Business Transformation

Despite widespread improvements in employee productivity, only a small proportion of companies are translating artificial intelligence (AI) adoption into substantial financial returns, according to McKinsey’s 2026 State of AI survey. The report found that 80 per cent of respondents had experienced improvements in individual productivity through AI. However, only 37 per cent reported a positive impact on earnings before interest and taxes (EBIT), while just 6 per cent of organisations qualified as high performers in AI implementation. McKinsey noted that companies making the greatest progress are redesigning their operating models around products, customer journeys and business processes. Such an approach can accelerate decision-making, strengthen accountability and help businesses respond more quickly to changing priorities. The report emphasised that there is no universal operating model for achieving AI success. Instead, organisations need to simplify workflows, eliminate unnecessary handoffs and ensure resources can be redirected efficiently as business requirements evolve. Only 11 per cent of surveyed organisations had reached the stage of fundamentally rethinking work and value creation through AI. The findings also pointed to growing organisational complexity, with coordinator roles expanding at approximately 1.5 to two times the rate of line roles over the past five years. According to McKinsey, AI could help businesses reduce administrative complexity and improve coordination rather than introduce additional layers of processes and oversight. Stanford economist Erik Brynjolfsson, in a recent conversation with McKinsey, argued that businesses risk overlooking AI’s broader potential when they focus primarily on reducing workforce numbers. He highlighted the importance of reorganising work to take advantage of the new capabilities that AI makes possible. However, the report warned that excessive automation could undermine employee development by removing opportunities to acquire essential skills through routine tasks. If AI agents take over entry-level responsibilities traditionally used to build professional expertise, organisations could face a future shortage of experienced workers capable of exercising sound judgement. A separate survey on AI readiness revealed a significant difference between individual confidence and organisational preparedness. While 70 per cent of respondents said they felt personally ready to work with AI, only 27 per cent of leaders considered their organisations prepared for the changes associated with an agentic AI future. McKinsey stressed the need for clear AI governance frameworks that establish appropriate usage guidelines and define accountability. As an example, the report cited a global life sciences company whose policy requires AI to support employees without undermining human creativity, expertise, autonomy or oversight. Employees remain responsible for work produced with AI assistance. The report concluded that the organisations extracting the greatest value from AI would not necessarily be those deploying the largest number of AI agents or automating the most tasks. Instead, long-term success would depend on rethinking how businesses create value and aligning workflows, talent strategies and leadership practices with the capabilities of AI. Source: ANI