The Josh Bersin Company

What if every talent process you ran was AI-enabled — not to replace what you do, but to make you superhuman at it?

That’s exactly how Matt Hoffman, Head of Talent and Partner at venture capital firm M13, operates. In this episode Matt explains how his team uses AI to help early-stage founders build a talent-first culture from day one – across recruiting, compensation, coaching, and beyond.

The results are remarkable. Using tools like Findem for AI-powered sourcing, Matt’s team can pinpoint candidates who didn’t just work at the right company — they worked there at exactly the right stage of company growth. That’s a level of targeting precision that data accuracy and explainability make possible, and that simply wasn’t achievable before AI.

But here is where Matt’s perspective gets truly compelling. AI is often framed as a speed tool, a way to do things faster and more efficiently. Matt pushes back hard on that narrative: AI should make your hiring better, not just quicker. And in the startup world, that distinction is everything.  Every hire at a 10-person company changes the organization by 10% — so getting it right matters far more than getting it done.

That is the essence of talent density: finding exactly the right people for where your company is and where it needs to go, rather than simply finding people fast.

His advice to HR and talent leaders is as practical as it is powerful: fall in love with the problem, not the solution. Start with the outcome you need to achieve, then let technology enable it — never the other way around.

If you have ever wondered what a truly AI-augmented talent strategy looks like when it is built with intention, depth, and relentless focus on talent density, this one’s for you.

Related resources

Podcast: Why AI Is A Massive Job Creation Technology. Automated Integration. Findem. And Thank You.

Podcast: Understanding Talent Density And Ditching Integrated Talent Management

Research: Insights-First AI: Better and Explainable People Decisions

Research: The Talent Acquisition Revolution: How AI is Transforming Recruiting

Research: How To Create Talent Density

This week Korn Ferry announced the $1.1 Billion acquisition of AMS, one of the leading providers of enterprise recruitment outsourcing. As I overview in this podcast, this deal demonstrates several things:

First, the talent acquisition space has become enormously important and is rapidly changing with AI, demographic changes, and internal productivity initiatives. AMS has become a global leader in recruitment process outsourcing and TA advisory work, leading to the $1.1 Billion valuation. AMS’s product AMS One is one of the only tech platforms that integrates almost every recruiting technology into one operational view, enabling AMS and clients to monitor, tune, and optimize all areas of recruiting in one place.

Second, Korn Ferry, as a leader in executive search and talent management services (including training offerings), sees enormous synergies and can add AMS’s revenue and $1.5 Billion backlog to their financial strength. While KF was not growing much, this now gives the company a new growth platform – including the opportunity to use AMS’s global service centers for other offerings.

This podcast is an overview of the deal, we’ll publish more after we get a briefing from KF’s management team.

Additional Information

History of Korn Ferry Acquisitions

The Talent Acquisition Revolution: How AI Is Transforming Recruitment

The Josh Bersin Institute Global HR Excellence Certification (inaugural cohort starts in September)

Understanding Agentic HR In Detail: The HR 2030 Vision and Architecture

 

 

 

Chapters

(00:00:00) - Korn Ferry vs AMS Merger Explained

Today I overview why the Frontier AI vendors are changing as they compete for revenue and how that opens new doors for corporate AI solutions. Remember, your personalization of the technology is more important than the model itself.

Then I discuss our new HR 2030 architectural research and how rules, policies, and security are so important in this new world of Agentic HR. It’s a new world and all focused on “Dynamic Enablement for Growth.”

Additional Information

AI As Fuel For Organizational Change: The Biggest Market Of All

Are Frontier Models Becoming A Commodity?

