Companies are putting significantly more money into artificial intelligence as the technology moves from a specialist IT project to a business-wide investment. New research from Boston Consulting Group (BCG) shows that corporate AI spending has climbed from about 1.7 percent of revenue in late 2025 to 3.3 percent in 2026, effectively doubling in less than a year.
The findings come from BCG’s Applied AI Index 2026, based on a survey of 1,330 C-suite executives and senior leaders. More than 80 percent of AI spending now sits outside traditional enterprise IT budgets, according to BCG. Finance, marketing, customer service, operations and other business functions are becoming more directly involved in deciding where AI money goes.
AI is no longer simply software bought by the technology department. Companies are increasingly embedding it into products, workflows and business decisions, signalling a major change in how organisations view the technology.
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AI spending is moving beyond the IT department
Earlier AI adoption was often built around trials and small pilot projects. Now, businesses are spending more as they attempt to integrate AI into everyday operations.
BCG says nearly half of companies are already generating meaningful value from AI. This includes the 7.5 percent it classifies as “future-built” and another 41 percent that are actively scaling AI and outperforming their peers.
The strongest performers are also seeing wider business benefits. BCG found that future-built companies recorded 2.3 times the total shareholder return, 2.4 times the revenue growth and 2.8 times the EBITDA growth of lagging companies.
Many companies are still struggling to convert spending into measurable results. The difference is that AI investment is now spreading across the organisation rather than remaining concentrated in technology teams.
For business leaders, this creates a new responsibility. Tracking AI spending only through an IT budget may no longer show the true cost of adoption. Senior management will increasingly need a combined view of technology, people and operating costs when assessing whether AI investments are justified. It also means finance and operational leaders may have a larger role in AI planning, procurement and performance reviews. That is a major change in how AI is managed.
Back story: From AI experiments to enterprise strategy
The latest findings build on a very different picture from BCG’s 2025 research, when only about 5 percent of companies were generating substantial value from AI. Over the past year, investment has increased while more businesses have moved from testing individual tools to building AI capabilities into wider operations.
The development follows the rapid spread of generative AI tools, including workplace assistants, coding systems and customer service applications. As companies have become more familiar with these technologies, AI decisions have increasingly moved beyond traditional technology functions.
BCG’s latest research also points to the next stage of this transition: agentic AI. By 2030, 42 percent of companies expect to give AI agents real decision-making authority. However, only 5 percent currently have the necessary controls in place to do this safely.
That gap between ambition and governance could become one of the biggest issues for businesses. As AI systems become capable of taking actions rather than simply producing answers, companies will need stronger oversight, security, audit processes and cost controls.
What the spending surge means for businesses
The BCG research shows that AI is becoming part of the operating model of the modern business.
For Nigerian companies, this trend is worth watching closely. Businesses adopting AI will need to look beyond buying popular tools and ask where the technology can solve a specific operational problem or improve a measurable business outcome. Spending without clear ownership or targets can quickly become difficult to justify.
Successful AI adoption also involves people and processes, not technology alone. BCG says leading organisations are treating AI as an enterprise-wide programme, redesigning workflows, investing in skills and building governance alongside new systems.
As spending continues to rise, the companies that gain the most may not be those with the biggest AI budgets. They may be those that can connect investment to clear business priorities, train their people to use the technology effectively and maintain enough control to manage its risks.
AI has entered a new phase. The race is no longer simply about experimenting with the technology. It is increasingly about turning larger investments into measurable value while keeping increasingly powerful systems accountable.
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