Gartner just dropped a prediction that should make every CHRO and CIO pause. By 2028, 40% of agentic AI projects will be cancelled. Not downsized. Not delayed. Cancelled. The reasons? Escalating costs, unclear business value, and inadequate risk controls.
The research behind this prediction is focused on data integrity. Is your data trusted? Is it connected? Can your AI systems actually make decisions on a foundation that holds up? These are legitimate, urgent questions. If your data infrastructure can't support reliable decision-making today, autonomous agents won't fix that tomorrow.
But here's what the checklist misses.
Data readiness is necessary. It is not sufficient. Because even if your data is pristine, your AI architecture bulletproof, and your governance airtight, there is another readiness gap that will determine whether your AI investment actually delivers value: your people.
The Readiness Gap Nobody Is Auditing
The Gartner checklist asks CX and IT leaders to assess whether their data can support agentic AI. That's a smart starting point. But consider what happens after the data passes the audit.
Managers still have to interpret AI-generated insights and act on them. Frontline leaders still have to coach their teams through the behavioral changes that AI adoption demands. And employees still have to trust that their manager knows how to lead through ambiguity and disruption.
None of that is a data problem. It's a leadership development problem. And right now, the leadership development industry is failing at it on a massive scale.
Sixty percent of first-time managers receive zero formal training. They learn by trial and error, on real people, in real moments. That was already a crisis before AI entered the picture. Now, with agentic systems making autonomous decisions alongside — and sometimes instead of — human teams, the stakes for manager readiness just multiplied.
Why This Is a CIO Problem, Too
If you're a CIO reading Gartner's checklist and thinking this is between you and your data team, I'd push back. Every AI deployment is, at some point, a change management deployment. And change management lives or dies with the managers who are expected to carry it.
When an agentic AI system changes a workflow, a manager has to explain why. When it produces a recommendation that contradicts someone's instincts, a manager has to facilitate that conversation. When employees feel uncertain about whether AI is going to replace their role, a manager has to address that fear with something more than a talking point from corporate communications.
Gartner calls it "inadequate risk controls." I call it an underdeveloped management layer. The result is the same: cancelled projects and wasted investment.
The Missing Infrastructure
This is the problem we built Lotic Systems to solve.
Most leadership development is episodic. A two-day workshop. A quarterly offsite. A program that teaches frameworks nobody applies once Monday arrives. There is no infrastructure for ongoing practice. No system that meets managers where they actually work, in the moments that actually matter.
RippleIQ™, our AI-powered coaching platform, was built to close that gap. It connects individual leadership data from a psychometric capability assessment to real-time AI coaching and organizational health metrics. Managers get personalized support before a difficult 1:1, during a team transition, or in the middle of an AI-driven process change. Not six months later in a training recap. Right then.
For CHROs, this means a closed-loop system that installs, measures, and sustains manager capability. For CIOs, it means the human layer of your AI deployment is actually supported with the same rigor you apply to data governance. The before-and-after is documented. The ROI is real.
Two Checklists, One Strategy
I'm not arguing against Gartner's data readiness checklist. I'm arguing that it's incomplete without a parallel assessment of people readiness. If your organization is planning to deploy agentic AI at scale, here are the questions your data checklist won't ask:
- Can your managers explain AI-driven decisions to their teams in a way that builds trust instead of eroding it?
- Do your frontline leaders know how to coach through ambiguity, or are they still relying on command-and-control habits that AI adoption will expose?
- When an AI system changes a workflow or a reporting structure, do your managers have the skills to lead people through the emotional reality of that transition?
- Is there any infrastructure — not a workshop, actual infrastructure — supporting your managers with ongoing coaching in the moments that matter?
If the answer to most of those is no, your data readiness won't save you. You'll have clean data flowing into a system that your people can't operationalize.
The Real Risk Is the One You're Not Measuring
Gartner's 40% cancellation prediction is alarming. But the failure rate for leadership development programs is already 50%. These two numbers are about to collide. Organizations pouring resources into AI readiness while ignoring the human layer are building sophisticated systems on top of a management infrastructure that was already cracking.
At Lotic Systems, we believe the organizations that win the next decade won't be the ones with the cleanest data. They'll be the ones whose managers are ready to lead alongside AI. That requires a system, not a seminar. It requires measurement, not motivation. And it requires coaching infrastructure that operates with the same precision your CIO demands from data architecture.
Your data checklist is a start. Your people checklist is what finishes the job.