Software vendors are pitching their Agentic AI capabilities left and right, but few go further and support your organization’s transformation to adopt them. IT teams evaluating and implementing AI agents often reinvent the wheel on the workforce lifecycle, despite HR having built concepts and procedures for human workers already.
That's why I discussed with Todd Raphael, Talent Acquisition & HR Tech Expert, on “What’s the BUZZ?” how HR needs to evolve workforce planning for organizations introducing Agentic AI.
Making Agents Part of the Workflow
When organizations rush to build agents, the hard part starts after the launch. Vendors let you “build an agent in five minutes,” but few explain how it fits into your weekly work. As a people leader, your first job is to define clear steps: where the agent begins, what human handoffs look like, and how approval, escalation, and auditing work. That means mapping out a typical day or week in a team’s life and inserting the agent where it adds value without breaking accountability.
Operationalize the agent role. Treat agents as tools that perform tasks, with documented inputs, outputs, and failure modes. Agree on who owns the agent, who reviews its outputs, and who is responsible for retraining or updating it. Put monitoring in place for accuracy, bias signals, and usage patterns. This goes beyond a one-time compliance check and rather becomes part of your ongoing maintenance. Finally, create simple playbooks: “If the agent flags a candidate, a human reviews this; if confidence < X, route to specialist.” These steps keep agents useful and reduce surprises.
NEW ONLINE COURSE — Mitigate AI Business Risk
Business leaders are under pressure from their boards and competitors to innovate and boost outcomes using AI. But this can quickly lead to starting AI projects without clearly defined, measurable objectives or exit criteria.
Learn how to implement proven risk mitigation strategies for starting, measuring, and managing AI projects. Along the way, get tips and techniques to optimize resourcing for projects that are more likely to succeed.
The easiest mistake is to equate job value with task lists. Jobs include invisible work like relationships, customer trust, informal mentoring, institutional memory, and little acts that keep customers coming back. When someone leaves, those gaps suddenly appear. Agents will handle many routine tasks well, but they won’t replicate human relationships or the local knowledge people carry.
Start by mapping out both explicit tasks and the informal, hard-to-quantify work people do. Use interviews, shadowing, and exit conversations to capture examples. Who brings in certain clients, who smooths cross-team friction, who is the go-to for product knowledge? Make these contributions visible in performance frameworks and in succession plans.
Rethink how you define “impact.” Instead of counting only tasks automated, measure outcomes such as customer retention, speed to resolve edge cases, and revenue influenced by personal relationships. That will keep the focus on what humans uniquely deliver and where agents should augment, people.
Thanks for reading The AI MEMO! Share this thought-provoking post with your network.
Too many AI projects are run by IT with only a nod to HR. But HR owns the lifecycle: hire, learn, retain, redeploy. If agents change what work looks like, HR needs to shape that change. Start by aligning workforce planning with how agents will change tasks and skills. Which roles will be partly automated? Which skills will rise in value? Build upskilling pathways and internal marketplaces so people can move into higher-value roles instead of being let go.
Treat workforce planning as continuous. Use data from recruiting, performance and retention to spot where agent use correlates to turnover or to changed outcomes. Create governance: who approves new agents, what ethical checks are required, and how do you audit for bias and accuracy? Finally, prepare managers. Many will worry about status and roles in flatter networks; give them frameworks to evaluate people by impact and knowledge, not just by direct reports. HR’s job is to keep the organization resilient and to make the human side of agent adoption practical and fair.
Summary
Three things matter if you’re responsible for people in an organization moving toward Agentic AI. Integrate agents into real workflows with clear owners, handoffs, and monitoring. Surface and protect the invisible human contributions like relationships, institutional memory, and customer experience, and measure the impact that is greater than the sum of all tasks. Lastly, make HR central to planning: map skills, create re-skilling paths, and govern agent rollouts across the full hire-to-retire lifecycle.
Take these next steps: Map a single workflow and add a one-page agent playbook, interview colleagues to uncover invisible work, and add agent governance to your next workforce planning meeting. Start small, keep humans visible, and let workforce planning guide the broader change.
Equip your team with the knowledge and skills to leverage AI effectively. Book a consultation or workshop to accelerate your company’s AI adoption.
Join my bi-weekly live stream and podcast for leaders and hands-on practitioners. Each episode features a different guest who shares their AI journey and actionable insights. Learn from your peers how you can lead artificial intelligence, generative AI, agentic AI, and automation in business with confidence.
