With the rising demand for artificial intelligence, more and more companies are succumbing to pressure to adopt AI.
This phenomenon, according to Senthil Muthiah, senior partner at McKinsey & Company, “is the growing urgency organisations face both externally, from the hype in the supply market and competitive landscape, and internally, from board and investor expectations to integrate AI to find new ways to be competitive, efficient, and innovative. Companies are compelled to adopt AI to capitalise on its benefits and avoid falling behind.”
However, according to McKinsey research, 86% of leaders feel their organisations are not well-prepared to adopt AI in day-to-day operations.
Fully harnessing the impact of AI in organisations is challenged by the need for foundational changes to the operating model and broad leadership support. Moreover, pressure builds due to compliance and governance concerns, as well as change management mandates.
Proceed with caution
Muthiah warns of the consequences of making AI investments before clearly defining the problem organisations aim to solve.
“AI delivers value differently across various aspects of work. Each organisation has unique economic leverage points where AI can create a disproportionate impact. Identifying and prioritising these areas is essential to ensure focused investment and effort,” he said.
According to the McKinsey executive, the organic approach to AI adoption, or the broad-based “AI everywhere” approach adopted by many companies, tends to be uncoordinated and unscalable.
“When these initiatives fail to scale, organisations struggle to justify continued investment. Misaligned AI efforts can cause challenges in integrating AI with existing systems, ultimately limiting transformation opportunities,” he said.
The danger of this approach is that it places unrealistic expectations on AI solutions, leading to misaligned assessments and expectations.
“The objective should not be to apply AI indiscriminately to every task but to deploy it strategically, tying investment to value, and recognising the need for development of agents as with other employees,” Muthiah posits.
Sequencing AI adoption
When resources and capabilities are limited, Muthiah said, “The instinct is to pursue AI broadly. The discipline is to sequence it narrowly.”
The instinct is to pursue AI broadly. The discipline is to sequence it narrowly. Senthil Muthiah.
He said that organisations should start by focusing on structured, co-located, rules-driven work, such as call centres, accounts payable, and contract matching.
“These environments have clear processes and centralised control points, which means faster deployment and measurable outcomes. They also produce the organisational confidence and proof points needed to unlock investment for harder problems,” he said.
This helps organisations identify where AI can create the greatest business impact, or the areas where automation or AI-assisted work can significantly reduce costs, improve productivity, or enhance efficiency.
For example, a services company may use AI voice bots in call centres to handle routine customer inquiries at a lower cost, while allowing human agents to focus on more complex concerns. In financial institutions, AI can help coordinate workflows in middle-office operations that still rely heavily on manual processes.
According to Muthiah, every organisation has these high-impact opportunities, but few have clearly identified and prioritised them. He said this prioritisation becomes the organisation’s AI sequencing strategy.
Muthiah added that technology itself is rarely the biggest challenge in AI transformation. Based on McKinsey research, technology accounts for only about one-third of successful transformation efforts. For every dollar spent on AI tools and platforms, organisations may need to spend twice as much on change management, employee training, and adoption support to realise the benefits fully.
Because of this, he advised organisations not to move too quickly into new AI use cases until employees and internal processes are ready to absorb the change.
“In short: focus where the path is clearest, concentrate where the economics are strongest, and pace deployment according to your organisation’s actual capacity to change — not simply its capacity to buy software,” Muthiah said.
Striking a balance
Muthiah posits that there should be a balance because rushing to adopt AI can create inefficiencies and distractions within teams, especially when organisations prioritise technology over strategy.
“Quick wins” led by individuals that are uncoordinated and unscalable can detract from broader transformations. Teams can become distracted by pilots and accumulate disconnected experiments rather than a coherent transformation,” he warns.
AI hype can distort expectations around the pace, scale, and feasibility of transformation.
“The organisations that resist the pull of euphoria and focus on the substance are more likely to reach the growth and productivity goals they set at the outset,” Muthiah added.
The organisations that resist the pull of euphoria and focus on the substance are more likely to reach the growth and productivity goals they set at the outset. Senthil Muthiah
For companies already feeling behind in AI adoption, Muthiah believes the most practical first step is to focus on clarity and alignment by defining a value-driven AI strategy.
“A structured approach can help companies move from pressure to action effectively,” he said.
He added that the first step is to assess the current state and readiness by evaluating the organisation’s existing technology infrastructure and data quality.
“Concurrently, determine human readiness. Do you have the right champions, workforce leadership, and change management capabilities? From these assessments, identify gaps and opportunities for AI adoption,” Muthiah said.
Once organisations understand their readiness gaps, the next challenge becomes prioritisation. “Organisations should consider prioritising large wins, not early wins,” he reminded.
Organisations should prioritise large wins over early wins. Senthil Muthiah
Lastly, he urged organisations to engage leadership by aligning on the value at stake, ensuring AI initiatives are integrated into broader business strategies. He also underscored the importance of fostering collaboration by bringing employees along on the journey.
“By starting with these foundational steps, companies can transition from reactive pressure to a proactive, value-driven AI strategy,” Muthiah concluded.
