While discourse often centers around the risk of AI eliminating jobs, recent data shows that at least some leaders expect they will actually be growing their headcount as they implement the technology in their organizations.
A recent Deloitte poll of 2,000 director-to-C-suite level professionals found, among other data points, that 39% of respondents predict they will increase headcount to implement their generative AI strategies at least slightly, versus the 22% who say they will expect to reduce headcount.
These figures differ based on respondents’ self-reported expertise with AI, with those who have more expertise generally expecting more headcount changes, either positively or negatively. Of those who say they are very proficient with AI, 45% predict their organization’s headcount will increase and 23% say it will decrease. Over half (57%) of those with the least expertise, meanwhile, generally expected things to remain the same; in contrast, only 28% of those with high reported expertise believe the same.
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These predictions are part of the overall anticipation that generative AI will change talent strategies. The poll found that three-quarters (75%) of the respondents expect this shift to happen within two years. Only 16% thought it would take longer than that, and 18% say they are making such changes now. As for what changes are expected, the most commonly cited at 48% was “redesigning work processes to take advantage of generative AI,” followed by “designing and implementing upskilling and reskilling strategies” at 47%.
“These survey results suggest a strong need for more attention paid to generative AI’s talent impacts,” said the Deloitte report. “In the near term, AI education and fluency will be especially important to fostering adoption and overcoming initial resistance to change. In the longer term, upskilling or reskilling and redesigning work processes and career paths will likely be essential for capturing generative AI’s full value and positioning workers for future success.”
This data is similar to that found in another recent survey from EY, which polled more than 250 leaders in the technology industry. It found that half of technology business leaders (50%) say they anticipate both layoffs and hiring at their company in the next six months as a result of AI adoption. More granularly, the data shows that 20% of the tech leaders surveyed said they anticipate layoffs and 27% said they anticipate hiring over the next six months. However, three out of five technology leaders (61%) say emerging technology has made it more challenging for their company to source top technology talent.
They are also working hard on upskilling talent. Over three in four technology business leaders (76%) say they have implemented internal technical certification to help employees keep pace with rapidly changing GenAI. Further, more than half (51%) say they have put external technical certification in place at their company to help keep pace with rapidly changing GenAI. Finally, nearly two-thirds of technology business leaders (64%) say their company has put internal development programs in place to help employees keep pace with rapidly changing GenAI.
“One thing is certain: Companies are reshaping their workforce to be more AI savvy,” said EY technology, media and telecom AI leader Vamsi Duvvuri. “With this transition, we can anticipate a continuous cycle of strategic workforce realignment, characterized by simultaneous layoffs and hiring, and not necessarily in equal volumes. But it’s not all doom and gloom. Employees and companies alike continue to show enthusiasm around AI, specifically when it comes to opportunities to scale and compete more effectively in the marketplace.”
This upskilling, reskilling and shifts to talent strategy are due at least in part to the technical skills and knowledge needed to successfully implement generative AI solutions in an organization. Getting value from generative AI is not always easy. Indeed, another poll from RSM found that while many are using AI in their workplace, a majority say implementing the technology has been harder than expected.
The poll, which included 510 middle-market decision makers in the U.S. and Canada, indicated a great deal of enthusiasm for AI. It found 78% of middle-market organizations are adopting AI, with 77% adopting generative AI in particular. With this enthusiasm has come investment: 89% of executive respondents reported their organizations plan to boost their budgets around AI technologies and 74% are focusing their dollars specifically on generative AI.
Yet, 54% of respondents report that generative AI has been harder to implement than they expected. Further, 67% say they need outside help to get the most out of their generative AI solutions.
“AI and generative AI are making significant impacts to our industry — perhaps more than any previous technology,” said Sergio de la Fe, enterprise digital leader and partner with RSM. “Our survey underscores the necessity for middle-market organizations to develop a comprehensive AI strategy that encompasses the entire value chain. Considering the complexity of AI technologies, it’s no surprise that roughly two-thirds (67%) of middle-market leaders surveyed recognize the need for external assistance to fully capitalize on the advantages of their selected AI solutions.”
Concerns
All three surveys named largely similar concerns regarding AI that give pause to even enthusiastic adopters. The concerns include opacity of the models and their decision-making process, outputs that may not be entirely trustworthy, potential data leaks and cybersecurity attacks, as well as ethical and legal considerations.
Another recent report from CPA.com, though, found accounting leaders are largely unperturbed. It found that 68% of accounting leaders have confidence in their organization’s responsible use of AI. This is in contrast to their subordinates, who aren’t as confident in their leaders: Only 29% of front-line employees believe their employers have sufficient measures to ensure that AI is used responsibly.
“Organizations will not be able to enjoy the full benefits of AI if it is not considered a safe and trustworthy tool,” said the CPA.com report. “… Failure to use AI responsibly could result in financial penalties under new regulations as well as reputational damage.”
As corporate accounting departments cross the threshold into late July 2026, the adoption of continuous, automated auditing systems has reached a definitive turning point. Driven by advances in artificial intelligence and deep integration with modern Enterprise Resource Planning (ERP) platforms, leading finance organizations are moving away from traditional, periodic post-hoc audits in favor of real-time, 100% transactional verification. This technological transition is redefining internal control environments, reducing compliance costs, and eliminating the structural delays inherent in legacy quarterly closing processes.
