As technology companies increasingly cite AI-led transformation while reshaping their workforces, experts are questioning whether the march toward becoming “AI-native” reflects genuine business reinvention or has become a convenient justification for layoffs.
Globally, several technology companies have tied workforce changes to AI-led transformation. Firms including Atlassian, Block, Meta, IBM, and Oracle have cited AI-driven efficiency gains, organisational restructuring, or a shift toward AI-first operations while reshaping their workforces.
“’AI-native’ has become one of the most overused terms in business today. While it sounds like a destination that companies have already reached, in reality, for most organisations, it is still an aspiration. A truly AI-native company has not simply deployed a few AI tools or automated isolated tasks but redesigned how work gets done from workflows and decision-making to operating models and customer delivery. By that definition, very few companies are AI-native today,” Husain Tinwala, CEO, upGrad Rekrut, explained.
According to the upGrad Rekrut Tech Talent Landscape Report, only 16% of organisations have redesigned workflows end-to-end around AI. The remaining 84% are introducing AI within existing structures rather than transforming them altogether.
This distinction, Tinwala added, matters because an increasing number of workforce reductions are being linked to AI transformation. If an organisation has not fundamentally redesigned its operations, it becomes difficult to attribute workforce reductions solely to AI-driven productivity gains.
Neelabh Shukla, Chief Business Officer, Careernet, echoed this, adding that AI-native announcements arriving without corresponding details or demonstrated productivity outcomes invite scrutiny. The organisations making this transition can show what they are building, not just what they are promising and restructuring away from.
Workforce reductions are influenced by a combination of factors like economic conditions, margin pressures, post-pandemic hiring corrections, changing business priorities, and cost optimisation efforts. While AI may be part of the story, it is rarely the entire story.
“In previous business cycles, organisations explained restructuring decisions through business performance, market conditions, or financial realities. Today, AI is sometimes a singular explanation, even when multiple business drivers are at play. Employees deserve a more complete understanding of these decisions,” Tinwala shared.
Meanwhile, Shukla said, transparency practices are improving unevenly. The more progressive organisations are explaining the specific workflows being automated, the roles most likely to evolve, and the reskilling pathways available. The gap is in distinguishing AI-driven change from other concurrent business pressures. Organisations making that distinction help employees and the broader market assess the change on its merits.
“Most companies won’t publish whether the AI paid off before they made the cut. They may be seeing the productivity and the business outcomes first. But most reports indicate that the transition rate from proof-of-concept to real-world deployment is still extremely low. In many cases, the restructuring is arriving ahead of the proof. And that’s self-defeating, because the capability you need to make AI productive is the capability you risk cutting or scaring off when you move too early,” said Anuj Agrawal, Founder & CEO of Zyoin Group.
Shukla argues that AI-native transformation can create value for all stakeholders—boosting shareholder returns, improving customer experience, and enabling employees to move into higher-value work by reducing repetitive tasks. In this view, AI is a productivity driver that can lead to more meaningful employment if managed well.
On the other hand, Agrawal contends that while AI’s long-term benefits may eventually extend to workers and customers, the immediate gains are accruing largely to shareholders and leadership. He argues companies have a responsibility to prioritise reskilling and redeployment over layoffs, treating employees as talent to be transitioned rather than costs to be cut.
Published on June 7, 2026
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