Over the past three years, the primary financial benefits from artificial intelligence (AI) have accrued to companies involved in creating the technology, including chipmakers, cloud service providers, and AI model developers. Even as recently as the second quarter of 2026, firms linked to AI infrastructure accounted for roughly half of the earnings growth within the S&P 500 index. However, experts suggest the next phase of AI adoption will shift value toward companies that effectively integrate and utilize AI, rather than those building the foundational technology.

Today, AI technology is widely accessible and relatively inexpensive, making possession of the technology alone insufficient for competitive advantage. Instead, organizations face a shortage of the capability to apply AI successfully within their operations. According to a 2026 global survey of executives, nearly 90% of companies employ AI regularly in at least one area of business, and 80% of employees report that AI has enhanced their personal productivity. Despite this widespread usage, only 37% of organizations indicate AI has translated into improvements in operating profit, a figure unchanged from the previous year. Moreover, just 6% report that AI has contributed an operating earnings before interest and taxes (EBIT) impact of 5% or greater.

The discrepancy between AI usage and profit gains is attributed primarily to how organizations structure their processes. Incremental time savings for employees do not automatically reduce costs unless workflows are fundamentally redesigned to leverage AI’s capabilities. Research highlights that companies achieving significant profits from AI tend to rebuild workflows around the technology rather than layering AI onto existing processes. Nearly 75% of top-performing companies have adopted this approach, compared to approximately 25% of others. Leadership engagement, measurable goals, and a focus on growth as well as cost reduction also distinguish successful organizations.

While only a minority of companies currently generate substantial value from AI, the rewards for those that do can be significant. A 2025 study of over 1,000 companies found that just 5% were creating AI value at scale, yet these firms achieved more than three times the shareholder returns of their peers over three years. Larger organizations, with greater data resources and budgets, tend to adopt AI more rapidly; in the U.S., 37% of businesses with 250 or more employees used AI in spring 2026, compared with under 20% of the smallest firms.

Initial productivity data corroborates these trends. Since early 2024, U.S. labor productivity has risen about 2.4% annually, surpassing the pre-pandemic rate of 1.6%, particularly in sectors heavily exposed to AI such as information services, finance and insurance, and professional services. However, experts caution it remains early to fully assess AI’s economic impact. A survey of chief financial officers found that companies expect AI-driven productivity gains to approximately double in 2026, indicating anticipated effects may lag current metrics.

For investors, the focus is increasingly on identifying companies poised to benefit most from AI use rather than those simply building AI technologies. Key traits associated with likely beneficiaries include large labor costs in tasks suited to AI automation (e.g., information handling, analysis, customer service), pricing power that allows firms to retain cost savings as profit, proprietary or unique datasets enabling customized AI applications, and proven management capability in executing and measuring AI-driven workflow changes. Sectors fitting this profile include financial services, insurance, professional business services, and information and media, with healthcare, retail, and certain industries showing potential yet slower progress.

Several risks remain. The timing of AI’s benefits is uncertain, with new technologies often taking years to affect financial performance noticeably, and market valuations potentially discounting anticipated gains prematurely. Competitive pressure may drive cost reductions for customers rather than higher margins for companies. Additionally, operational costs of running AI systems pose limits, as about 20% of firms report these expenses constrain AI use. Furthermore, given the theme remains partially dependent on AI infrastructure providers, volatility in those stocks could impact the broader AI-related investment landscape. Many conclusions are based on executive surveys, and respondents tend to be optimistic about their progress.

In summary, while the initial AI boom favored technology creators, the evolving landscape points toward a gradual shift in value toward end users who can effectively integrate AI into their operations. However, the transition is still in early stages, with profit improvements uneven and likely to materialize more fully over time, underscoring the need for careful and selective investment strategies.