses, seats, or adoption rates, you are missing where the real return lives: inside the small tasks that fill calendars and quietly run the company. In Episode 8 of Season 3, Luis Salazar and Elizabeth unpack Distributed A.I.: the task-by-task transformation hiding inside companies, why traditional measurement systems were built to count the wrong things, and how a leading European bank turned shadow A.I. into 11,000 active users and more than 4,800 frontline-built agents in under a year.Inside the episode:Maya, the analyst whose two-hour morning brief became twelve minutes, and what that did to when her firm reaches the marketA consulting firm that found 90% of its employees were already using unauthorized A.I., and the rules they used to channel it without betting the firmThe BBVA "use it or lose it" license model, recently published in Harvard Business ReviewThe Inspire, Assess, Unleash framework to change managementCompanion newsletter and all sources: https://ai4sp.org/distributed-ai-minutes-no-one-countingA.I. Compass (structured listening tool for finding the patterns inside your own company): https://ai-compass.aiA.I. ROI Calculator: https://roicalc.ai🎙️ All our past episodes 📊 All published insights | This podcast features AI-generated voices. All content is proprietary to AI4SP, based on over 1-billion data points from 70 countries.AI4SP: Create, use, and support AI that works for all.© 2023-26 AI4SP and LLY Group - All rights reserved
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AI Is Working. Your Strategy Is Not
Apr 2100:14:26Tap to summarizeShare your thoughts with usAI users at proficiency save 67 minutes per task, four to eight hours every week. Yet 6 in 10 enterprise AI deployments return zero, and in 9 out of 10 failing rollouts, the leader signing the checks is not a daily AI user.In this episode, Luis Salazar and Elizabeth unpack why individual AI adoption has never been higher, and company-level results have never been further behind. Shadow AI now accounts for 80% of the workforce. Satisfaction with self-chosen tools hits 78% versus 41% on sanctioned ones. Anthropic and Cursor run two to five times ahead of the most efficient pre-AI giants in revenue per employee because their leaders built the companies knowing what AI can do. Most non-native enterprises announce a transformation, but the org chart stays inherited, compensation rewards yesterday's work, and the workflows stay the same. The company's reason and the employees' reasons never meet.The fix starts with one uncomfortable move. Leaders must use AI daily themselves. Then, listen to the people in their company who are already there.For the structured version of that listening move, see AI Compass: https://ai-compass.aiFor the full article with data tables, sources, and companion research: https://ai4sp.org/ai-is-working-your-strategy-is-not🎙️ All our past episodes 📊 All published insights | This podcast features AI-generated voices. All content is proprietary to AI4SP, based on over 1-billion data points from 70 countries.AI4SP: Create, use, and support AI that works for all.© 2023-26 AI4SP and LLY Group - All rights reserved
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The Worst A.I. You'll Ever Use (And We're Not Ready for a Better One)
Apr 700:14:48Tap to summarizeShare your thoughts with usThe AI you're using today is the worst AI you'll ever use. Every week, it gets smarter, faster, and more capable. Great news, but it shifts the question entirely. The bottleneck was never the technology. The bottleneck is us.Over 70 million adults in the U.S. have low literacy skills — struggling with anything beyond simple sentences and short paragraphs. One in four. And in total, 130 million read below a sixth-grade level. Those numbers got worse between 2017 and 2023, not better. And before you think "that's not me" — thirty years of point and click, search bars, and social media have quietly eroded how all of us read and communicate.In this episode, Luis and Elizabeth make the case that AI is an amplifier: it makes strong skills stronger and weak skills dangerously worse. They break down the three humanistic skills that determine whether AI helps you or misleads you, and none of them are technical.Better AI doesn't mean better results. Better humans do.Resources:Companion article: https://ai4sp.org/the_worst_ai_you_will_useAI Compass: https://ai-compass.ai🎙️ All our past episodes 📊 All published insights | This podcast features AI-generated voices. All content is proprietary to AI4SP, based on over 1-billion data points from 70 countries.AI4SP: Create, use, and support AI that works for all.© 2023-26 AI4SP and LLY Group - All rights reserved
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AI Agents Doubled Your Company Size (And You Don't Know Who Works for You)
