Corporate AI spending booms, but investors may wait a while for the payoff

The rush of corporate money into artificial intelligence is accelerating, but for investors hoping for quick wins that might be gained from AI boosting companies’ profitability, the path to real value may be slower and more uneven than the headline numbers suggest.

A new report from Boston Consulting Group finds that companies plan to double their spending on AI in 2026, lifting it to about 1.7% of revenues, more than twice the increase projected for 2025.  Nearly all companies in the survey say they will keep investing in AI even if it does not generate immediate returns.  

A parallel study by Capgemini points to the same direction of travel. According to the research, executives expect to allocate 5% of their annual business budgets to AI initiatives in 2026, up from 3% in 2025, as they pivot toward long-term value creation and away from low-impact experiments.  

These reports suggest that corporate AI adoption is becoming a structural theme, not a passing fad, but the same surveys also hint that the translation from corporate enthusiasm to durable shareholder returns, especially in broad-based equity portfolios held by retail investors, will likely be a multi-year process.

BCG’s research, based on a survey of 2,360 executives across 16 markets and nine industries, including 640 chief executives, underscores how central AI has become in the C‑suite with 72% of CEOs now saying they are their company’s main decision maker on AI, and four out of five more optimistic about AI’s ROI potential than they were a year ago.   Ninety percent believe AI agents will deliver measurable returns in 2026.  

Capgemini reports that 38% of large organizations already have generative AI use cases in operation, and six in ten are exploring agentic AI applications.  Many are pausing lower-value projects to concentrate on functions with well-defined processes and measurable outcomes. 

Be realistic on timing

Those findings help explain why AI-linked stocks, from chipmakers to cloud platforms and software providers, have already enjoyed powerful re-ratings. For now, markets are paying up for the potential embedded in those corporate plans. But the surveys also highlight reasons for investors to temper expectations around timing.

First, the spending itself is front-loaded, while the benefits are back-loaded. Both BCG and Capgemini stress that organizations are channeling money into infrastructure, data, governance, and workforce upskilling; areas that are prerequisites for AI at scale but rarely yield immediate revenue growth.

Capgemini notes that companies aim to focus on “infrastructure, data, governance, and workforce upskilling, laying a strong foundation for AI adoption and impact.”  Those are long-cycle investments, with payoff periods that may extend well beyond the horizon of a typical retail investor’s news-driven expectations.

Second, the surveys reveal a gap between confidence and realized impact, especially in Western markets. BCG’s work finds that roughly three quarters of CEOs in India and Greater China are confident AI will pay off, compared with 52% in the US and even lower shares in the UK and Europe.  In many Western companies, a material portion of AI investment is motivated by fear of falling behind peers or responding to competitive pressure, rather than by clearly articulated value cases.  

Spending driven by strategic necessity but without rigorous return hurdles can dilute margins before it strengthens them, especially in sectors with limited pricing power.

Third, corporate AI strategies are becoming more selective, which may favor specific winners rather than broad benchmarks. Nearly two thirds of organizations in Capgemini’s study say they are shifting resources away from lower-value projects to higher-impact areas.  That suggests future AI gains may accrue disproportionately to companies that can marry strong data assets, clear use cases, and disciplined governance; attributes that wealth managers can evaluate, but that passive retail portfolios may not fully discriminate among.

Advisors’ positioning

For advisors serving US retail clients, the implication is not to shun the AI theme, but to frame it as a long-duration structural story rather than a short-term trade. The evidence from BCG and Capgemini shows that boards and executives are committing real capital, redesigning processes, and retraining workers to embed AI into the core of their businesses.   

But the same evidence also underscores that much of today’s investment is foundation building. Returns are likely to emerge unevenly across sectors and regions, and over several years rather than quarters. For retail investors exposed through diversified equity allocations, the AI boom may look less like a sudden windfall and more like a gradual, compounding influence on productivity, profitability, and competitive dynamics.

In that sense, the current phase of AI investing resembles previous waves of transformative technology: initial exuberance, heavy infrastructure and capability spending, and then, eventually, a sorting of durable winners from the rest.