[2/2] The state of AI in 2025. Agents, Innovation, and Transformation: Strategies for High Performance Companies (AI column)
Finishing. analysis In this report from McKinsey, I couldn't pass up the most interesting part of the study -- comparing conventional companies to high-performance companies. 6Percentage of organizations that have achieved significant AI impact on business These leaders have a strikingly different approach. McKinsey researchers define them according to two criteria:>5Percentage EBIT from AI and proven “significant” value from AI use The authors of the report use these companies as a golden image or a model for the rise, which should be followed by those who are not yet ready to report on the effect in the market. 5% of total EBIT.
Below are the differences between AI-Stokhanovites and other companies.
1Leaders set ambitious goals for AI Half of these companies say they intend to use AI to transform business, not just improve efficiency. According to the survey, they're in 3More often than others, they are aimed at radically rethinking their operations through AI. These companies see AI not as a tool, but as a new “operational mechanism” of the organization.
2High performers are rebuilding workflows for AI They're almost in 3 More often than not, they claim to have radically redesigned individual workflows when implementing AI. This is confirmed by statistics: fundamental redesign of processes is one of the most influential factors of success. (based on regression analysis). Simply put, leading companies are not limited to automating individual tasks, but are rethinking the sequence of actions, the roles of people and machines, and embedding AI at the heart of those processes. This approach requires more effort, but also brings a qualitatively different level of effect.
3Leaders are spreading AI wider and faster They are applying AI to a much larger number of functions and are moving faster in scaling pilots. In most functions, high performers already use AI, and in dealing with agents they are ahead of others: in each business function, leaders are at least three times more likely to progress to the stage of scaling agents. In other words, if a new technology emerges,6% try to implement it widely immediately.
4Direct responsibility of top management for AI agenda In such companies in 3 More often than not, there is agreement that their top leaders are committed to AI initiatives. (Take responsibility, personally promote the use of AI). Leaders don’t just sponsor, they actively participate. Without this cultural shift, large-scale change is difficult to implement. In fact, culture and leadership are becoming a major protective barrier. (moat) These companies distinguish them from their competitors.
5High performers invest more and systematically approach AI development More than a third of leaders spend more 20% of the total digital budget for AI is almost 5 more often than other companies. Around 75% of high performers are already at the stage of scaling AI or fully scaled it, while among the rest, only 33%. They are also increasingly hiring AI professionals and closing key talent and data gaps. All high-performing organizations implement six-dimensional practices n (strategy, talent, operating model, technology, data, implementation and scaling). For example, leaders are more likely to establish clear processes for validating human model output. (quality control)They have built AI tools into core business processes and track KPIs for AI solutions. Such scrupulous implementation gives them an advantage.
And then there's the FOMO effect on all non-high performers. (Fear of missing opportunity) It should be noted that the top-6Companies are turning AI into a competitive advantage through growth, innovation and organizational transformation, while many others are stuck with local improvements. This leads to a rupture where a small group of companies are already rewriting the rules and the rest risk falling behind.
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