HR is the Missing Chair at the AI Table

The AI Implementation Heresy

Share your thoughts with us [https://www.buzzsprout.com/2406097/fan_mail/new] We debate the rise of forward deployed engineers and multi-billion-dollar deployment arms from major AI vendors, and we name the tradeoff: faster wins can also create deeper vendor dependency if capacity is not built inside your team. We share the day 100 question to ask before you sign anything, plus a simple operating model for AI governance: assign a named agent manager, give them real hours, train them, and budget for the humans who sustain the system. The AI agent demo looks magical, and that is exactly why it can become dangerous. We keep watching a familiar cycle: outside experts parachute into a company, build something impressive in weeks, and then a silent countdown starts the moment they leave. Nothing “breaks,” but value slips, costs creep, answers drift, and the business quietly learns to stop trusting what it just paid for. We dig into why this happens by borrowing a blunt framework: the law of amplification. AI does not automatically fix broken systems. It amplifies what is already true about your organization, including your documentation quality, policies, decision rights, data hygiene, and ability to manage change. We also explain why AI agents are not the kind of classic software you can install and forget. They behave more like a garden, shaped by model upgrades, shifting business priorities, and stale knowledge bases. Without weekly attention, “agent drift” turns yesterday’s alignment into tomorrow’s risk. If you want enterprise AI that lasts, not just a launch-day headline, listen through to the checklist and put it to work. Subscribe, share this with the person who owns AI rollout, and leave a review with your answer: who runs your agents on day 100? Stats and resources: https://ai4sp.org/ai-implementation-heresy 🎙️ All our past episodes [https://ai4sp.org/60]  📊 All published insights [https://ai4sp.org/60] | 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

Are you chatting with, or building with AI?

Share your thoughts with us [https://www.buzzsprout.com/2406097/fan_mail/new] McKinsey 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 [https://ai4sp.org/everyone-chats-with-ai-almost-no-one-can-build] (goes live at publish) 🎙️ All our past episodes [https://ai4sp.org/60]  📊 All published insights [https://ai4sp.org/60] | 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

What Is Our Work Worth in Times of AI?

Share your thoughts with us [https://www.buzzsprout.com/2406097/fan_mail/new] AI 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/ [https://ai4sp.org/what-is-our-work-worth-ai/?utm_source=buzzsprout&utm_medium=podcast&utm_campaign=260602] * AI readiness diagnostic: https://ai-compass.ai/ [https://ai-compass.ai/?utm_source=buzzsprout&utm_medium=podcast&utm_campaign=260602] 🎙️ All our past episodes [https://ai4sp.org/60]  📊 All published insights [https://ai4sp.org/60] | 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

HR is the Missing Chair at the AI Table

Share your thoughts with us [https://www.buzzsprout.com/2406097/fan_mail/new] OpenAI 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/ [https://ai4sp.org/missing-chair-at-the-ai-table/] 🎙️ All our past episodes [https://ai4sp.org/60]  📊 All published insights [https://ai4sp.org/60] | 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

Distributed AI: The Minutes No One Is Counting

Share your thoughts with us [https://www.buzzsprout.com/2406097/fan_mail/new] Your 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 market * A 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 firm * The BBVA "use it or lose it" license model, recently published in Harvard Business Review * The Inspire, Assess, Unleash framework to change management Companion newsletter and all sources: https://ai4sp.org/distributed-ai-minutes-no-one-counting [https://ai4sp.org/distributed-ai-minutes-no-one-counting] A.I. Compass (structured listening tool for finding the patterns inside your own company): https://ai-compass.ai [https://ai-compass.ai/] A.I. ROI Calculator: https://roicalc.ai [https://roicalc.ai/] 🎙️ All our past episodes [https://ai4sp.org/60]  📊 All published insights [https://ai4sp.org/60] | 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