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Gen AI will upgrade you not replace you: KPMG

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As the AI revolution continues apace, data has confirmed that generative AI is making some workers more productive and some companies more profitable, though this does not mean it’s a good idea to start cutting staff. 

During a virtual roundtable hosted by KPMG last week, Pär Edin, the US AI go-to-market leader for the Big Four firm, said that there is hard data showing that, for at least some workers, generative AI has been paying dividends in terms of productivity, referencing research from last year finding that, on average, the technology has introduced productivity gains of about 14%. He noted this is based on not some ideal future state but what can be done with the technology today, with solutions that are already out in the market. He added that, in conversations with AI researchers, there is confidence this figure will hold as a realistic expectation. 

He referenced KPMG’s own research on top of this, which found that—after analyzing 10,000 companies—generative AI has a EBITA impact ranging from 3 to 17%, which is calculated as time freed up multiplied by the labor cost of that time, which he felt was a highly significant impact. Effectively, he said, generative AI has created an entirely new driver for productivity. 

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“It varies by sector and company, but those are really, really huge numbers. This is an additional lever that didn’t exist 18 months ago. Now any company can pursue single-digit or low double-digit percentage points of improvement. Not overnight, but within a 12-36 month period using existing tools,” he said. 

While all this does mean companies can do more with less, Edin warned that this does not mean companies should start reducing headcount. In fact, he said, generative AI is pretty terrible at fully replacing people, at least right now. While AI is often touted for its automation capabilities, he said over the past few years companies have found this was a flawed conception. The promise of generative AI, he said, isn’t so much in replacing people but augmenting them. 

“It’s not a headcount-reduction tool in the sense some may have thought about. [Instead, it’s] really a task augmentation tool. We talked about how to get those numbers–you need to break down the entire workforce. I don’t mean headcount but tasks and activities. For every one of those, there are some pretty interesting benchmarks on how much time could be freed up by using better tools. Think of it more as a power tool for the mind than an automation factory,” he said. 

He understands that this might not be what certain business leaders want to hear. Edin noted that he has had many conversations with finance and accounting leaders that basically come down to ROI. This isn’t always the easiest to measure, especially when it comes to AI tools, and so sometimes it can be difficult to communicate the benefits. If it’s not reducing the cost of labor, some wonder, what’s the point? Edin, though, felt that focusing on the cost of labor was missing the point entirely. 

“The most likely case we discussed was not labor cost or headcount reduction but gradual market expansion. So, think of it as companies continuing to grow at the same or greater pace on the top line while not growing labor costs and headcount at the same rate—or even keeping them steady,” he said. 

Given that, by definition, this is more about supporting future growth than directly creating it, he conceded it can be difficult to quickly make back the investment. This has led to a push and pull for accounting and finance leaders between wanting to implement AI for its productivity benefits while, at the same time, wanting to spend only on that which has a direct business case. 

“There is a tug-of-war between wanting to fund this as much as possible, because it does drive productivity, but at the same time not being too overblown about what it will do when explaining this to the board or an investor. This is a balancing act between wanting to do it and being fiscally responsible,” he said. 

It may be easier to directly communicate the need to adopt AI in the future. Edin broke AI development down into three phases: retooling, reengineering and reimagining. The first phase, retooling, is about doing the same job with the same person and role but just more efficiently than before. He noted most companies are in this phase, rolling out pilots and training their staff. The second phase, reengineering, is where workflows themselves are changed to include AI, which he said serves to free up time and enhance efficiency by not just doing the same job but faster but doing a better job overall. Some companies, he said, are just entering this phase. Finally, reimagining is something few to no companies are doing now: thinking about AI as it applies to the entire business model.

“This is when you think about disruption. Will your entire business model be wiped out? Or will you disrupt others? You might go lower in the value stack, or even enter a different market entirely using this technology,” he said. “These phases are somewhat sequential but are happening in parallel depending on the company. Most companies sit somewhere between the first two phases.” 

Agentic AI—where bots are given limited autonomy and initiative—may place companies between the second and third phase, but even then he said it will not mean the end of human involvement. 

“There will be many types of tools. Even in an automated factory, you still have wrenches and screwdrivers. It will be an ecosystem. We’ll continue to use many different tools. The AIs are great because they’re flexible—they can do things they weren’t originally designed to do, and they can get better,” he said. 

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Accounting

Continuous Auditing Transforms Corporate ERPs

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continuous auditing transforms corporate erps

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.

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Accounting

U.S. Imposes New 50% Tariffs on Canadian Imports Under Rare Legal Provision

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U.S. Imposes New 50% Tariffs on Canadian Imports Under Rare Legal Provision

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.

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Accounting

Automated Continuous Auditing: Transforming Compliance and Real-Time Financial Oversight

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Transforming Compliance and Real-Time Financial Oversight

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.

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