HR Is About to Hire AI Agents: What to Do Before 2026
Companies are preparing to bring artificial intelligence agents into their workforces. A new report from Korn Ferry says 52% of talent leaders plan to introduce autonomous AI agents next year. These agents will have identities, permissions, and defined responsibilities-just like colleagues.
"This isn't some distant future scenario," said Bryan Ackermann, Head of AI Strategy and Transformation at Korn Ferry. HR tech vendors are already creating employee-like records for AI agents, and Microsoft is issuing security IDs to non-human workers. The infrastructure for human-AI teams is being built now.
What this means for HR
Talent acquisition will expand from hiring people to orchestrating teams of employees, contractors, and autonomous systems. HR will need playbooks for sourcing, onboarding, and tracking both humans and AI agents. Leaders must know when to let AI run, when to override it, and how to handle conflicts in mixed teams.
Jeanne MacDonald, CEO of Korn Ferry's RPO division, is clear: AI will change operations, but it won't replace human judgment. "We need to embrace AI but not lose sight of the bigger picture. Talent acquisition is about people, and human intelligence will always be the differentiator."
The forecast: agents at massive scale
Korn Ferry projects that by 2036, autonomous agents will outnumber human workers 1,000 to 1 in customer service. Their presence will grow across manufacturing, logistics, and even management support. That scale demands structure, governance, and new skills inside HR.
The entry-level risk you can't ignore
Many firms are eyeing back-office and junior roles for automation. The report warns this could drain the leadership pipeline. Those entry-level hires often become your future managers. "The savings look great on your 2026 budget," the report asks, "but what happens in 2029 when your most experienced employee is a bot?"
David Ellis, SVP of Talent Transformation at Korn Ferry, puts it plainly: "It would be a mistake to stop hiring entry-level people. These are the fastest adopters of new technology. If you don't have these people, but your competitors do, then your rivals are going to be faster and more agile."
The recommendation isn't to eliminate junior roles, but to redesign them. Let AI handle the repetitive work so early-career employees can build skills in creativity, problem-solving, and relationship management. Only 22% of surveyed companies have linked succession planning with AI readiness-this is a gap HR can close.
Your 90-day action plan
- Define the "AI agent" job family: Document use cases, scope of authority, handoff points to humans, and escalation rules.
- Create identity, access, and records: Work with security to issue unique IDs and permissions for agents. Track them in HR systems with clear owners and lifecycle events (onboard, update, offboard). See Microsoft Entra ID workload identities for patterns.
- Onboarding/offboarding for agents: Standardize provisioning, environment setup, prompts/instructions, test data, and kill-switch procedures. Treat it like day-one and last-day checklists.
- Performance and quality: Define KPIs (accuracy, timeliness, exceptions, customer CSAT), review cadences, and shadow tests. Track human time saved and error rates alongside risk incidents.
- Controls and accountability: Set approval thresholds, audit logs, bias checks, and incident response. Align with frameworks such as the NIST AI Risk Management Framework.
- Job redesign for early careers: Convert routine tasks into "AI-supervisor" rotations. Give juniors responsibility for prompt updates, exception handling, customer escalations, and process improvement.
- Succession planning with AI readiness: Map critical roles, identify AI-augmented capabilities, and build development paths that include agent supervision, data literacy, and change leadership.
- Comp and costing model: Treat agents as OPEX with clear cost centers (licenses, infrastructure, oversight). Compare unit economics to FTE and contractor baselines without hollowing future leadership.
- Procurement and vendor risk: Standardize evaluation criteria: data handling, security posture, model updates, IP, and service-level guarantees. Require sandbox trials and red-team tests before scale.
- Policy and ethics: Write practical rules for human-in-the-loop, disclosure to employees/customers, and acceptable use. Train managers on when to pause or override an agent.
- Change management and comms: Explain "why we're doing this," what changes, and what grows in value (judgment, empathy, creativity). Make it clear that AI is a tool-people are accountable for outcomes.
- Data and integration: Clean the data agents will use. Set up safe connectors, role-based access, and redaction for sensitive info.
Hiring AI agents without losing your bench
Balance automation with development. Keep hiring at the entry level, then reallocate work: let AI clear queues while humans handle exceptions, customers, and projects that expand judgment. Rotate juniors through "agent ops" roles so they learn systems thinking and product mindset early.
In performance reviews, credit employees for improving agent outcomes, not just doing more tasks themselves. This builds a culture where people lead systems, instead of competing with them.
Governance that actually works
Pick a cross-functional owner for each agent (HRBP + business + security). Give them a simple scorecard: value delivered, risk incidents, training data changes, customer impact. Meet monthly and decide: scale, fix, or retire.
Document every agent's purpose, inputs, outputs, and escalation rules in plain language. If a new manager can't understand it in five minutes, it's too complex to deploy at scale.
Where to focus this year
- Customer service and back-office workflows with clear rules and measurable outputs.
- Agent-supervised apprenticeships for early-career hires.
- Manager training on decision overrides, exception handling, and coaching with AI in the loop.
- Link succession planning to AI fluency, not just role tenure.
Bottom line for HR
AI agents are entering the workforce next year. Treat them like teammates with clear jobs, controls, and performance expectations. Use the efficiency to level up human work, not strip out your future leaders.
If your team needs practical upskilling to move fast, see AI courses by job for curated paths.
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