National Wealths: What AI Lacks Is the Ability of Institutions to Use It Practically

- Companies believe that “AI” boosts productivity at a rate exceeding official figures

- Nearly 9 out of 10 institutions use “AI” regularly in at least one area of their business

- 8 out of 10 employees reported an increase in their personal productivity

- 37 percent of institutions say AI has made a difference in their operating profits

National Wealth Management, in its latest “Thought Leadership” report, noted that most of the returns generated from artificial intelligence (AI) over the past three years went to companies that develop 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 companies in the S&P 500 index, the main U.S. stock market benchmark.

The report suggests that the next phase will be different, as the technology has become widely available and its usage costs have declined; therefore, merely possessing it no longer distinguishes one company from another. What the AI sector currently lacks is not the technology itself, but the ability of institutions to deploy it practically. This shift will gradually transfer a larger share of opportunities from AI developers and their infrastructure to the companies using it, although this transition is still in its early stages.

The report points out that it is now difficult to find a major company that does not use AI in some form. A global survey conducted by McKinsey in 2026, which included executive leaders, showed that nearly 9 out of 10 institutions use it regularly in at least one area of their business. Employees also seem to welcome it, as 8 out of 10 participants stated that AI increased their personal productivity. However, only 37 percent of institutions reported that AI had made a difference in their operating profits, the same percentage recorded a year ago. The proportion of institutions that reported an impact on pre-tax, pre-interest profits of 5 percent or more did not exceed just 6 percent.

The report explained that while a tool that saves an employee 20 minutes when preparing a report may make their workday easier, it rarely leads to reduced company costs unless the organization’s structure itself is redesigned around this technology.

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

The report clarifies that while potential gains appear substantial, a recent study conducted by Boston Consulting Group (BCG) in 2025, covering more than a thousand companies, revealed that only 5 percent of companies were creating actual value by using AI on a large scale, while 60 percent reported little or no gains. Nevertheless, leading companies achieved more than three times the shareholder returns compared to other companies over the past three years, although these top performers were often advanced in this field even before the emergence of AI.

Size also plays a crucial role, as large firms possess larger datasets and bigger budgets, and adopt artificial intelligence technologies at a faster pace than smaller companies. In the United States, 37 percent of firms with 250 or more employees were using AI in spring 2026, compared with less than 20 percent of smaller firms, according to the U.S. Census Bureau.

The report also cited official statistics that are beginning to reveal a similar picture; U.S. labor productivity (output per hour worked) rose by about 2.4 percent annually since the beginning of 2024, compared with 1.6 percent 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 and business services sectors, which are most exposed to AI, where productivity 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 showed that firms believe AI is boosting productivity at a rate higher than what official figures indicate, noting that realizing additional revenue takes time, and they expect this effect to nearly double in 2026.

The report also notes that for investors, the focus is no longer solely on companies developing AI technologies, but is increasingly shifting toward firms 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 raising efficiency and lowering costs. Second, the company’s ability to retain the savings achieved 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.

The report pointed out that despite the promising opportunities AI offers, there remain three main challenges investors should take into account. First, the timing factor, 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 profits.

1. The center of financial returns is shifting from infrastructure companies, such as chipmakers and cloud model providers, to operational firms capable of generating added value from technology applications.

2. Markets are witnessing a clear gap in returns, with adoption rates nearing 90 percent, while only 37 percent of firms are achieving financial returns, and just 6 percent capturing the largest share of profits.

3. The obstacle is no longer access to the technology itself, but managerial capability to restructure the work environment, lead change, and clearly measure return on investment.

4 - Indicators show growth in productivity within the most technology-intensive sectors, led by the financial sector, professional services, and information technology.

5 - The strongest opportunities lie with companies that combine high wage structures, significant pricing power, exclusive data assets, and a strong track record of execution.

6 - The transformation requires a patient and selective approach to exposure, particularly since the curve is still in its early stages and profit impacts may lag behind market expectations.