The market for artificial intelligence in HR is growing at nearly 25 per cent annually. Platforms such as Workday, SAP Joule and Microsoft Copilot promise to collapse silos across hiring, learning, performance and workforce planning. On the surface, momentum appears undeniable.
Beneath it, something more troubling is emerging.
According to AIHR’s HR Priorities 2026 report, 98 per cent of organisations say urgency around AI has increased. Fifty-nine per cent must demonstrate measurable impact within the next 12 months. Yet 91 per cent admit they are not fully prepared to build an AI-enabled culture.
This is not a gap. It is a chasm.
Urgency without readiness does not accelerate transformation. It creates anxiety—followed by rushed adoption, shallow pilots and mounting frustration when results fail to materialise.
A familiar scene
Consider a common moment inside HR teams today. A senior leader asks for an AI roadmap. A pilot tool is selected. A small task force is formed. Six months later, dashboards exist, demos look impressive—and very little about how work actually happens has changed.
The issue is not intent. It is architecture.
The structure problem
Across organisations, fewer than half of HR teams believe their structure can deliver on strategy. Confidence in systems is similarly weak. Most concerning, a majority do not feel equipped to lead digital transformation at all.
These are not capability gaps at the individual level. They are structural deficits. HR functions built for sequential workflows are now confronting technologies that demand integration, speed and cross-functional ownership.
As IT and business teams move faster—often under direct CEO mandate—HR finds itself trapped between pressure and preparedness. AI gets layered onto legacy processes rather than forcing a redesign of how work, decisions and accountability flow.
The fluency deficit
Only around a third of HR professionals feel ready to work with AI in a meaningful way. Most report little or no AI embedded into daily HR processes. Upskilling, where it happens, is largely self-directed and informal.
This matters because fluency determines influence. Teams that lack AI literacy struggle to co-own strategy, map workforce implications or shape reskilling agendas. Over time, they risk becoming order-takers rather than architects—consulted late, if at all.
The sidelining does not happen dramatically. It happens quietly, one project at a time.
The capacity question
AI’s promise is seductive. Employees could reclaim over 120 hours annually. Organisations anticipate productivity gains of around 30 per cent and meaningful reductions in labour cost per employee.
History urges caution.
Efficiency gains treated purely as cost savings often erode institutional capability. IBM’s experience—cutting roles aggressively only to rehire when growth stalled—is a reminder that productivity without reinvestment creates fragility, not resilience.
The harder choice is capacity reinvestment: using time saved to build skills, experiment and innovate. Few organisations appear structurally ready to make that decision. Without clarity, time reclaimed by AI simply gets filled with more work. The promise of “giving time back” collapses into pressure to do more, faster.
From headcount to skill count
AI is already absorbing coordination work once central to middle management. As work becomes modular and fluid, organisations still planning around static roles are falling behind.
Skills-based organisations are significantly more likely to innovate, adapt and deliver results. Most executives acknowledge this. Yet planning remains stubbornly anchored to headcount.
The shift required is from role inventories to skill portfolios—spanning employees, contractors and increasingly, AI agents. HR has an opportunity here to redefine how value is created through skills taxonomies, talent mobility and distributed leadership. The alternative is structural rigidity that constrains growth.
The architecture of hesitation
Legacy infrastructure plays a decisive role. Siloed data prevents holistic insight. Rigid workflows slow response. Traditional HR operating models actively dilute AI’s value.
Some organisations are experimenting with agile, outcome-driven pods that blend HR, IT and commercial expertise. AI is embedded into everyday decisions rather than treated as a separate initiative.
Most are not there. Instead, AI gets bolted onto incompatible architecture, producing pilots that do not scale and investments that disappoint.
What reinvention actually demands
AIHR outlines five priorities: co-own strategy, reinvest capacity, rewire for agility, move from headcount to skill count, and build AI fluency.
Read properly, these are not improvements. They are trade-offs.
Co-own strategy—or remain downstream.
Reinvest capacity—or absorb pressure.
Redesign structure—or protect legacy comfort.
This is why urgency alone is insufficient. Nearly everyone feels it. Few are equipped to act on it.
Creative paralysis
Every major shift in how work gets done renders certain organisational structures obsolete. New capabilities do not neatly layer themselves onto old systems; they replace them. Functions that redesign themselves for the new reality gain relevance. Those that do not slowly lose it.
What HR is facing today is not incremental change but structural replacement. Operating models designed for stability, linear workflows and role-based planning are colliding with technology that rewards speed, modularity and integration. Something has to give.
The data reveals a function caught in paralysis. Leaders understand what must change. They recognise the stakes. They see AI reshaping coordination, skills and decision-making in real time. Yet many remain structurally, culturally and technically unable to act on that understanding.
This paralysis has consequences. HR teams without AI fluency are excluded from enterprise-level conversations. Functions organised around headcount rather than capability limit organisational agility. Those unable to redesign for cross-functional work find themselves marginalised precisely when business demands speed, flexibility and collaboration.
This is not a temporary implementation challenge that will resolve with better tools or more pilots. It is a moment of replacement. Either HR redesigns itself for how work now happens, or it becomes a function that explains the future rather than shaping it.
Source – https://www.hrkatha.com/features/research/98-feel-urgency-to-deliver-on-ai-91-arent-ready/