In Friday’s edition of Goldman’s Briefings newsletter, Argenti outlined four strategies on “How to Get the Most Out of AI in Your Career” as autonomous agents increasingly take on complex tasks once reserved for humans.

1. Become a conductor, not just a doer

Argenti argues that the modern professional must evolve from executing work to orchestrating it. Success, he explains, will no longer hinge on the code one personally writes or the analysis one single-handedly produces. Instead, the mark of leadership will be managing agile teams of human and AI collaborators—delegating, coordinating, and integrating outputs to achieve greater results than either type of contributor could alone. “Your ability to manage a hybrid team of human and AI resources” will be key to thriving, Argenti says.

2. Ask provocative, non-obvious questions

One of the most valuable human skills in an AI-driven environment is curiosity, according to Argenti, who urged employees to “get creative with AI, posing provocative, non-obvious questions.” While AI systems excel at synthesizing existing data, they struggle to generate breakthroughs without human provocation. By posing bold, imaginative, and sometimes unconventional questions, people can push AI beyond predictable patterns and uncover insights that would otherwise remain hidden. “While AI excels at refurbishing existing knowledge,” Argenti writes, “its true creative potential is unlocked by human curiosity.”

Rahsaan Shears, principal and aIQ program lead at KPMG U.S., previously told Fortune that AI adoption has moved from a “fear factor” that AI will displace most white-collar work to “cognitive fatigue” as workers realize that AI’s maturity level is that of a toddler’s. She said there’s a “persistent need for human engagement,” and critical thinking, questioning, and adaptability are increasingly valuable human skills to have.

3. Build a personalized toolkit of AI models

Rather than relying on one dominant platform, Argenti advises professionals to curate a customized mix of AI tools suited to different tasks. No single model will outperform all others across the board, he notes. The key lies in knowing which system excels at which function—whether it’s data analysis, content generation, or coding—and assembling those systems into a tailored digital toolkit. “The expert will curate a personal toolkit of models and assistants,” according to Argenti, and “know[s] which one to deploy for which task.”

4. Verify AI outputs with skepticism

Argenti cautions that even the most sophisticated AI systems can produce “plausible-sounding errors.” As these tools become more deeply integrated into workflows, validating their results will demand both domain expertise and investigative rigor. “A blend of deep knowledge and a detective’s skepticism,” he writes, will be essential to separate reliable insights from confident falsehoods.

KPMG’s Shears flagged this as a particular pitfall, telling Fortune that she’s seen a propensity among younger workers, supposedly “digital natives,” to trust their devices and technology. Because AI is “more early in its maturity, they need to be more skeptical, which is a different kind of relationship than they historically had from a digital interaction perspective.”

The human edge in the Age of AI

Argenti’s message is ultimately one of empowerment: AI is not replacing human talent but redefining what it means to be skilled. The future belongs to those who combine technological fluency with creativity, discernment, and leadership—the qualities that machines still struggle to replicate.

For this story, Fortune used generative AI to help with an initial draft. An editor verified the accuracy of the information before publishing.