Artificial intelligence has moved from hype to necessity. It is no longer an experiment – it’s the foundation of competitiveness. According to McKinsey’s March 2025 report, “The State of AI: How Organizations Are Rewiring to Capture Value,”corporations around the world are rebuilding their internal systems to make AI part of their business DNA. The goal is not just to use technology – but to reprogram the way organizations operate and make decisions.
McKinsey’s main conclusion is clear: the real value of generative AI (GenAI) doesn’t come from algorithms, but from how companies integrate it into management and workflows.
Over 75% of surveyed organizations already use AI in at least one business function, and adoption is growing rapidly. The frontrunners are large corporations with annual revenues above $500 million. These firms are restructuring operations, hiring AI talent, retraining employees, and building new risk governance systems.
The report shows a strong correlation between executive involvement and profitability from AI. 28% of companies say their CEO personally oversees AI governance, while 17% assign this role to the board of directors. Where the CEO takes responsibility, companies report higher EBIT impact.
Crucially, 21% of organizations have already redesigned core workflows to integrate AI.
McKinsey senior partner Alexander Sukharevsky explains:
“AI transformation isn’t an IT project – it’s a leadership issue. Without full engagement from the top, even the best technologies fail to deliver impact.”
Most companies are building hybrid AI management models.
• Risk, compliance, and data governance are fully centralized.
• Implementation, engineering, and adoption teams are partly decentralized across business units.
This “hub-and-spoke” approach helps balance control with agility. Large enterprises prefer central hubs, while smaller organizations opt for distributed models.
AI oversight practices vary widely. 27% of organizations review all AI-generated content before publication, while roughly the same share review less than 20%. Top risks include inaccuracy, cybersecurity threats, data privacy, and intellectual property issues.
Larger companies lead in mitigating these risks, focusing heavily on data protection and reliability – though transparency and explainability remain weak points.
McKinsey’s Alex Singla emphasizes:
“Winners are those building AI as infrastructure, not a collection of disconnected use cases.”
McKinsey identifies twelve key practices that correlate with higher returns from AI initiatives, including:
• Dedicated adoption teams,
• Clear roadmaps and KPIs,
• Internal communication about AI value,
• Role-based employee training,
• Mechanisms for trust and feedback among staff and customers.
However, fewer than one-third of companies follow most of these practices. Large enterprises are far ahead – with defined strategies, transformation offices, and internal learning programs.
As associate partner Bryce Hall puts it:
“The hype phase is over. It’s now about discipline – scaling, adoption, and measurable ROI.”
AI is reshaping hiring priorities. 13% of organizations have hired AI compliance specialists, 6% have added AI ethics experts, and data scientists remain the most in-demand professionals. While hiring challenges persist, they are easing as more professionals upskill. Around 40% of employees have already undergone reskilling, and many more will in the next three years. Most companies (38%) don’t expect AI to reduce headcount overall.
Job cuts may occur in customer service and logistics, while new positions are expected to grow in IT, engineering, and product development.
McKinsey senior partner Lareina Yee notes:
“The fear that AI will kill jobs is exaggerated. It’s not about elimination – it’s about evolution.”
AI adoption surged in 2024:
55% of companies used AI in 2023, 72% in early 2024, and 78% by the end of the year.
GenAI use rose to 71%.
The top areas of application include:
• Marketing and sales,
• Product and service development,
• Customer operations,
• Software engineering,
• IT management.
By sector, technology firms lead in code generation and R&D; telecoms focus on customer service; financial institutions on analytics; and professional services on knowledge management. AI tools are now part of executives’ daily routines. 53% of C-level leaders say they use GenAI at work, compared with 44% of middle managers. The shift shows that AI is no longer a tool for analysts – it’s becoming a strategic partner in decision-making.
Text generation remains the most common use of GenAI (63%), but image creation (36%) and code generation (27%) are rapidly expanding. Companies are moving toward multimodal AI – producing video, audio, and design content.
Organizations are beginning to see measurable returns from GenAI. Revenue in business units using AI has grown, in some cases by more than 10%, while costs have dropped across marketing, IT, and supply chain functions. Yet, at the enterprise level, most companies still report limited impact: 80% see little or no change in EBIT so far. This indicates that GenAI is delivering local functional benefits, but not yet full-scale corporate transformation.
McKinsey concludes that companies are entering a “rewiring” era – rethinking management, workflows, and culture around AI. Leaders are investing in infrastructure, talent, risk governance, and scaling capabilities. The next frontier is Agentic AI – autonomous systems that perform tasks independently and will redefine productivity.
For Kazakhstan, the McKinsey report offers valuable lessons on how to build an AI-driven economy:
1. Leadership Commitment.
AI only creates value when leaders take ownership. Government ministries and state enterprises must establish clear AI governance structures, not isolated pilot projects.
2. Reskilling and Education.
The workforce must evolve from basic users to AI architects. Kazakhstan needs large-scale digital reskilling programs and interdisciplinary education.
3. Data Infrastructure and Ethics.
Data governance and security require national coordination – dedicated centers of excellence and clear ethical frameworks for AI development. If these principles are applied, Kazakhstan can move from being a technology adopter to becoming a regional leader in intelligent governance and data-driven growth.
Alen Serik, expert of the portal EconomyKZ.org
