Whos most at risk? AI shows highest impact on white-collar and sales jobs Technology

It guides decision-making across the business and ensures consistency as AI becomes embedded in everything from agentic use cases to vendor ecosystems. Some interesting pricing models for using AI agents are developing. Box CEO Aaron Levie raises the possibility of pricing agents like traditional labor, based on how long it takes an agent to complete a task. Regardless of which model they buy into, CIOs will need to map out a clear path to how agentic AI investments will create value for the business.

Operationalize oversight before it becomes urgent

Restrictions on sales of advanced chips to China have been central to the AI race between the world’s two largest economic powers, but such controls are also controversial. Proponents argue that these restrictions are necessary to slow China down enough to allow U.S. companies to keep their lead. Meanwhile, opponents say the export controls have loopholes — and could still spur innovation. The emergence of China’s DeepSeek AI chatbot in January particularly renewed concerns over how China might use advanced chips to help develop its own AI capabilities. Mike Vaughan serves as chief data officer for Brown & Brown Insurance.

• Agentic AI raises the intelligence bar even higher, adding new levels of autonomy and reasoning that allow AI agents to work together, make decisions based on context, and trigger actions across different business functions.
• It integrates with Excel and assists in creating step-by-step plans to cleanse, sort, and make sense of data.
• However, the trade rivalry between the U.S. and China has been weighing heavily on the industry.
• As CIOs map out their strategies, it’s becoming clear that agentic AI will change how they manage their organization’s IT environment and how they deliver services to the rest of the business.

China says it’s approving permits for rare earth magnets to be exported to the U.S., while Washington has lifted curbs on chip design software and jet engines. Washington has been tightening controls on exports of advanced technology to China for years, citing concerns that know-how meant for civilian use could be deployed for military purposes. That’s because the H20 chip was developed to specifically comply with U.S. restrictions for exports of AI chips to China. Nvidia’s most advanced chips, which carry more computing power, are off-limits to the Chinese market. Recent surveys show 78% of organizations use AI in at least one business function — up from the 55% reported two years ago. Yet despite AI’s rapid proliferation, effective governance remains elusive.

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Very few firms have implemented internal guidelines and policies to govern their use. That disconnect introduces real risk — not only in data security and compliance, but also to trust, performance and long-term innovation. As CIOs map out their strategies, it’s becoming clear that agentic AI will change how they manage their organization’s IT environment and how they deliver services to the rest of the business.

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• “Every organization has key end-to-end business processes, which are mostly already automated,” says Elliott.
• It has become smarter because of AI tools that do the hard work.
• Routine and well-defined tasks tend to be more automatable, while tasks involving high levels of discretion or emotional intelligence remain largely resistant to AI disruption.
• When policies lag adoption or rely too heavily on restrictions, the result is vulnerability to data breaches, regulatory penalties and reputational damage.
• These tools help with things like making charts, writing formulas, sorting messy data, and even predicting future numbers.

It even explains what the formula does, so it’s easier to learn. Microsoft Copilot works well for people who want to finish tasks quickly without searching for formulas online. “Every organization has key end-to-end business processes, which are mostly already automated,” says Elliott. “AI agents offer a new way of patching problems, either by automating steps or by handling exceptions more flexibly.” In this manner, agents can begin to make or suggest process improvements as they go along. Nvidia has profited enormously from the rapid adoption of AI, becoming the first company to have its market value surpass $4 trillion last week.

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It can provide answers such as “which product returned the most” and display the results in an easy-to-understand manner. This comes in handy while doing school projects or business presentations. Monday’s announcement from Nvidia signals that its lobbying efforts paid off. White House AI and crypto adviser David Sacks told Bloomberg on Tuesday that allowing Nvidia to restart Chinese sales of its H20 chip would help the U.S. better compete abroad — particularly with Chinese chipmaker Huawei Technologies. Type a sentence like “sort products by price” and the tool does it.

Conclusion: Why These Tools Matter

It removes the need to click a bunch of buttons or search menus. If AI is positively reshaping workflows, as intended, then governance is simply the operating system behind it — invisible when working well but essential to everything running smoothly.

This isn’t about building an AI compliance fortress but creating a system that can identify blind spots early, track patterns over time and evolve. This contradicts earlier narratives that predicted AI would primarily threaten blue-collar or low-wage employment. Apart from identifying AI’s applications, the researchers examined how AI applicability correlates with wages, education levels, and employment patterns. They found that occupations with higher education and wage requirements tend to have higher AI applicability scores. This raises important questions about inequality and skill-biased technological change.

Scalability is essential — not just across geographies, but across roles and technologies. The risks introduced by a generative AI content tool differ from those posed by predictive analytics in finance or compliance. Your policy should reflect that nuance, flexing where needed while maintaining core principles. And yet, governance remains one of the most misunderstood aspects of AI use. Too often, governance is viewed as a set of rules intended to minimize risk exposure by hindering AI’s effectiveness. That mindset doesn’t reduce risk, it just shuffles it around.

By linking work activities to more than 900 occupations in the U.S. workforce, the researchers determined which jobs are most exposed to generative AI. Occupations in computer and mathematical fields, office and administrative support, and sales and related professions ranked highest in AI applicability. This is largely due to the fact that these roles rely heavily on tasks involving information processing, document drafting, and customer interaction, areas where AI currently excels. Robotic process automation (RPA) emerged in the early 2000s as a rules-based method for automating simple, repetitive tasks, such as data extraction or order processing. The study also sheds light on how users interact with AI in the real world, including the mismatch between what people expect from AI and what it can actually deliver.