Trump Champions “Superintelligence,” Redefining AI’s Value Through Its Potential to Expand Human Capabilities

Renaming AI to emphasize its capabilities and value aligns with industry discussions on strengthening human capabilities
AI supplements specialist knowledge, making “superhuman labor” a reality and expanding the individual’s role
Broader responsibilities bring greater accountability for verification, making human judgment a core skill

President Donald Trump has formally declared that the US government will use “superintelligence (SI)” instead of “artificial intelligence (AI)” in all official documents. The change is intended to give the technology’s capabilities and value fuller expression in its name, echoing industry discussions about using AI to strengthen human capabilities. As AI supplements human expertise, “superhuman labor”—in which one person takes on work across several fields—has also become a reality. With the scope of individual work expanding, the judgment needed to assign tasks to AI and verify the quality of its output is emerging as a core skill.

Trump Announces “Superintelligence” Rebrand 

According to CNN on September 22, local time, Trump made a surprise announcement at the 81st United Nations General Assembly in New York that he would rebrand the term AI itself. He argued that the name must change to convey the technology’s capabilities and impact. The word “artificial” makes the intelligence sound fake, Trump said, although it is anything but fake and is a remarkable technology. He added that “super” sounds better than “artificial” and describes the technology far more accurately. The aim appears to be a shift in perceptions through a new name to replace one that, in his view, understates the technology’s value.

Trump made clear that he intended to incorporate the change into official US government documents and promote its adoption internationally. He said “artificial” would be replaced by “super” in all future US official documents and urged other countries to follow suit, expressing hope that documents worldwide would use the same term. Before the announcement, Trump had held a poll on his social media platform, Truth Social, asking for an alternative to what he called the inaccurate name AI. Having offered “Superior Intelligence” and “Supreme Intelligence,” among other options, he presented “Super Intelligence” as the new name before world leaders at the UN General Assembly. The White House also included his statement that AI would henceforth officially be called “Super Intelligence” in its published highlights of the speech.

AI That Strengthens Human Capabilities and Industry’s Vision of Intelligence Augmentation

Trump’s perspective is consistent with the industry’s emphasis on strengthening human capabilities through technology. IBM states in its Principles for Trust and Transparency that AI is intended to augment human intelligence, making the expansion of human capabilities and potential a goal of its technology development. When Google unveiled its video creation tool Flow last year, it likewise said the tool would help creators turn ideas into videos and experiment with new forms of expression. The premise is that advances in AI should translate into stronger human creative and professional capabilities. This positive assessment of the technology’s capabilities and utility also resonates with the rationale behind Trump’s proposed name, “superintelligence.”

Evidence from workplaces already shows AI supplementing employees’ specialist knowledge. Last year, researchers from Harvard Business School, the University of Pennsylvania’s Wharton School and other institutions conducted a product development experiment involving 776 employees of global consumer goods company Procter & Gamble (P&G). They assigned participants real business problems and examined the quality and content of their proposals with and without AI. Research and development staff using AI tended to consider a product’s commercial viability, while business staff also examined its technical feasibility. By adding information supplied by AI to knowledge from their respective fields, employees brought a wider range of perspectives to their proposals. The researchers concluded that AI helped share expertise across departments and made up for gaps in employees’ product development experience.

AI Proficiency Emerges as a Key Hiring Criterion

These changes are also shaping the skills employers seek. In a report based on a survey of 31,000 knowledge workers across 31 markets last year, Microsoft (MS) and LinkedIn found that 66% of managers involved in hiring and related decisions said they would not hire a candidate without AI skills. The report also identified demand for employees in nontechnical roles who could incorporate tools such as ChatGPT and Copilot into their work. As AI enables employees with specialist knowledge to handle a wider range of tasks, proficiency with the tools has gained weight in hiring decisions. Heavy AI users in the survey experimented with new ways of using the technology, revised their questions until they obtained the results they wanted, and found and applied prompts suited to their work. The ability to assign tasks to AI according to their requirements and refine the results has thus become part of practical AI proficiency.

Corporate training is becoming more focused on developing these practical skills. Global energy technology company Honeywell has launched a Generative AI Academy to help employees use the tools and cultivate staff who can expand AI adoption across the company. Rapid changes in AI technology have also increased the need to retrain employees. In its 2025 Global AI Jobs Barometer, global consultancy PwC warned that even when companies hire people with AI skills, those skills can quickly become outdated without continued investment in learning. Employees must keep learning new tools and features and how to apply them to their responsibilities. The report therefore identified support for employee skills development as a key action for companies seeking to make full use of AI.

Table 1. Changes in Workforce Skills and Management Priorities as AI Adoption Expands

Human-Centered AI Use and Its Connection to “Superhuman Labor”

Developing these skills gives rise to superhuman labor: people who combine specialist knowledge with the ability to operate AI can carry out research, analysis, development and other work together, increasing the volume of work an individual can manage. Doing so requires the ability to divide an assignment into smaller tasks, decide which parts to give to AI and assemble the separate results into a finished product. Human knowledge and experience are what turn AI’s processing power into tangible results. Viewed against this shift in work, SI can also be interpreted as a proposal to understand AI with the people who use it at the center and to develop their capabilities.

Labor economics research has also advanced the case that AI could expand the range of work in which human expertise can be applied. In a 2024 paper published by the National Bureau of Economic Research (NBER), David Autor, a professor at the Massachusetts Institute of Technology (MIT), examined AI’s potential to support human decision-making by combining information, rules and accumulated experience. His argument is that workers with the foundational knowledge their jobs require could use AI to undertake more complex tasks in fields such as healthcare, legal document drafting and software development. Autor presented this as a feasible direction for deploying the technology, explaining that AI could broaden the application and raise the economic value of human expertise. The argument also supports the interpretation that exceptionally productive workers derive their competitive advantage from applying the knowledge they have built to a wider range of tasks.

The Rise of the “Agent Boss”

As the range of work to which expertise can be applied expands, individual roles change as well. Employees take on the management responsibility of assigning multiple tasks to AI, monitoring progress, reviewing results and deciding whether to move them to the next stage. In its 2025 Work Trend Index, MS described employees who build and direct AI agents as “agent bosses.” Managers surveyed for the report expected agent training and management to become part of their teams’ routine work within five years. The importance of this role has also been raised in finance. In a Goldman Sachs example reported by the Financial Times (FT) last September, partner Kerry Bloom said she used AI to refine project ideas and reduce the time spent on work, while cautioning against excessive reliance on the technology. As the amount of work a person can handle grows, so does the importance of reviewing the results and deciding whether to use them.

In this process, the ability to manage output quality could become a distinct performance criterion. If an AI-drafted document omits necessary information or fails to reflect the context of the work, colleagues who receive it must bear the burden of checking and supplementing the content. In a survey published in Harvard Business Review (HBR) last September, BetterUp Labs and Stanford researchers reported that 41% of respondents had encountered such AI output. Handling each instance took an additional two hours on average. The researchers called it “workslop” and recommended that companies clearly define both the purpose of AI use and quality standards for its output. Their finding suggests that assessing actual productivity gains requires examining the time spent on subsequent review and revision alongside an individual’s speed of work.