Why companies are no longer “testing” artificial intelligence — they’re building on it.
There’s a quiet change in the language of corporate strategy and the business world is taking notice.
A year ago, executives spoke about pilots. Today, they talk about platforms.
According to McKinsey & Company’s 2025 State of AI Survey, 88% of organizations now report using AI regularly in at least one business function — up from 78% last year. More telling: over one-third of high-performing organizations allocate more than 20% of their digital-technology budgets to AI initiatives.
Those numbers may sound abstract, but they represent a major shift in corporate posture — from experimentation to infrastructure. AI has stopped being a research budget line and become a structural layer, fundamental in how companies operate, analyze, and decide.
When organizations spend 20 %+ of their tech budget on intelligence systems, it’s no longer about tools — it’s about business-model change.
The End of “Optional”
Executives once justified AI investment as a hedge against disruption. That has been reversed since. Now, the risk is not investing in AI.
McKinsey’s data shows that firms reporting the highest AI investment intensity also report the largest share of revenue boost — particularly in marketing, supply-chain, and product-development functions.
In financial services, this transition is even more pronounced.
The Bank of England noted in its Financial Stability in Focus (April 2025) report that institutions prioritizing AI-driven efficiency have shown “stronger operational resilience and improved cost control” amid volatility. The same report highlights AI’s role in automating compliance monitoring, risk modeling, and liquidity management — traditionally labor-intensive domains.
Markets Follow the Infrastructure
The numbers show us a bigger picture.
Global compute infrastructure spending in finance grew 34% year-over-year in 2025, driven largely by cloud-based model training and data-pipeline upgrades.
Asset managers, meanwhile, are quietly treating AI capabilities as a form of tangible asset — a balance-sheet line item that improves valuation multiples and investor confidence.
Analysts increasingly describe this moment as “digital leverage”: the idea that intelligence systems amplify the value of very dollar of labor and capital.
Where cost-cutting once defined automation, capability compounding now defines AI investment.
In other words, AI has become the new capex.
The Human Layer
This doesn’t mean humans are disappearing from the equation.
At the highest-performing firms, AI is augmenting judgment rather than replacing it.
Decision-support models are being embedded in leadership workflows — from strategic forecasting to pricing optimization — giving executives “augmented intuition.”
But this human-machine balance brings its own governance challenges.
As the Bank of England warns, firms adopting generative and predictive systems at scale “must develop model risk frameworks equal to their financial ones.”
Intelligence, in other words, needs oversight.
AI is infrastructure, not experiment.
What the Shift Means for Markets
The implications ripple far beyond corporate balance sheets.
If the world’s most efficient companies are allocating one-fifth of their digital budgets to AI, that capital will flow into the upstream layers — chips, cloud providers, data platforms, and regulatory technology.
In 2024, NVIDIA’s market cap briefly passed $3 trillion on the promise of AI demand.
Now, the demand is no longer theoretical — it’s contractual.
Enterprise procurement cycles are increasingly built around intelligence capacity: compute allocation, model licensing, and integration services.
This is why many analysts are calling AI the new electricity — essential, invisible, and economy-wide.
The New Baseline
We may look back on 2025 as the year AI stopped being a differentiator and became the default.
From central banks analyzing speech tone to retailers optimizing every shelf, the infrastructure of decision-making itself is changing.
It’s not that AI is replacing human insight — it’s systematizing it.
Companies that treat intelligence as an asset, not an optional add-on, are building the next layer of market advantage: foresight at scale.