Gartner: 85 Percent of Companies to Boost AI Spending Despite Unclear Returns

Companies around the world are accelerating their spending on artificial intelligence even though they cannot show it is paying off. A new Gartner study finds that only one in five organizations has managed to successfully scale AI across multiple departments at once, yet the vast majority of business leaders plan to spend even more on it next year.

The paradox of rising budgets

Gartner surveyed 1,303 respondents from organizations whose annual revenue exceeded $50 million in fiscal year 2025. The survey was conducted between January and April 2026. The results point to a situation the firm's analysts describe outright as a paradox: money is flowing into artificial intelligence faster than ever, but companies' ability to prove that money is paying off has essentially stalled.

According to the report cited by CRN Polska, even though only 22 percent of companies can claim genuine AI scaling beyond isolated pilots or single departments, as many as 85 percent of functional leaders say they intend to increase spending on it in the coming year. In 2025, organizations devoted an average of 12 percent of their functional budgets to AI.

Companies don't know what they're spending on

One of the study's most troubling findings is the extent of the financial opacity involved. About 11 percent of organizations admitted they have no idea how much their department actually spent on artificial intelligence in 2025. That means in one out of every nine companies, decisions about further investment are being made without basic knowledge of how much has already been spent or to what effect.

The gap between companies that measure results and those that don't is enormous. Organizations that rigorously track the return on their AI investment reported success in 81 percent of their initiatives. Where monitoring is loose or nonexistent, companies are unable to determine the profitability of nearly a third of their projects, 29 percent.

This lack of financial transparency increases risk as spending accelerates. Without disciplined measurement tied directly to business outcomes, organizations risk wasted resources and unmet expectations - Tina Nunno, Vice President and Gartner Fellow

Trendy projects versus profitable projects

The study also reveals a gap between what companies are most eager to deploy and what actually delivers returns. The most popular AI applications are cybersecurity threat detection and response and IT automation, each adopted by 54 percent of surveyed companies, followed by code generation, chosen by 44 percent of organizations.

Meanwhile, the highest real returns on investment don't come from these trendy areas but from less glamorous applications: intelligent IT resource and cost optimization (40 percent of respondents reporting returns), synthetic data generation (28 percent), and automated code generation and refactoring (23 percent). About 30 percent of AI spending goes toward productivity goals, which 75 percent of leaders cite as their primary investment objective, rather than directly toward revenue growth or innovation.

Gartner's recommendations

Tina Nunno recommends that functional leaders track every dollar spent on AI, broken down by outcome categories such as productivity, revenue growth, risk reduction, or innovation. This breakdown is meant to let companies defend their budgets to the board and pull the plug faster on projects that fail to deliver promised results.

For Polish companies that are only now increasing AI's share of their budgets, Gartner's findings serve as an important warning. Investing in artificial intelligence without a system for measuring results, even one based on simple metrics tied to specific business goals, risks repeating the global pattern: rising spending alongside uncertain results and no real knowledge of what actually works.

The report feeds into a broader debate over whether the current investment boom around artificial intelligence is translating into real corporate profits, or mainly into rising costs without a matching increase in revenue. Gartner stresses that while the technology is maturing, the financial discipline surrounding it is still lagging behind.