Feature
White Paper
The Future of Leadership Development: AI-Driven Manager Enablement
Talent management is broken, we can all agree. Blame the onslaught of job seekers, AI, hyper-tailored resumes, disconnected data and even the modern HR tech stack. No matter the reason, we've got talent problems and they are expensive.
Korn Ferry's 2026 Global Talent Analytics Survey of 1,600 C-suite and HR leaders puts a number on it. Ninety-nine percent of leaders admit that disconnected talent data is creating a negative financial drag, with more than 80% estimating that tech fragmentation wastes at least 3% of their total payroll.
The data problem is real. But it's not the whole story.
Steve Cadigan, the former CHRO who scaled LinkedIn from 400 to 4,000 employees, told Reworked that blaming fragmented systems misses the point. The issue, in his mind, isn't just that the talent systems don't talk to each other. It's that decisions belonging to humans are being handed to machines that can't even use the data they already have.
Table of Contents
- Dirty Data Undermines HR Credibility
- Recruiters Do What Tech Cannot Do: Read Between the Lines
- The Talent Problem Is a Human Problem
Dirty Data Undermines HR Credibility
Korn Ferry's argument for a data-driven overhaul appears structurally sound. Over the last decade, enterprises acquired software to solve specific, isolated headaches. One platform for hiring, another for performance tracking, a third for payroll, a fourth for skills assessments, another for succession planning ... most often without a coherent operating model underneath any of it.
"The result is complexity: multiple systems, inconsistent data definitions, duplicated workflows and declining confidence in reporting," Korn Ferry Global Lead of People Strategy and Performance Practice, Roger Philby, told Reworked. "The real question now isn't whether organizations need more data. It's whether they can create enough interoperability and semantic consistency to make that data actionable."
Only 5% of organizations report fully connected systems where data moves cleanly between platforms. So basic talent management has become expensive guesswork. To answer something as fundamental as "Who is ready to step into a leadership role?" managers have to manually reconcile conflicting metrics from disconnected platforms. Most give up and go with their guts instead.
Seventy-one percent of leaders default to intuition when making high-stakes people decisions. And the more talent systems a company deploys, the worse it gets. Organizations running 10 or more tools are nearly twice as likely to rely on gut instinct over data.
That's when HR loses its seat at the table. Here’s how Philby put it, "The business doesn't believe HR because they don't believe the data can be trusted. And that's because HR isn't always great at being data practitioners and communicators, pulling everything together and translating it into a story the business can act on."
Philby was careful not to dismiss intuition outright. In his view, leaders defaulting to gut instinct isn't a cultural failure. It's a rational response to data they've learned not to trust. "Most executives are not anti-data," he said. "They're anti-low-confidence data." The problem, he argued, isn't that intuition exists. It's when intuition becomes a substitute for reliable workforce intelligence rather than being informed by it. Talent decisions now drive business performance directly, whether that's productivity, transformation delivery, innovation or growth. And CFOs are starting to notice.
That's not far from what Cadigan said either. His concern is that the wrong decisions are being handed to machines and that both humans and employers are bearing the consequences.
The cost doesn't show up as a line item. It shows up as a resignation letter. Nearly a third of executives report high-potential employees sitting underutilized until they stop waiting and leave. And the organization ends up paying to hire externally what it already had internally.
Recruiters Do What Tech Cannot Do: Read Between the Lines
When organizations treat talent management as a pure data engineering problem, it's the candidate who pays the price. Cadigan argued that by focusing entirely on fixing data gaps with more platforms, the enterprise has accidentally built something that pushes good people away.
"Technology that's been built to solve a quantity problem is being applied to solve a quality problem," Cadigan said.
Driven by panic over high application volumes and talent pipeline shortages, HR departments have outsourced early-stage sourcing to AI filters and automated testing suites. The result is an environment where the first interaction between a human being and a brand is void of human connection.
"Talk to any recent college grad, looking for a new job is the most miserable experience. Imagine taking a test on Excel while a bot is watching," Cadigan said.
A seasoned recruiter listens for the gaps. The hesitation when someone talks about a past failure. The genuine energy when they describe solving something nobody asked them to solve. They read the subtext. Automated filters can't do that. They can't tell you whether someone hit their number because the market was booming or because they clawed it out against a broken supply chain. They can't spot the candidate who's missing a keyword but could master a new domain in three months. They can't pick up on how someone navigates friction or builds trust across a room full of people who disagree.
When organizations default to automated filters, they don't just screen out bad fits. They screen out the people who refuse to perform for an algorithm.
The Talent Problem Is a Human Problem
The talent problem isn't strictly about data, and it isn't strictly about human instinct. It's about how organizations deploy technology to amplify human judgment rather than replace it.
Webinar
Jun
17
Engaged, But Not Convinced: What's Eroding Beneath Your Strongest Engagement Numbers
Perceptyx EX Benchmark '26: leadership trust, change confidence and conviction gap truths at large enterprises.
Register
Webinar
On demand
Retention Is a Communication Problem: New Data from 6,000+ Employees
This session gives leaders a clear diagnosis and practical path to treat retention as an infrastructure problem.
Watch Now
Webinar
On demand
Do Learning Programs Really Work? How to Turn Education Into Engagement In Healthcare
See how leaders are using learning programs to build trust with healthcare professionals and create measurable engagement.
Watch Now
Webinar
On demand
Fuel Your Front Line: Workforce Trends Shaping 2026
Get expert insight into the tools and tactics top frontline teams will need in 2026.
Watch Now
Webinar
On demand
Fix the Disconnect Between Projects and Profit
Your margins are hiding in disconnected data. Let's find them.
Watch Now
Webinar
On demand
AI in Customer Service: Faster Resolutions, Happier Customers
Don’t let rising demand burn out your team. See how to build a smarter, more resilient support org.
Watch Now
Cadigan doesn't reject technology in talent management. He redefines its purpose. Instead of using bots to filter candidates through compliance tests, he argued that AI can actually surface capability that humans might miss. "AI can help employers see what the naked eye can't see, such as, if they worked on these projects, they will have these skills," he said. The better question, in his view, isn't whether someone ticks a box today. "Can we ask AI to show me what this person has learned?"
Philby framed the bigger organizational challenge clearly. The goal isn't to hand decisions to a platform or to ignore the data sitting inside one. "The question is less 'who owns the data' and more 'can the enterprise trust the workforce decisions being made from it,'" he said.
Editor's Note: HR is facing challenges on multiple fronts. Here is just a small taste of what they're up against:
- AI Is Making the Hiring Crisis Worse — Using AI as a cure-all creates a doom loop: candidates and hiring managers game each other with AI, and hiring stays broken.
- HR Data Analytics Skills Are in Demand: 4 Ways to Upskill — Research finds HR teams are lacking data analytics skills to make smarter decisions faster. Here is why — and how — you can upskill to seize the future of HR.
- Companies Don't Know Their Own Talent. AI Can Change That — Companies know less about their employees than LinkedIn does. That's a problem.