CEO of AI-powered performance review firm says annual evaluations weren’t designed for the AI era: ‘The practice just hasn’t kept up’

The article argues that annual performance reviews are an outdated, backward-looking process and that AI can reduce managers' administrative burden by automating feedback and documentation. David Hassell of 15Five said some firms already conduct reviews four times a year, though he recommends at least two per year paired with continuous weekly feedback. The piece is mostly commentary on workplace management practices rather than a direct market-moving event.

Analysis

This is less a “productivity software” story than a budget reallocation story. If AI meaningfully compresses manager-admin time, the first-order winner is not just workflow vendors but any software layer that sits inside HR operating systems and can become the system of record for feedback, goals, and promotion evidence. The second-order effect is that firms will increasingly buy outcomes, not forms; that favors platforms that can prove engagement lift and manager time savings, while hurting legacy performance-management modules whose differentiation was compliance and documentation rather than decision quality.

For Korn Ferry, the risk is not that demand disappears overnight, but that the consulting attach rate weakens as clients standardize and automate more of the review process. The slow-burn threat is margin compression over the next 6-18 months if AI-enabled alternatives reduce the hours needed for review design, calibration, and manager training. That said, the near-term impact is likely limited because performance management is embedded in broader talent advisory budgets, and buying cycles are long; this is more of a share-gain/loss narrative than an immediate revenue shock.

The contrarian view is that “more frequent feedback” can create new friction: higher cadence increases manager accountability, legal exposure, and data quality requirements, especially in regulated or unionized environments. If AI makes reviews easier to document, it can also make adverse action easier to evidence, which may slow adoption in companies that fear litigation. The biggest catalyst would be a large enterprise case study showing reduced attrition or higher promotion accuracy over 2-3 quarters; absent that, adoption likely remains incremental rather than disruptive.

Key Decisions for Investors

• Maintain a tactical underweight/short bias on KFY into any strength over the next 3-6 months; the thesis is multiple pressure from AI-led self-service talent workflows and slower consulting attach, with downside limited if broader advisory demand holds.
• Long a basket of AI-enabled HR workflow beneficiaries on pullbacks: NOW, CRM, and DAY over a 6-12 month horizon; these names can monetize workflow automation more directly than point solutions, offering better upside if enterprises standardize performance management in software.
• Pair trade: long enterprise workflow software vs short legacy HR services exposure, using NOW or CRM against KFY; target 10-15% relative outperformance if AI adoption shifts spend from labor to software over the next two reporting cycles.
• Avoid chasing pure-play HR-tech names without clear distribution advantages; if the market starts pricing broad adoption before proof of ROI, the risk/reward deteriorates quickly because implementation friction can delay monetization by 2-4 quarters.
• Watch for earnings call language over the next 1-2 quarters around ‘manager efficiency’ and ‘AI-assisted reviews’; a measurable uptick in adoption metrics would be the catalyst to cover shorts and rotate into the winners.