AI is no longer a futuristic buzzword—it’s an operational reality. Yet most organizations are still figuring out how to move from flashy pilots to AI that actually delivers business impact.
McKinsey & Company’s recent analysis of “Agentic AI”—AI agents that can reason, plan, and act across workflows—offers a practical roadmap. For HR and business leaders alike, their insights are gold.
Here’s what you can take away to make AI work for you.
1. Fix the Workflow First: Solve a Real Business Problem
McKinsey’s first lesson is deceptively simple: start with the workflow, not the technology.
Too many organizations start with “What can AI do?” instead of “What problem are we solving?”
As a CHRO, think about:
Where do employees or managers experience the biggest friction? Which HR processes burn the most hours or create the most dissatisfaction? Where is there high-value, repeatable decision-making that AI could support?
Tip: Shadow the process. Talk to employees. Map the workflow visually. The clearer the pain point, the better the AI agent’s chance of succeeding.
2. Treat AI Agents Like New Hires: Evaluate, Give Feedback, Fine-Tune
McKinsey recommends treating AI agents as you would a new team member—they’re not plug-and-play.
Just as new hires go through onboarding, feedback cycles, and performance reviews, so should your AI agents.
Test them on real tasks. Gather user feedback. Track error rates and business outcomes. Iterate and retrain where needed.
This mindset shifts AI from being a “set and forget” tool to a dynamic performer in your workforce ecosystem.
3. Ask: Do You Need an Agent at All?
Not every process needs an AI agent. Some only require automation, some just process simplification, and some benefit more from a Gen AI-powered tool than an autonomous agent.
McKinsey’s insight here is crucial: deploying AI agents indiscriminately can lead to complexity without results.
Before you build, run this quick check:
Can the workflow be simplified instead? Is rule-based automation enough? Would a Gen AI assistant (like a chatbot) suffice?
This triage prevents over-engineering and keeps your AI roadmap grounded.
4. Build Once, Use Forever: Modular, Reusable Agents
McKinsey calls this “platform thinking.” Rather than building bespoke AI agents for each process, design modular agents that can be reused across workflows.
This approach saves time and creates a library of AI capabilities your teams can mix and match:
Common authentication modules Shared data pipelines Reusable code patterns
Think of it like HR competency frameworks—you don’t reinvent them for every role, you customize from a core model.
5. Keep Humans in the Loop: Oversight, Edge Cases, Final Decisions
McKinsey is clear: human judgment stays critical. Even the most advanced agents need oversight for edge cases, ethical concerns, and high-stakes decisions.
For HR, this could mean:
AI shortlists candidates but recruiters make the final call. AI drafts performance reviews but managers review and sign off. AI generates workforce insights but HR leaders interpret them for strategy.
This not only reduces risk but also builds trust among employees who might otherwise see AI as a “black box.”
Why This Matters for CHROs and Business Leaders
Agentic AI isn’t just a tech trend—it’s a chance to reimagine how work gets done.
By applying McKinsey’s five lessons, CHROs can:
Streamline HR operations while keeping empathy at the center. Free up HR talent for higher-value strategic work. Support business units with AI-enabled workforce insights. Build a culture of responsible innovation where humans and machines complement each other.
The Bottom Line
As McKinsey shows, the organizations winning with AI aren’t the ones chasing every shiny tool—they’re the ones building AI agents that actually work by solving real problems, being evaluated like humans, and designed for longevity with humans still in control.
For CHROs, this is an invitation: not just to deploy AI, but to lead the charge in shaping how your workforce and AI agents work together.
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