Regardless of how a firm ultimately implements AI, Kim Petro, a practice advancement coach from Woodard, stressed the importance of doing so ethically. While AI has opened up a whole new world of possibilities, not all of them are necessarily positive, and so it is important to be mindful of the consequences of using AI solutions.
She pointed to biased hiring algorithms that disadvantage certain people without the developers even realizing it, “so if someone turns in a resume with the wrong name and the algorithm is scrubbing that for appropriateness to the job, it can completely disregard it when it really should not be, there could be discrimination.”
She said there is also evidence people are using AI to create financial advice without disclosing that it came from AI, which “oh my god is so dangerous, the liability we bring on ourselves by giving bad advice and not disclosing where we got it.”
AI ethics or AI law concept. Businessman with ai ethics icon on virtual screen for compliance, regulation, standard , business policy and responsibility.
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Students, it is well known, are also using AI to cheat on their school work, she said. Meanwhile, she added, there are bots trolling social media for purposes ranging from ridiculous to nefarious.
During her own talk at Scaling New Heights in Orlando, Petro outlined some key considerations to avoid some of the less ethical applications of AI.
For one, people should be transparent about their AI use, making sure to always disclose when they use it; Petro herself disclosed she used AI for research and building course content, so “I need to tell people it’s not my own content, it’s scrubbing the Internet and grabbing bits and pieces from other things. I also need to use my own voice when using this content.”
Ethical users also make sure they verify what their AI tells them, noting the propensity of certain language models to make things up wholesale. They should also be aware that not only can the model can wrong, it can also have bias, such as in the aforementioned case of the hiring algorithm.
She also said users overall should try to respect intellectual property; she pointed to an example where board game designers were using AI to make art instead of hiring artists, but the artists the model drew from did not get proper attribution.
Finally, she said that people need to be aware of the privacy and security risk of using AI, especially public models, especially free accounts on public models. This is because inputs can go right into the company’s servers, including any personal or financial information that generally needs to be kept private.
“We don’t want our confidential or sensitive information in there because if you use a free account it informed the generative model for everyone. Not good. Even if you use it just for financials, we highly recommend using a paid account so it is not informing the model,” she said.
While many use AI to draft reports for clients, she said that if there is a risk the information will wind up with an unauthorized third party they should scrub all the identifying details from the prompt before entering it into the model, and then replace the information in the actual report itself.
Other ethical AI uses she suggested include brainstorming, “not content replacement but to help us do the research,” as well as approved image generation for marketing purposes using appropriately licensed artwork, such as “you have a great logo and want to make a banner for LinkedIn.”
Professionally, there is also internal process generation and automation, basically “we can have ChatGPT write me a process for automating monthly close or bank recs, it doesn’t matter as long as we use it internally and, again, has human review. I cannot stress that enough.”
The specific issues that a firm might face regarding AI ethics can vary greatly, and so she also stressed the importance of creating best practices and acceptable use policies, such as making sure a human reviews everything, only using tools that create audit trails, or assigning permissions with user roles.
Overall, she said users should remember to:
“Ask yourself, am I representing this content as my own? If you are, may God strike you down. Well, just kidding. But maybe think about it and really write that this was not your work, it was someone else’s.”
“Could this harm instead of help? If I’m a board game designer, say I’ll save some money and use AI to create this graphic design. I won’t pay an artist to do that. So I scrub the Internet using AI and pull from different artists and it’s blatantly obvious and… [the artist] has nothing to protect their work.”
“Would I be comfortable explaining how I use this to my client? You may have clients who’re not tech savvy and you tell them you put something in AI and they say ‘you put all my information to all robots everywhere!’ They freak out. Would they be okay with you using AI? Are you telling them upfront you use AI but, hey, we won’t have your personal information out there, are you okay with that?”
“Normalize conversations around ethical technology use. This is a bnig thing, especially with policies and enforcing them. AI is changing every day, evolving fast, so fast that we have to keep up with the conversations and learning and make sure we stay on top of it.”
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.