How is artificial intelligence (AI) reshaping the business world? That is the question global consultants McKinsey address in their latest report, The State of AI: How Organizations Are Rewiring to Capture Value.
Based on a global survey of more than 1,300 respondents across industries, the report charts the rapid rise in AI adoption over the past year and shows how leading firms are fundamentally restructuring their operations to unlock value.
According to the study, 72% of respondents say their companies have now adopted AI in at least one business area, up from 55% in 2023. More striking still is that just a year after generative AI tools such as ChatGPT entered the mainstream, more than half of companies are already using them, with two-thirds expecting to increase investment in the next year.
Larger firms are significantly ahead of their smaller counterparts not only in adopting AI but in scaling it across their organisations. They are also more likely to be seeing a tangible return with McKinsey estimating that generative AI could add up to £3.3 trillion in annual global productivity gains.
Commitment from the top is critical in making the most out of these new technologies in organisations where the CEO is directly involved in AI governance such as setting policy, defining objectives, or overseeing risk, the chances of delivering measurable business value are nearly twice as high with half of companies reporting financial benefits from AI having CEOs leading the charge as compared to just 29% of those seeing no such impact.
But it’s not only about strategic leadership as capturing real value from AI demands also demands operational change. The report identifies twelve organisational enablers essential for scaling AI ranging from having a clear strategy and strong cross-functional collaboration, to robust performance tracking and investment in upskilling. Yet few firms are doing this well and fewer than one-third say they’ve implemented even half of these enablers demonstrating the large gap between AI’s potential and its actual deployment.
Talent has emerged as a critical bottleneck with nearly 60% of organisations saying they are actively reskilling employees to work with AI tools, a figure that rises to 71% among firms already seeing a financial return. At the same time, 44% of companies have hired new talent specifically for AI roles over the past year with the most in-demand positions including data engineers, machine learning specialists, AI product owners, and prompt engineers.
Despite these efforts, there’s a growing mismatch between organisational needs and available talent with only 23% of respondents believing that their company has the AI expertise it needs to scale effectively. This shortfall isn’t limited to technical staff with companies also struggling to recruit product managers and senior leaders who understand how to integrate AI into business processes and manage AI-enabled teams.
To deal with this, some firms are responding by building internal training academies or partnering with universities to develop AI talent pipelines whilst others are turning to consultants or outsourcing to fill urgent gaps. However, the longer-term challenge is that most companies need a workforce strategy that combines hiring, reskilling and redeploying staff to meet a rising demand for AI literacy across all functions.
Despite headlines on fears of widespread job losses due to AI, these are not borne out in the data with just 8% of respondents expect AI to lead to a significant reduction in overall head count. Instead, most see it to boost productivity and free up human talent for higher-value work with nearly half of companies believing that AI will reshape how employees spend their time by reducing manual tasks while increasing focus on decision-making, strategy, and creativity.
Not surprisingly, generative AI is being used most widely in marketing and sales (36%), product and service development (33%), and service operations (32%).
These are areas where AI augments human creativity, automates repetitive tasks, and draws insights from vast data sets. For example, businesses are already using generative AI to personalise customer outreach, generate content at scale, and rapidly prototype new products and for those organisations using AI in marketing, 40% say it has had a measurable impact on revenue growth.
Therefore, the question facing most businesses is no longer whether to adopt AI, but how to adopt it. For the º£½ÇÊÓƵ economy, the message from the McKinsey report is that our businesses must act now or risk falling behind. In a digital, globalised economy, AI adoption is no longer optional but necessary and if firms continue to lag in investment, talent development and integration, there will be a further growth in the productivity gap resulting in a slowdown in innovation and fewer opportunities for growth.
Certainly, if we do not encourage and support the embedding of AI into businesses infrastructure, services and industrial policy, the º£½ÇÊÓƵ’s edge in innovation and entrepreneurship will be at risk with serious consequences for the economic growth of the nation.
