Artificial intelligence (AI) has rapidly evolved from an experimental technology to a core driver of business transformation. McKinsey & Company’s latest research, The State of AI: How Organisations Are Rewiring to Capture Value, provides an in-depth look at how businesses are integrating AI into their operations, particularly generative AI (gen AI), and the challenges they face in scaling its impact. While adoption is increasing, many organisations still struggle to implement the best practices necessary to fully harness AI’s potential.
AI adoption on the rise
AI is no longer a niche tool used by tech companies—it has become a mainstream business capability. According to McKinsey, more than 75% of surveyed organisations have deployed AI in at least one business function. The use of generative AI has also surged, with 71% of organisations now regularly employing it, a significant increase from earlier in 2024. Industries such as finance, healthcare, retail, and manufacturing are integrating AI for customer service automation, fraud detection, personalised marketing, and supply chain optimisation.
However, AI adoption varies widely by company size and sector. Larger organisations with annual revenues exceeding US$500 million are more likely to have dedicated AI teams and structured implementation strategies. Smaller businesses, on the other hand, often lack the resources or expertise to scale AI effectively.
Leadership and AI governance
One of the report’s key findings is that strong leadership is crucial for successful AI adoption. In nearly 30% of organisations, AI governance falls under the direct oversight of the CEO. This executive involvement is strongly correlated with higher returns on investment (ROI) from AI initiatives. Companies with well-defined AI governance frameworks tend to see better financial outcomes and operational efficiencies, as they can more effectively align AI initiatives with overall business objectives.
Despite this, many organisations lack structured AI governance, leading to fragmented adoption and underutilisation of AI’s potential. Companies that fail to establish clear AI leadership often struggle with integration, accountability, and risk management.
Restructuring workflows to maximise AI’s potential
Merely deploying AI tools is not enough—companies must rethink how work is done to fully benefit from AI’s capabilities. The report highlights that 21% of organisations have significantly restructured workflows to accommodate AI. These changes often involve breaking down traditional departmental silos and fostering cross-functional collaboration between IT, operations, and business units.
Organisations that redesign workflows around AI see substantial performance gains, particularly in cost reduction and efficiency improvements. In contrast, companies that implement AI in isolated functions without integrating it into broader processes often fail to realise its full value.
Managing AI-related risks
With AI adoption comes an increasing focus on risk management. Companies are becoming more proactive in addressing issues such as data accuracy, cybersecurity threats, and intellectual property concerns. The rise of generative AI has introduced new challenges, particularly regarding misinformation, biased outputs, and ethical concerns around content creation.
To mitigate these risks, organisations are developing AI risk management frameworks that emphasise transparency, accountability, and compliance. While some companies have made significant progress in this area, many still lack comprehensive strategies for managing AI risks at scale.
The changing workforce: skills and adaptation
AI is reshaping the workforce, creating new job opportunities while also disrupting traditional roles. Many companies are hiring AI specialists, such as data scientists and machine learning engineers, to drive innovation. At the same time, organisations are investing in reskilling programmes to help existing employees adapt to AI-powered workflows.
Automation is eliminating some repetitive tasks, freeing up employees to focus on strategic and creative work. However, workforce transformation remains a challenge, as many employees remain uncertain about AI’s impact on their jobs. Companies that successfully integrate AI into their operations prioritise change management and employee engagement to ease the transition.
Challenges and future outlook
Despite AI’s rapid adoption, McKinsey’s research suggests that most organisations are still in the early stages of full-scale implementation. Less than a third have adopted the best practices necessary for maximising AI’s value, such as setting clear key performance indicators (KPIs), establishing AI centres of excellence, and fostering trust in AI-driven decision-making.
Looking ahead, AI’s role in business will only continue to grow. Organisations that take a strategic approach—by investing in AI governance, restructuring workflows, managing risks effectively, and preparing their workforce—will be best positioned to gain a competitive advantage in the digital economy. Those that fail to integrate AI into their broader business strategy risk falling behind.
McKinsey’s research underscores that AI is no longer just a tool—it is a fundamental shift in how businesses operate. As organisations continue to rewire their processes and structures, the companies that take AI seriously and invest in its potential will lead the next wave of digital transformation.
