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Orgs going full steam ahead on AI, regardless of economy

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Companies seem to be going all in on AI, not only planning huge investments in it this year but making these investments central to their growth strategy, even amid other economic headwinds. 

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A number of studies and surveys has found that businesses are planning major spending on AI technology this year. For instance, a recent survey from Big Four firm KPMG found that the average projected investment over the next 12 months has nearly doubled since last year, going from $124 million at the end of 2025 to $207 million now. Similarly, another survey conducted by Top 10 Firm Grant Thornton said that 68% of CFOs expect IT and digital transformation spending to increase over the next year, marking the highest level recorded in the 21 quarters the survey has been conducted.

Meanwhile, finance and procurement solutions platform Coupa found in its own survey that finance leaders were heavily prioritizing AI spending in the coming year: 49% cited increasing their AI investments as a top strategic priority and 42% cited training and upskilling staff to use AI. 

And while economic headwinds are a reality throughout the business world, organizations do not appear to be letting that stop them. The KPMG survey said that 79% said AI will continue to be a top investment priority even if a recession occurs in the next 12 months. This is despite mixed feelings about the future of the economy, as cited by the GT survey: Optimism dropped from 52% to 46%, but pessimism also fell from 31% to 25%; overall, more have a neutral view of the economy, going from 17% to 29%. 

This planned spending, however, might be because of, not despite, these perceived headwinds, as businesses seem to be placing a lot of hope in AI to carry them through these troubling economic times. The Coupa survey, for instance, asked leaders about their top profitability strategies going forward, and a clear majority, 60%, cited increasing their investment in AI. Meanwhile, asking about their top growth strategies, the most common answer, at 58%, was once again to increase AI technology investments. And finally, 85% said AI was central to their financial strategy this year, and a whopping 100% are planning AI investments over the next six to 12 months. 

Other surveys also show confidence that organizations’ AI bets will pay off. The Coupa survey said 19% expect return on investment within six to 12 months, 52% expect it within 13-24 months, and 26% think it will take two to three years. Only 3% thought it would take longer than that. They might be getting these expectations from their peers: The KPMG survey found 62% of finance leaders saying they have either achieved measurable ROI or expect to sometime in the next year, up from 59% the last time they asked this question. 

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In general, leaders appear to be counting on gains from AI, according to the GT survey. It noted that while CFOs are investing in technology at record levels, they’re not cutting elsewhere to fund it. The survey revealed that 72% expect their net profit to grow over this year, up from 68% last quarter, which the report said could indicate faith that AI will expand revenue and increase productivity. 

Organizations also might be planning spending increases because their technology costs have gone up. A report from Big Four firm Deloitte found that AI consumption and spending have exploded to the point where usage has dramatically outpaced cost reductions, which has led some to look for more economical options like on-premise hosting for the high-volume workloads that AI requires. The report noted that large language model tools can become cost-prohibitive when deployed across an enterprise, and some organizations are starting to see monthly bills for AI use in the tens of millions of dollars. In particular, agentic AI can spike token costs. 

Regardless of motivation, though, companies also seem well aware of the challenges of AI implementation. The KPMG survey showed that leaders did a lot of learning over last year about them: those citing difficulty scaling use cases as an ROI barrier went from 33% in Q1 last year to 65% now; similarly, those citing skills gaps went from 25% to 62%, those naming difficulty quantifying indirect or long-term benefits went from 34% to 59%. The only thing that went down were those talking about risk considerations like data privacy and cybersecurity, going from 74% to 58%. Yet, at the same time the KPMG survey found they’re eager to address these issues, as 91% of leaders named data security, privacy and risk concerns as the top factor influencing AI strategy for the next six months. 

Similarly, the Deloitte report noted that, over and over, people have named three fundamental infrastructure obstacles that prevent organizations from fully realizing the potential of agentic AI: legacy system integration, data architecture constraints and governance/control frameworks. Deloitte said that, right now, most enterprises are not set up to take advantage of the opportunities agents represent. 

This is quite similar to what leaders cited in the Coupa survey. When asked about the largest constraints to integrating AI into daily workflows, 72% said data quality and readiness, 65% cited integration complexity, and 70% said data security and compliance. However, Coupa also noted another issue is that organizations may have trouble actually determining whether their AI investments were worth it in the first place, as 76% said that difficulty actually quantifying ROI was hindering further implementation. 

However, Twisha Sharma, senior research principal for Gartner Finance practice, said companies may not be realizing their goals because of the way they’re viewing AI. Many talk about AI investments as a big broad category, but Sharma, in a recent talk, noted that the economics of AI differ sharply from one use case to another, which makes developing a standard approach difficult, as it likely won’t be able to capture the full picture. Each use case, she said, has different timelines, different ambitions, different risk profiles and different ongoing costs. Finance teams need to dissect cost models more precisely if they want to benefit from AI. 

“AI does not follow one cost curve, and it does not produce one uniform type of value,” said Sharma. “CFOs need to stop looking for a single ROI formula and instead build a balanced portfolio that includes productivity use cases, targeted process improvements, and selective transformational bets.”

Sharma warned that CFOs risk undervaluing AI if they focus too narrowly on immediate financial returns, such as revenue growth, cost reduction or cash flow improvement alone. She said many AI initiatives create important nonfinancial value first — including better decision support, stronger business agility, wider organizational reach, innovation capacity and even a shift in finance’s role within the enterprise — long before those benefits are fully visible in the P&L.

“The value of AI is not always captured first in traditional financial metrics. In many cases, it appears earlier in better decisions, faster adaptation and stronger organizational capability. CFOs need to account for that if they want a complete picture of what AI is really delivering,” said Sharma.

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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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