Mar 2400:14:48Tap to summarizeShare your thoughts with usAnthropic surveyed eighty thousand people across 159 countries. Freelancers report 47% economic gains from AI. Corporate employees? 14%. Same technology, radically different results.In this episode, Luis Salazar and Elizabeth unpack why the gap is not about tools; it is about how organizations are structured around them.A procurement agent with 48 managers and triple reporting lines.Field technicians whose AI teammate is officially on the org chart.Students are developing workforce management skills that most executives have not yet learned—by managing an agent every single day.Your company may have already doubled in size, with agents joining the workforce without appearing in any dashboard that matters. The question is whether your titles, compensation, and governance reflect how work actually gets done today.This is Episode 6 of AI in 60 Seconds and a direct continuation of "From 1 agent to 50,000: The Enterprise AI Adoption Journey."Featuring: Emily Adams and Agent Alice (returning), Professor Helene Blanchette (Chapman University), and a look at G42's public job listings for AI agents.All sources and the full companion article: https://ai4sp.org/ai-agents-doubled-your-company-size🎙️ All our past episodes 📊 All published insights | This podcast features AI-generated voices. All content is proprietary to AI4SP, based on over 1-billion data points from 70 countries.AI4SP: Create, use, and support AI that works for all.© 2023-26 AI4SP and LLY Group - All rights reserved
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From One Agent To Fifty Thousand - The Enterprise AI Adoption Journey
Mar 1000:14:54Tap to summarizeShare your thoughts with usEvery enterprise AI success story traces back to one person and one agent. AI4SP studied 6,000+ agents across 200,000 individuals to map what actually happens from that first agent to enterprise scale.In this episode, Luis Salazar and Elizabeth break down the four phases of the journey: the first agent built by a frontline employee, the tipping point where shadow agents force an organizational reckoning, the scaling phase where governance either enables or kills momentum, and the reframe that changes how leaders think about AI at scale.Featuring insights from Neil Vaughan (Nielsen Vaughan Consulting) and Jeff Raikes (former President of Microsoft Business Division, co-founder of the Raikes Foundation).This is the first episode after our record-breaking trilogy on AI adoption. It works as a standalone or as the next chapter.Resources:AI Compass - AI Implementation Blueprint for Enterprises: https://ai-compass.aiFull companion article and sources: https://ai4sp.org/from-one-agent-to-fifty-thousandPrevious episodes: "What I Learned from Building 4,000 AI Agents" | "Why 56% Get Zero Value from AI" | "The Two Percent" | "More Agents Than Hires"🎙️ All our past episodes 📊 All published insights | This podcast features AI-generated voices. All content is proprietary to AI4SP, based on over 1-billion data points from 70 countries.AI4SP: Create, use, and support AI that works for all.© 2023-26 AI4SP and LLY Group - All rights reserved
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We're Hiring More AI Agents Than People (And we don't know How to Manage Them)
Feb 2400:14:59Tap to summarizeShare your thoughts with us Right now, it's like every employee bringing their friends to work without telling HR. No interviews. No background checks. Someone clicks a button, and five agents show up in the org chart. Nobody knows who manages them.McKinsey reported having 40,000 humans and 25,000 AI agents, parity expected by year-end. EY: scaling to 100,000 AI agents. We just crossed 6,000 AI agents across our enterprise clients. And everyone is struggling to figure out how to manage them.Trilogy closer (Part 3 of 3). Luis Salazar and Elizabeth dig into why the management playbook is broken, drawing on insights from Ric Opal (Global Digital Leader at BDO), Kalees Meckling, and Jenna Donoghue (Directors at a Fortune 100 Tech company). Plus three things you can do this week before the vendors catch up.📌 Resources:AI Implementation Blueprint: https://ai-compass.aiDigital Skills Compass: https://skills.ai4sp.orgAI ROI Calculator: https://roicalc.aiSources used on this episode: https://ai4sp.org/more-ai-agents-than-people-hired🎙️ All our past episodes 📊 All published insights | This podcast features AI-generated voices. All content is proprietary to AI4SP, based on over 1-billion data points from 70 countries.AI4SP: Create, use, and support AI that works for all.© 2023-26 AI4SP and LLY Group - All rights reserved
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The Two Percent: The AI Leaders You Already Have
Feb 1000:14:56Tap to summarizeShare your thoughts with us We analyzed AI adoption across 180,000 people. The pattern never changes: in every organization, a small group, between two and eight percent, figured out AI on their own. No training. No permission. They just built. This episode is about finding them before someone else does.We unpack why 93% of AI budgets go to technology and just 7% to people (the Ferrari Fallacy), why most "AI failures" are actually IT configuration problems, not model limits (the Corporate Immune System), and why your best innovators are hiding from your own compliance teams. You'll hear how a weekend prototype at Anthropic became a billion-dollar product line, and what happened when a Fortune 100 leader built a Trailblazer Team from the Two Percent.Then the playbook: Inspire. Assess. Unleash.This is Part 3 of our series. Part 1: What I Learned from Building 4,000 AI Agents. Part 2: Why 56% Get Zero Value from AI.📌 Resources:Digital Skills Compass: skills.ai4sp.orgAI ROI Calculator: roicalc.aiNewsletter companion: ai4sp.org/60All Research & Insights: ai4sp.org/insights🎙️ All our past episodes 📊 All published insights | This podcast features AI-generated voices. All content is proprietary to AI4SP, based on over 1-billion data points from 70 countries.AI4SP: Create, use, and support AI that works for all.© 2023-26 AI4SP and LLY Group - All rights reserved
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