FEATURE
Future-built companies are 3.5 times more likely than laggards to establish dedicated AI transformation programmes. They are also considerably more disciplined about measuring financial returns.
According to BCG, 95 % of future-built organisations use clear performance indicators or directly track AI’ s contribution to their profit and loss accounts.
By comparison, 47 % of laggards measure AI value only directionally, if at all.
This distinction is particularly relevant to enterprises seeking to justify investment in an environment where technology budgets compete with other business priorities.
Rather than treating AI as a collection of individual projects, leading organisations manage it as a coordinated, multiyear business transformation.
They identify a limited number of high-value opportunities, redesign processes around those opportunities and establish accountability at senior leadership level.
For CIOs, this requires closer collaboration with finance, operations and business-unit leaders to ensure AI initiatives are linked directly to commercial objectives.
AI spending moves beyond IT
The transformation of AI from an experimental technology into a mainstream business investment is also changing how organisations allocate their budgets.
BCG found that average corporate AI spending has increased from approximately 1.7 % of revenue in late 2025 to 3.3 % in 2026.
Perhaps more significantly, over 80 % of AI expenditure now falls outside traditional enterprise IT budgets.
Investments increasingly include AI-enabled products, workforce training, data transformation, governance and operational redesign.
“ AI spending has doubled in less than a year, and much of it no longer sits in the enterprise IT budget,” said Michael Grebe, managing director and senior partner at BCG and a coauthor of the report.“ Companies that still treat AI solely as an IT cost category are underestimating both what they’ re spending and what it could return.”
This development is reshaping the CIO ' s responsibilities.
Technology leaders must increasingly act as enterprise-wide coordinators, maintaining visibility over AI investments distributed across departments while ensuring that technology spending produces measurable value.
The challenge is particularly relevant for organisations operating with constrained budgets or fragmented technology environments.
Without central visibility, separate business units may duplicate investments, adopt incompatible platforms or create additional governance challenges.
BCG ' s findings suggest that the most successful organisations are not simply spending more. They are making deliberate decisions about where resources should be allocated and how returns will be measured.
Agentic AI raises the stakes
While generative AI has dominated enterprise technology discussions, the next major transformation is expected to come from agentic AI.
Unlike systems that primarily generate content or respond to instructions, AI agents can perform multistep tasks, interact with enterprise applications and, within defined boundaries, make decisions with varying degrees of autonomy.
BCG estimates that agentic AI accounted for 17 % of overall AI value in 2025, rising to 22 % in 2026. By 2030, its contribution is projected to reach 39 %.
Among future-built companies, 44 % report already realising full value from agentic AI, compared with just 2 % of laggards.
The potential applications extend across customer service, financial operations, software development, supply chains and business process automation.
For African enterprises, agentic AI could create opportunities to streamline labour-intensive processes, improve service delivery and support operations across geographically dispersed markets.
However, the transition from AI assistance to autonomous decision-making introduces new risks. www. intelligentcio. com
INTELLIGENT CIO AFRICA
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