HR 2030: The Reference Blueprint for Agentic HR (sign up for info)

HR 2030 New Course in Galileo Learn

The Global HR Excellence Certification (GHRE)

Get Galileo: The AI Superagent for HR

Chapters

(00:00:00) - HR 2030: The AI Marketplace
(00:04:33) - The AI That Will Be Embedded in Your Glasses
(00:07:41) - HR 2030: A reference architecture for the technology
(00:09:37) - An Agent's role in the Company
(00:18:38) - The third layer of an AI agent
(00:21:16) - The Purpose of AI: Why Are We Here?
(00:23:58) - Employers' HR Vision 2030

Sana Learning is a revolutionary product in the $400 Billion L&D market. Today I sat down with Rita Azevedo, Director of Client Engagement at Sana, to talk about everything. What is AI-native learning, how does Sana Learning fit into Workday’s strategy, and how do companies like Polestar, Rolls Royce, Travelers, and others revolutionize L&D with Sana.

And most of important of all, we get Rita’s perspective on the reinvention of L&D, which we call “Dynamic Enablement for Growth.”

As you’ll hear, AI-native learning platforms like Sana can totally transform training teams, turning them into “business enablement” functions working directly in the business. We discuss how Polestar has done this in detail.

Rita is an experienced L&D leader (having lead training at Klarna) and has worked at Sana since the company had only 30 employees, so she has a wealth of knowledge and experience in AI transformation in L&D.

PS: We are customers of Sana (Galileo Learn is built on Sana, and our new Global HR Excellence Certification is built on Sana), so we can speak to its features in detail if you’re interested.

Chapters

00:00 Introduction to the Podcast and Guest
01:44 The Revolution in Learning and Development
03:30 Sana’s Position in the Learning Market
05:53 Understanding Sana Learning’s Unique Features
07:08 The Future of Learning: Proactive vs. Reactive
09:11 Case Study: Polestar’s Learning Approach
12:47 User Experience and Integration in Learning
14:07 The Role of AI Tutors in Learning
16:07 Dynamic Skills Assessment in Learning
18:42 The Shift in L&D Responsibilities
21:35 Empowering Subject Matter Experts
24:25 Managing Content Creation and Quality
27:18 The Future of Learning and Change Management
31:02 Advice for Organizations Exploring Learning Solutions

 

Additional Information

The AI Native Revolution in Corporate Learning (research)

Our new Corporate Learning Maturity Model

HR 2030: The New Role, Operating Model, and Tech Stack for HR

Get Galileo: Experience Sana Yourself!

Chapters

(00:00:00) - Meet Rita Azevedo from sana
(00:02:16) - SANAA's Take on Learning & Development
(00:04:26) - Sauna Learning: Workday Learning Powered by Sauna
(00:06:34) - Sana Learning's AI-based Learning Platform
(00:10:12) - Sales Training: The Future of Learning at Sana
(00:13:33) - L&D 2.8: User Experience
(00:14:44) - L&D: The Tutor, the Editor and the Admin
(00:17:04) - The L&D paradigm shift
(00:19:22) - How Skills are Being Rated in the Future
(00:22:30) - L&D: The Future of Content Management
(00:27:56) - Learning vs. Agents: Can Microsoft Win with Both?
(00:30:46) - How to move legacy courses to Scrum
(00:31:50) - A New Way to Start with Workday's AI in 2020

As AI vendors hype “recursive self-improvement” and other scary features, we see more and more “mainstreaming” of AI technology in business. In other words, the AI does not solve problems by itself: we as HR and IT leaders need to clearly define our needs and then buy, build, and tune the technologies we buy.

Some AI vendors (ie. Paradox, Radancy, Sana, Maki, others) are laser focused on very specific use-cases, and they are delivering solution-first offerings that really add value. The frontier vendors, however, are struggling to do this and much of their revenue still comes from “enabling others” to create solutions. And the new usage-based pricing is forcing this kind of pragmatic thinking.

In this podcast I highlight this “commoditization” of core AI features and explain why your “problem identification” work is perhaps the biggest effort in the HR 2030 Agentic HR strategy.

(Take our new HR 2030 course or sign up for our new Global HR Excellence Certification.)

Additional Information

Is AI A “Normal” Technology?

The Rise of the Supermanager

Our New Book Superpowered, Coming This Fall!

New Course: Galileo Is Ready To Teach You What You Need to Know about HR 2030

 

 

Chapters

(00:00:00) - A Lesson on AI in Software Engineering
(00:09:44) - Bill Gates on the Need for People in AI