Companies are increasingly expected to move beyond simply deploying artificial intelligence (AI) tools and begin redesigning workflows, operating models and employee roles to unlock broader enterprise-level value, according to a research report by McKinsey.
The report said organisations that successfully integrate AI into the way work is fundamentally performed could gain a significant competitive advantage, while companies that focus primarily on improving individual employee productivity may find it difficult to translate AI adoption into sustained business outcomes.
Based on a global survey of 750 employees and business leaders, the research identifies three broad stages of AI transformation: enablement, automation and reinvention. While organisations are increasingly experimenting with AI and integrating it into existing processes, most remain in the first two stages, with only 11 per cent of surveyed leaders saying their organisations have reached the reinvention stage.
Nearly 90 per cent of respondents said their organisations remain focused either on enabling employees to use AI more effectively or on automating existing workflows. McKinsey said this indicates that most businesses are still in the early phases of their AI transformation journeys and have yet to make deeper changes to how work is structured and delivered.
A significant gap also exists between individual and organisational readiness for AI adoption. Around 70 per cent of respondents said they personally felt prepared to adopt and use AI, but only 27 per cent of leaders believed their organisations were ready to make the broader changes required for an increasingly agentic AI environment.
The report found that organisational readiness has a stronger relationship with enterprise value creation than individual preparedness. Organisational readiness accounted for 48 per cent of the difference between leaders who reported successfully capturing value from AI and those who did not. By comparison, personal readiness accounted for 25 per cent of the difference.
McKinsey also highlighted workflow redesign as one of the most important factors determining whether AI adoption translates into measurable business value. During the enablement stage, leaders were 5.3 times more likely to report enterprise value capture when their organisations redesigned workflows than when existing workflows remained unchanged.
The finding suggests that simply making employees faster through AI tools may not be sufficient to improve overall business performance. Companies need to identify how the additional capacity created by AI can be redirected towards higher-value activities, strategic priorities and more complex tasks.
As organisations progress towards greater automation, the importance of AI-fluent leadership and employee capability building is also expected to increase. McKinsey found that leaders with highly AI-fluent teams were 3.9 times more likely to report enterprise value capture.
Similarly, leaders who received support and training to develop new skills were 3.3 times more likely to report successful value creation from AI. This highlights the importance of investing not only in technology but also in workforce capabilities, leadership development and organisational change.
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According to McKinsey, the largest opportunity lies in the reinvention stage. At this stage, companies redesign work, employee roles and operating models around AI rather than simply using technology to automate existing processes.
The report concluded that AI transformation will increasingly depend on an organisation's ability to continuously experiment, redesign and adapt. Companies that can change their workflows and operating models faster than competitors are likely to be better positioned to convert rapidly evolving AI capabilities into sustained enterprise value.
The shift, therefore, is expected to be from AI adoption as a technology initiative to AI-led transformation as a fundamental business strategy.
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