By 2026, HR technology is unlikely to be treated as a peripheral function running pilots in hiring or learning. Instead, it will increasingly shape how work is designed, how skills are deployed, and how people-related decisions are made at scale.
The inflection point, however, is not artificial intelligence itself. AI is already embedded in most large organisations. What is changing is the expectation placed on leadership: who is accountable for these systems, how decisions are governed and explained, and how organisations ensure technology augments rather than displaces human judgement.
This shift frames how Preemita Singh, President and CHRO at Havells India, and Ramachandran Sundararajan, Chief People Officer at HCLTech, are thinking about HR technology as they look toward 2026.
From experimentation to operating infrastructure
Both leaders agree that the phase of experimentation is drawing to a close.
Singh said HR technology in 2026 would be “deeply aligned with core business priorities while staying rooted in human values”, with AI embedded across recruitment, learning, performance and wellbeing.
Crucially, she does not position AI as a standalone capability.
“AI will be embedded across recruitment, learning, performance, and wellbeing—not as isolated solutions, but as components of a connected and ethical digital ecosystem.”
This distinction signals a shift away from fragmented HR tech stacks toward integrated systems that shape workforce planning, talent allocation and capability assessment at scale.
At HCLTech, Sundararajan said this transition is already underway.
“AI has already become mainstream and in HCLTech it is getting deployed enterprise-wide, including within the People function, with ‘human in the loop’.”
The emphasis on “human in the loop” is central. As algorithms influence hiring decisions, performance insights and career mobility, organisations must define where judgement resides—and who is accountable when outcomes are shaped by systems rather than individuals.
Skills intelligence replaces static workforce planning
A consistent theme across both perspectives is the shift toward skills as the organising principle of talent systems.
Singh pointed to the emergence of “sophisticated skills-intelligence platforms that provide real-time visibility into workforce capabilities and future needs”, particularly for organisations operating across both corporate and manufacturing environments.
Importantly, she does not frame skills intelligence as a learning initiative.
“Organisations must view skills as a strategic asset, not a training output.”
This reflects a broader change in workforce planning. Fixed role architectures and annual manpower plans are giving way to dynamic models that continuously map skills, availability and potential.
Sundararajan echoed this transition, noting that talent management is “gravitating towards a skills-first approach”, enabled by AI and automation that support “intelligent decision making around skills and hiring”.
“This means building ecosystems that can dynamically map, assess, and deploy skills across the workforce.”
In this model, HR technology becomes less about process efficiency and more about ongoing resource orchestration—matching skills to demand continuously, not episodically.
Where automation will be most visible
Despite AI’s broad reach, both leaders identified specific HR processes where impact will be most pronounced.
Singh pointed to recruitment, learning and workforce planning. Talent acquisition, she said, will increasingly rely on “capability-based assessments and AI-driven shortlisting” to improve speed and fairness.
Learning, meanwhile, will move away from standardised programmes.
“Learning will become far more adaptive and personalised, meeting the needs of both corporate and factory teams through formats such as microlearning, vernacular content, and simulation-based modules.”
Automation, she added, will reduce administrative load, allowing HR teams to focus more on culture, inclusion and long-term capability building.
Sundararajan described a similar trajectory, with automation reshaping “talent supply chains” through skill-based matching and optimisation. Performance management, he said, will shift toward “continuous, data-driven insights”, while learning becomes “highly personalized through AI-powered recommendations”.
The shared emphasis is not efficiency alone, but responsiveness—the ability to sense, decide and act faster as business conditions change.
The expanding remit of CHROs and CIOs
As HR technology becomes more consequential, leadership accountability is expanding.
Singh said CHROs will be expected to actively shape digital roadmaps while protecting organisational culture and human values. This includes preparing employees for change, supporting managers through large-scale transformation, and building confidence rather than fear.
“CHROs will increasingly operate as strategists, technologists, and behavioural scientists rolled into one.”
Sundararajan stressed the growing interdependence between technology and talent leadership.
“CIOs and CHROs must deliver greater efficiency and agility, driving productivity through value stream transformation and leveraging AI to optimize processes and outcomes.”
In practical terms, HR and IT can no longer function as parallel silos. Decisions about platforms, data architecture and governance now directly shape trust, capability and organisational culture.
Trust, governance and psychological security
If AI is becoming unavoidable, trust is becoming non-negotiable.
Singh was explicit about the risks organisations must anticipate, particularly around data governance and transparency.
“Employees, humans at workplaces, us all seek Psychological Security.”
She emphasised the need for assurance that personal and family data is handled responsibly, calling for the “highest standards of professional ethics and cautious approach” in data and information handling.
Sundararajan argued that these issues must be addressed by design, not after deployment.
“As AI adoption scales, leaders need to anticipate challenges such as ensuring unbiased decision-making, safeguarding sensitive data, complying with evolving regulations, and making AI-driven outcomes explainable.”
At HCLTech, he said governance frameworks test AI systems for fairness, privacy, data integrity and explainability—not as afterthoughts, but as core requirements.
Where leaders should invest—and where restraint matters
Neither leader pointed to a single “must-have” tool for 2026.
Singh highlighted the value of unified skills-intelligence platforms that connect recruitment, development, succession planning and workforce deployment, enabling faster and more informed responses to change.
Sundararajan, however, cautioned against technology-led decision-making.
“Prioritize investments that deliver tangible business outcomes rather than chasing technology as a novelty.”
He argued for focusing on high-impact use cases, building quickly, and refining continuously—ensuring that technology amplifies human potential rather than becoming an end in itself.
When judgement becomes the differentiator
By 2026, the defining question for organisations will no longer be whether they use AI in HR, but how responsibly, transparently and intelligently they use it.
As HR technology moves into the core of organisational decision-making, the differentiator will not be tools, but judgement—who designs these systems, who governs them, and how clearly decisions are explained to the people affected by them.
For CIOs and CHROs alike, the next phase is less about speed and more about stewardship.