Unlike traditional auditing frameworks that rely on statistical sampling—a process that inevitably leaves operational blind spots—continuous auditing software monitors operational data feeds continuously. Every purchase order, electronic invoice, payroll disbursement, and cross-border wire transfer is automatically cross-referenced against established corporate governance parameters, regulatory tax schedules, and anti-fraud algorithms in real time. Anomalies or unauthorized ledger entries are flagged instantly, allowing internal audit teams to investigate and remediate compliance gaps immediately rather than months after the close of a financial period.
The implications for executive financial management are far-reaching. By embedding continuous verification directly into daily transaction workflows, chief financial officers gain uninterrupted visibility into the organization’s true financial standing. Real-time balance sheet auditing eliminates the severe operational bottlenecks associated with month-end and quarter-end financial reconciliations, freeing accounting professionals to focus on strategic financial modeling, tax planning, and capital allocation rather than manual data entry and spreadsheet consolidation.
However, implementing continuous auditing requires accounting leadership to invest heavily in data governance and technical upskilling. Internal audit teams must evolve from manual ledger reviewers into system architects capable of auditing complex algorithms and validating automated data pipelines. Accounting firms and corporate controllers that master continuous auditing will establish a resilient compliance framework capable of meeting stringent international regulatory standards with total transparency.
WASHINGTON — In a major escalation of cross-border trade friction, U.S. President Donald Trump has signed executive orders imposing new 50% tariffs on a wide selection of Canadian exports, citing discriminatory practices by Ottawa targeting American auto, dairy, and beverage industries.
The new duties, announced Monday, will take effect in 30 days. They target a broad spectrum of consumer and industrial goods—ranging from wine, liquor, and milk products to commercial cement, furniture, clothing, and hockey equipment.
Untested Legal Mechanism
To enact the sweeping measures, the administration invoked Section 338 of the Tariff Act of 1930—a rarely used legal provision allowing the executive branch to levy additional tariffs of up to 50% on foreign nations deemed to discriminate against U.S. commerce.
White House officials noted that Section 338 addresses trade discrimination rather than national security or economic emergencies. The move comes months after prior global emergency tariffs faced legal challenges in domestic courts, signaling Washington’s pivot toward alternate statutory authorities to maintain import duties.
Senior administration officials briefed reporters that the measure directly responds to Canadian provincial bans on U.S. alcohol, restrictions on American vehicle exports, and import quota disparities affecting U.S. dairy and cheese producers relative to third-party trading partners.
“While the administration continues to secure reciprocal trade agreements globally, Canada retaliated against efforts to protect domestic industry,” U.S. Trade Representative Jamieson Greer stated.
USMCA Impact and Carve-Outs
Significantly, the newly ordered 50% duties will apply to designated items even if they otherwise comply with the United States-Mexico-Canada Agreement (USMCA).
However, the administration confirmed key targeted exemptions:
Energy products (including oil and natural gas)
Potash and critical minerals
Fish and seafood
Goods already governed by sector-specific duties (such as existing steel and aluminum tariffs)
Administration representatives emphasized that the tariffs do not stem from recent disputes concerning drifting Canadian wildfire smoke, noting that policy options regarding environmental spillover remain under separate review.
Canadian Response and Market Reaction
Following the White House announcement, the Canadian dollar experienced a sharp decline against the U.S. dollar, falling approximately 0.4% during evening trading.
Canadian Prime Minister Mark Carney issued a statement emphasizing that Canada’s earlier counter-duties had merely matched previous U.S. trade actions. “Canada stands ready to engage intensively to address outstanding issues with the U.S. to the mutual benefit of our citizens,” Carney stated, pointing to detailed proposals Ottawa submitted to modernize the USMCA framework.
Ontario Premier Doug Ford took a firmer stance, urging a “dollar-for-dollar” reciprocal response if the measures go into effect on August 19.
With a 30-day implementation window before the duties officially lock in, industry associations and trade groups on both sides of the border are calling for urgent bilateral negotiations to avert further supply chain disruption across North America.
The traditional accounting paradigm—defined by periodic monthly closures and post-hoc annual audits—is rapidly giving way to continuous, automated financial oversight. As of July 2026, forward-thinking accounting practices and multinational corporate finance departments are leveraging continuous auditing systems powered by advanced machine learning models. These systems monitor operational transactions in real time, shifting audit methodologies from sample-based post-analysis to absolute, 100% transaction-level verification.
The operational advantages of continuous auditing are transformative. Standard auditing procedures historically relied on statistical sampling, which, despite rigorous methodology, inherently left gaps where anomalies or fraudulent transactions could go undetected for months. Modern continuous auditing platforms integrate directly with enterprise resource planning (ERP) databases, instantly cross-referencing purchase orders, invoices, bank feeds, and tax records. Any deviation from established control parameters or unusual transaction behavior triggers immediate flags for internal audit teams, dramatically reducing detection lag from quarters to seconds.
Beyond fraud prevention, continuous auditing fundamentally alters internal reporting and decision-making. Executive leadership no longer has to wait weeks after the close of a quarter to evaluate precise financial standing; real-time verified ledger data provides an uninterrupted view of operating margins, tax liabilities, and cash flow dynamics. This real-time visibility enables corporate controllers to adjust capital allocation strategies dynamically, mitigating liquidity constraints and capitalizing on emerging commercial opportunities far more efficiently than competitors bound to legacy reporting cycles.
However, implementing continuous auditing requires accounting professionals to acquire new analytical capabilities. The role of the auditor is evolving from manual data reconciliation toward system validation, algorithmic model governance, and strategic risk interpretation. Accounting firms and corporate finance departments must invest in continuous technical education, ensuring that audit staff possess the data engineering skills necessary to design, maintain, and evaluate complex automated compliance systems.