Market Theme: Tariff Truce, U.S. Budget Package, and Credit Rating Downgrade

This past week in financial markets was driven by three dominant themes: the U.S.–China tariff truce, former President Donald Trump’s expansive budget plan, and the unexpected credit rating downgrade of the United States. But beyond macroeconomics, a different kind of fear dominated online discourse—AI replacing jobs, and companies freezing hiring due to automation.

A trending topic known as the “AI hiring freeze” has emerged, where companies are not only reducing headcount due to economic tightening but also actively cutting roles that can now be replaced by AI or robotics. From Microsoft’s 6,000 job cuts to stories of investment firms halting analyst recruitment, many are wondering: What should we learn or do in a world increasingly dominated by AI?

The Rise of AI, But the Decline of Basic Skills?

While many assume that with AI, knowledge becomes redundant—since “you can just ask a chatbot”—this is a dangerously flawed mindset. Relying entirely on AI without understanding the fundamentals turns humans into redundant intermediaries. As one hiring panel recently noted, over 300 applications for junior analyst positions were rejected primarily because candidates lacked “real knowledge.” In the age of AI, human reasoning becomes a premium skill.

AI models, especially those built on large language models (LLMs), often generate content that sounds convincing but can be factually incorrect or lack contextual awareness. Without foundational understanding, users cannot verify what’s right or wrong. That makes the ability to form coherent, logical insights—based on real knowledge—a non-negotiable competitive advantage.

Why the Ability to Ask the Right Questions Matters More Than Ever

One of the most underappreciated but vital skills in the AI era is the ability to ask meaningful, structured, and outcome-oriented questions. This ability is not just about curiosity—it's foundational for effectively utilizing AI tools. Whether you’re a manager analyzing regulatory impacts like IFRS 15 on insurance companies or a developer reviewing AI-generated code, unless you know how to break down problems and interrogate outputs, AI will fail to deliver value.

A senior executive illustrated this through an example where AI initially gave a flawed explanation of revenue recognition rules. Only after breaking the problem into component parts and asking AI targeted questions did the output become usable. The key takeaway? The user must know what to ask and how to guide the system to the correct path. Without this skill, AI becomes more of a liability than an asset.

Don’t Ignore “Human Skills”

Ironically, in the age of machines, it is human skills—communication, empathy, collaboration—that are proving most difficult to automate. The ability to present ideas clearly, interpret group dynamics, or offer emotional intelligence in client meetings is increasingly valuable. Many organizations report a severe shortage of professionals who possess both hard skills (domain expertise) and soft skills (like the ability to navigate internal politics or negotiate deals).

The worst combination in the modern workforce is someone with high technical potential but poor human skills. Not only do they struggle to collaborate, but they can also become destabilizing to team cohesion. Unfortunately, some educational institutions have leaned too far into soft skill training at the expense of deep, hard knowledge—ironically making graduates less competitive in complex fields like finance, medicine, law, and advanced research where judgment, expertise, and real-time decision-making are irreplaceable.

Real Jobs Still Require Real Competence

Despite fears, the AI revolution has not eliminated the need for doctors, engineers, quant traders, or researchers. Rather, it has shifted their role: professionals now use AI to augment decisions—but they must still know how to validate, correct, and intervene. In most high-stakes fields, only a small percentage of trained professionals have the competence to make that distinction. The rest risk being outpaced or replaced.

Ironically, many who are losing their jobs today weren’t delivering sufficient value even before automation. The AI wave has merely accelerated the inevitable. Those who bring value, especially those with deep domain expertise and the ability to work well with others, continue to be in demand.

The Widening Gap Among Young Professionals

While social media often highlights exceptional young talents, this creates a cognitive bias. In truth, the gap between top-tier young professionals and the average has widened dramatically. The myth that “everything is online” ignores the reality: online knowledge includes a massive amount of misinformation. Without the skill to discern credible information, “learning from the internet” becomes counterproductive.

The problem isn't just knowledge acquisition—it’s about application. Real-world value is demonstrated when a young analyst can stand before a room of 30-year veterans, present a 15-minute case, and respond to scrutiny without using AI tools. That ability, rare as it is, is what organizations are willing to pay a premium for.

The Macroeconomic Backdrop: Tariff Truce and U.S. Debt Tensions

The broader economic context of this talent discourse is equally telling. The U.S.–China “tariff truce” saw both nations unexpectedly reduce tariffs, with the U.S. cutting rates on Chinese goods from 145% to 30% and China reciprocating from 125% to 10%. This surprise move calmed financial markets, lifting equities and creating a temporary risk-on rally. Tesla and Nvidia were notable winners, reflecting renewed investor confidence.

But this truce is temporary. Manufacturing isn't returning to the U.S.—companies are simply relocating to cheaper markets like India or Vietnam. The root structural issues remain unresolved.

Meanwhile, Trump’s “One Big Beautiful Bill” is a $5 trillion tax cut plan aiming to fuel domestic investment and consumer spending. However, it also risks widening the federal deficit. The U.S. credit rating was downgraded by Moody’s in response, with concerns that unchecked spending and high interest rates could undermine debt sustainability. This has sparked new fears of inflation and a devaluation of the U.S. dollar, boosting interest in inflation-hedged assets like gold, real estate, and Bitcoin.

Final Thoughts: Learn What Can’t Be Replaced

So, what should you learn or do in an age where AI and robots are redefining labor? The answer is surprisingly old-fashioned: learn what AI can’t replace. This includes deep domain knowledge, the ability to formulate questions and strategies, and strong interpersonal skills.

Yes, automation is real. But so is the demand for people who can guide, critique, and control that automation. Those who combine technical fluency with human nuance will thrive. Those who ignore one or both will be left behind.

And don’t forget: much of professional success isn’t just your solo performance—it’s the backstage work of mentors, managers, and even luck. Your shot might only come once. Be ready when it does.

Disclaimer

This article is for informational purposes only and does not constitute financial or career advice. Always evaluate your personal circumstances and consult professionals before making major decisions.

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