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Can AI pass a course in accounting ethics?

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Recently I gave my Accounting Ethics class this assignment: Part 1: Choose a topic for an accounting ethics paper and have an AI program write it; Part 2: Critique the AI paper. What did it do well? What did it do poorly? The results were interesting.

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If I were grading the AI papers, there was not a single paper that would have earned an A. Some would receive a B, but most deserved a C. About half-dozen would receive a D or F. They were that bad.

The major shortcoming of the papers is that the analysis was shallow. It would mention a point without discussion or argument, much less evidence. The papers made many unsubstantiated assertions. Another shortcoming was the papers were often incoherent. A paragraph made sense, and it was followed by another paragraph that made sense, but the second may have had little to do with the first. There was no logical flow. A majority of the papers took a shotgun approach in which they wrote as many points as possible to address the topic. Such an approach lacked focus, treating the trivial the same as the principal issues. 

Most papers had incorrect and incomplete citations. Worse, they often omitted the best articles and books on a topic. Some citations were erroneous. Some were irrelevant, such as directions to fill out a tax form. And some were fake. One involved a faculty member I know purportedly authoring a paper in 2024. The problem is he died in 2017.

I was amazed how many references were used across papers, whether or not they were relevant. For example, Healy and Palepu popped up a lot, and so did Bazerman and Tenbrunsel. The AI program clearly was limited in what references it was utilizing.

Let me supply some examples that illustrate these AI-papers. The first example concerned whether an accountant who follows GAAP is necessarily ethical. The AI program drafted a paper that discussed whether the management of earnings is ethical. That’s OK, but it limits the paper to a small segment, probably because the data files of the program had management of earnings papers but not the topic the student chose. AI ignored the issue of special purpose entities, such as the case of Meta, which omits billions of dollars of debts from its balance sheet, a practice that is quite unethical, GAAP be damned. The program used Enron, WorldCom, and Lehman Brothers as examples. The problem is that these firms did not follow GAAP, so they do not fit the topic.

Another paper tackled the ethical implications of decision usefulness. Strangely, it mentions the Financial Accounting Standards Board conceptual framework but never cites any of its documents. It also ignores the vast literature on decision usefulness. The AI-paper does state that there is a tension between decision usefulness and truth but never teases out what that means. It also mentions that FASB replaced the quality of reliability with representational faithfulness without explaining that representational faithfulness was part of the original conceptual framework as a component of relevance. Besides, anybody paying attention realized that FASB deep-sixed reliability because it was tired of critics pointing out the unreliability of so many fair value measurements.

If the student has little or no knowledge of a topic, perhaps AI could fill in some knowledge gaps; however, its analysis proves shallow, with a tendency to assert rather than demonstrate, and its propensity to create false data and false citations is unnerving at a minimum. I was much happier with the students’ critiques, as most them nailed these shortcomings. 

Perhaps I should mention that most students employed ChatGPT, and it performed the worst. A few students used Gemini or Claude, and they produced better papers.

While AI is here for the long run, it has yet to become the master of writing accounting reports. We are in a transition period. Until AI reaches maturation — and who knows how long that will take? — we need to take a jaundiced view of things.

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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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