Why AI Investments in HR Are Failing And Why Turnaround Specialists Should Lead the Fix
AI investments in HR are faltering. Companies are spending millions on AI-powered recruiting tools, chatbots, performance management systems, and learning platforms, yet most executives report minimal ROI. The problem isn’t the technology – it’s that HR is using AI to make broken processes more efficient rather than reengineering how talent decisions get made.
This represents a fundamental misunderstanding of what AI enables.
When you automate a dysfunctional process, you get dysfunction at scale.
When HR deploys AI to screen more resumes faster using the same flawed criteria, or to deliver more training content that doesn’t change behavior, or to generate more performance review documentation that nobody reads, the technology amplifies waste rather than creating value.
Here’s the core problem as I see it. After decades of professionalizing around process optimization, HR departments instinctively approach AI as an efficiency tool. They ask: “How can AI help us fill requisitions faster, process more candidates, deliver more training, generate more data?” They rarely ask: “Should we be doing this at all? What would talent management look like if we designed it from scratch?”
This is why companies should consider deploying Non-HR turnaround specialists to lead AI-driven HR transformation for 18-24 months – not to improve HR, but to fundamentally reengineer how talent decisions drive business outcomes.
What Non-HR Turnaround Specialists See That HR Doesn’t
Turnaround specialists approach dysfunction differently than functional experts. When they encounter underperforming operations, they don’t ask “how do we make this process better?” They ask “what business outcome are we trying to achieve, and what’s preventing us from achieving it?”
Applied to HR and AI, this means reframing the entire conversation:
HR asks:“How can AI help us screen resumes more efficiently?”
Non-HR Turnaround specialist asks: “Why are we screening resumes at all? What if AI helped us identify people who’ve demonstrated performance capability in adjacent roles, regardless of whether they applied?”
HR asks: “How can AI personalize our learning management system?”
Non-HR Turnaround specialist asks: “Does training actually change performance, or are we just documenting compliance? What if AI helped managers give real-time feedback that actually develops capability?”
HR asks:“How can AI make performance reviews less time-consuming?”
Non-HR Turnaround specialist asks: “Do annual reviews improve performance, or just create documentation? What if AI continuously tracked contribution and surfaced insights when decisions need to be made?”
This isn’t about having better ideas. It’s about having the permission and perspective to question foundational assumptions.
HR professionals have built careers around existing HR processes – they have psychological and professional investment in defending them. Turnaround specialists have no such attachment.
Why This Matters Now
The AI moment creates unusual opportunity for structural change. When companies deployed previous waves of HR technology – applicant tracking systems, HRIS platforms, learning management systems – they were automating existing processes. The technology constrained what was possible. This is exemplified by the image above. I had this drawn when HR Tech vendors promised companies they’d win the war for talent. What’s changed?
But it can. Now.
AI is different. It can analyze unstructured data, recognize patterns humans miss, make predictions, generate content, and learn from outcomes. This means you’re no longer constrained by what could be turned into a workflow. You can fundamentally reimagine how all types of HR business decisions get made.
But this requires someone who thinks in terms of business reengineering, not process improvement. HR professionals are trained to optimize within existing frameworks. Turnaround specialists are trained to blow up frameworks that don’t work and build new ones oriented around outcomes.
For example, try this prompt on any AI system and see what happens:
Here’s what CoPilot had to say about this idea(it includes the prompt you can paste elsewhere).
Claude went over the topand did a complete financial assessment for a Board of Director’s meeting at a $1 billion company.
This is bigger than “Moneyball of HR!”– It’s about the future of talent management and the future the work and the future of the entire HR function.
Why Business Leaders Should Care
If you’ve invested in AI for HR and aren’t seeing ROI, the problem likely isn’t the technology or the vendor. It’s that you’ve funded efficiency improvements to processes that shouldn’t exist in their current form.
The solution isn’t better change management or more HR training. It’s bringing in someone who can objectively evaluate whether your talent systems deserve to exist, who has the credibility to tell executives their hiring processes are broken, and who has the skill to reengineer operations around business outcomes.
This isn’t about denigrating HR professionals. It’s about recognizing that transformational change often requires outside perspective. Companies routinely bring in turnaround specialists to fix operations, supply chain, or finance. Why should talent be different especially when talent decisions arguably matter more to competitive advantage than most operational choices?
The Real Question
Can someone from outside HR, armed with AI capabilities and a mandate to reengineer rather than optimize, transform how companies make talent decisions in 18-24 months?
The alternative is continuing to fund AI implementations that make broken processes more efficient, while wondering why your talent systems still don’t deliver competitive advantage.
That seems like a conversation worth having.