National Investments: AI... From the Race to Develop Technology to the Battle for Profitability

A report titled “Artificial Intelligence: From Tech Makers to Beneficiaries,” issued by National Wealth Management’s Thought Leadership division, stated that over the past three years, most of the returns generated by artificial intelligence have accrued to the companies developing it, ranging from chip manufacturers and cloud service providers to model developers. In the second quarter of 2026, AI infrastructure-related companies accounted for roughly half of the earnings growth of S&P 500 companies, the benchmark U.S. stock index.

The report noted that the next phase is likely to be different, as the technology has become widely available and its cost of use has declined; thus, mere ownership no longer distinguishes one company from another. What the AI sector currently lacks is not the technology itself, but the ability of organizations to deploy it practically. This shift will gradually transfer a larger share of opportunities from AI developers and their infrastructure to companies that use the technology, although this transition is still in its early stages.

The report added that it is now difficult to find a major company that does not use AI in some form or another. A global survey conducted by McKinsey in 2026, which included executives, revealed that nine out of ten organizations use it regularly in at least one area of their business. Employees also seem to welcome it, as eight out of ten respondents said AI has increased their personal productivity.

Nevertheless, only 37% of organizations reported that AI had made a difference in their operating profits, the same proportion recorded a year ago. The percentage of companies reporting an impact on pre-tax, pre-interest earnings of 5% or more did not exceed just 6%.

The explanation lies in a relatively simple reason: a tool that saves an employee twenty minutes when preparing a report may make their workday easier, but it rarely leads to reduced company costs unless the organization’s work processes are restructured around this technology.

So, what distinguishes leading companies? Research consistently indicates that the difference lies in corporate management style, not in the tools they purchase. Among all the factors McKinsey tested in 2025, redesigning workflows was most closely associated with achieving AI-driven profit gains. In simpler terms, this means rebuilding processes around the technology rather than simply adding AI to existing operations. About three-quarters of the best-performing companies adopted this approach, compared to only a quarter of other companies. These leading firms are also characterized by senior leadership that takes responsibility for these efforts, measures their impact, and seeks growth alongside cost reduction.

Potential gains appear substantial, yet a recent study of more than 1,000 companies conducted by Boston Consulting Group (BCG) in 2025 revealed that only 5% of companies were creating real value through widespread AI use, while 60% reported little or no gains. However, leading companies achieved more than three times the shareholder returns of other companies over the past three years, even though these top performers were often advanced in this field even before the advent of AI.

Size also plays a crucial role, as large companies possess larger datasets and bigger budgets, and adopt AI technologies at a faster pace than smaller firms.

In the United States, 37% of companies with 250 or more employees were using artificial intelligence in spring 2026, compared to less than 20% of smaller firms, according to the U.S. Census Bureau. Official statistics are beginning to reveal a similar picture: U.S. labor productivity (output per hour worked) has risen by approximately 2.4% annually since the start of 2024, compared to 1.6% in the five years preceding the pandemic, according to the Federal Reserve Bank of Dallas. Much of this improvement is attributable to the information, finance and insurance, and professional services sectors, which are most exposed to AI; productivity in these sectors grew at roughly twice the rate of the rest of the economy.

Although it is still early, a survey of chief financial officers conducted by the Federal Reserve Bank of Atlanta found that companies believe AI is boosting productivity at a rate higher than what official figures show, noting that realizing additional revenue takes time. They expect this effect to nearly double in 2026.

For investors, the focus is no longer solely on companies developing AI technologies, but increasingly on those better positioned to leverage these technologies to achieve tangible operational and financial gains. While there are no definitive criteria that pre-determine winners, three key characteristics distinguish companies best placed to benefit from AI. First, high labor costs associated with cognitive tasks such as information management, analysis, writing, and customer service, where AI can contribute to increased efficiency and lower costs. Second, the company’s ability to retain savings rather than passing them on to customers, which depends on pricing power and customer loyalty and enhances profit margins. Third, ownership of proprietary or unique data that enables the company to deploy AI in ways difficult for competitors to replicate, providing a sustainable competitive advantage.

Despite the promising opportunities offered by AI, three main challenges remain for investors to consider. First, timing, as technological innovations often take longer to translate into tangible financial results than markets expect. Second, competition, as savings from AI adoption may lead to lower prices benefiting customers rather than enhancing corporate profitability. Third, the ongoing costs associated with operating and developing AI solutions, which may absorb a portion of expected gains and limit their positive impact on earnings.