Artificial intelligence (AI) may create more jobs than it eliminates over the next four years, but that projection offers little comfort to employees whose roles are already being reshaped by automation. The bigger question facing organisations is no longer simply how many jobs AI will create or displace, but whether their workforces will have the skills, opportunities and organisational support to navigate the transition.
According to a latest forecast by Gartner, AI is expected to generate 10.6 million jobs globally while eliminating 8.9 million by 2030, resulting in a net increase of 1.7 million positions. However, the employment gains are unlikely to be evenly distributed. Gartner estimates that more than 20 per cent of the global workforce, or approximately 435.5 million employees, will need to adapt to changes in their jobs, including new responsibilities, workflows and ways of working.
The distinction is important. AI’s impact on employment may extend well beyond outright redundancies. Organisations could retain employees while fundamentally changing what they expect them to do. Roles that once involved repetitive analysis, documentation, coordination or routine decision-making may increasingly require employees to interpret AI-generated insights, exercise judgement and manage more complex responsibilities.
For HR leaders, this creates a challenge that cannot be addressed through technology training alone. Workforce planning will need to become more closely connected to business strategy, with organisations identifying which capabilities are becoming redundant, which are gaining importance and where employees can be redeployed rather than replaced.
Gartner also highlights another less visible consequence of AI adoption: delayed hiring. It estimates that five million positions globally will have experienced hiring delays by 2030 as businesses postpone recruitment while assessing the impact of AI investments. This could particularly affect fresh graduates and employees entering the workforce, as organisations reconsider the need for traditional entry-level roles. Even when positions are not formally eliminated, fewer opportunities to gain initial workplace experience could create a longer-term talent pipeline challenge.
The disconnect between technology adoption and workforce preparedness is already visible in India. Kyndryl’s 2026 Readiness Report found that around 60 per cent of Indian organisations investing in AI and machine learning were reporting positive returns, compared with 57 per cent in 2025. However, 37 per cent reported disagreements between their chief human resources officers and chief technology or information officers over AI strategy.
The findings suggest that technology investments and people strategies are not always moving in the same direction. While businesses are increasingly integrating AI into everyday workflows, the implications for job design, employee development and workforce deployment may not be receiving equal attention.
Around 85 per cent of Indian organisations surveyed had deployed AI beyond pilot projects. Yet 70 per cent said they had more AI pilots than they could realistically scale, while 58 per cent reported that innovation frequently stalled after the proof-of-concept stage. These figures point to a wider organisational challenge: implementing AI is not the same as preparing an organisation to work differently.
The Kyndryl findings also raise questions about how much support employees are receiving during this transition. When organisations introduce automation without clearly communicating its impact on roles, responsibilities and career progression, uncertainty can become an obstacle to adoption. Employees may be expected to work with new systems without understanding how their performance will be evaluated or what capabilities they need to remain relevant.
The responsibility therefore falls on HR to make workforce transformation a continuous process rather than a one-time reskilling exercise. This means mapping existing skills, identifying emerging roles, creating internal mobility pathways and giving employees opportunities to develop capabilities before their current responsibilities change. Managers will also need to be equipped to lead teams in which human judgement and machine-generated intelligence increasingly work together.
There is also a need to reconsider how organisations measure productivity. If AI allows employees to complete certain tasks faster, the gains should not automatically translate into expectations of higher workloads or reduced headcount. Businesses will need to consider how the time saved can be redirected towards problem-solving, innovation, customer engagement and more meaningful work.
Ultimately, Gartner’s projected net increase in jobs does not guarantee a smoother employment transition. The gains will depend on where new roles emerge, whether businesses invest in developing talent and how effectively employees are supported through changing career requirements. For HR, the real test of AI adoption will not simply be how much work technology can take over, but how much opportunity organisations create for the people who remain at the centre of it.