The rising adoption of AI solutions at accounting firms has come with a growing need for open and transparent conversations with clients about how the technology is used, and what measures are taken to address their concerns about it.
AI has already been a core part of not just accounting software but technology in general for years, to the point where it may be more difficult to find where it’s not used than where it is. While the general public may be vaguely aware of this, they may be surprised to learn the true extent of it in today’s world. Jeanne Hardy, founder and CEO of New York-based Creative Business Inc, which specializes in art industry clients, noted that the extreme reach of AI technology today means anyone trying to avoid it entirely will have a very difficult time of it.
“Intuit has been using AI for years now. Google and Microsoft, they’re using AI. They’re using AI in restaurants. All the vertical industry software uses AI. Your banks are using AI, that’s how they know what credit cards to ask you to get, when they should cut you off, what lines of credit you’re eligible for,” said Hardy, who is also the founder and CEO of finops platform Levvy.
Using AI in engagements means having open and transparant talks with clients.
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Starting the conversation
Given this, accountants are taking active efforts to make sure their clients are aware not just that they’re using AI but how and why they’re using it as well, which is usually done through conversation. Richard Jackson, global artificial intelligence assurance leader for Big Four firm EY, noted that often it is clients themselves who initiate these talks.
“We are having this conversation around the use of AI with almost every client—whether it’s senior management or at the board level or the audit committee level, people are asking questions like ‘what are you seeing, what is my organization doing, how do we compare, help us understand what you’re doing,'” he said, though added that if the client doesn’t bring it up first, they usually will. “In instances where it’s not client-initiated, we’re actually raising it ourselves to have some of those very transparent conversations around what we’re seeing with the use of this technology, what risks and challenges it raises whether in the client environment or the audit itself, and then how do we address those?”
Thomas DeMayo, who leads the cybersecurity and privacy advisory group for top 25 firm PKF O’Connor Davies, shared a similar experience, saying that while no one has specifically asked for a formal AI disclosure, the use of the technology tends to come up organically in the course of the client’s due diligence talks.
“We do periodically get due diligence where they’re making sure our systems are safeguarded. They ask questions and those questions have evolved to where they do [talk] about AI components. They ask [if we are] using a public model, do we keep AI private, those types of things,” he said.
Far from a chore, practitioners like Michelle Voyer, who leads the software solutions group for top 25 firm CohnReznick, enjoy having these talks as it allows them to highlight their technological sophistication.
“We’re open with clients about the tools we use, particularly when they contribute to accuracy and efficiency. It’s about reinforcing trust and demonstrating that technology enhances the quality of our work, without replacing professional judgment or accountability.”
While the topic is often brought up conversationally, some firms also put additional language in their engagement letters that addresses how technology, including AI, may be used. Voyer, for instance, noted that this can help provide an additional layer of clarity.
“We structure our engagement letters to reflect how technology may be used in the course of our work. When clients express preferences around the use of automated tools, we document those choices and clarify how that may impact timelines and costs.”
Others, like Hardy’s firm, don’t include such language yet but may do so in the future. Currently they’re planning on an email update on how they use AI and protect client data. From there they might decide to put a paragraph in their engagement letters using that email as a foundation.
Regardless, however, she felt AI use should be an ongoing conversation considering the rapid pace at which the technology advances.
“Because of the way that it’s changing, and new models coming and new applications happening, I feel like it should be a regular conversation to normalize it. Maybe it’s quarterly, or maybe you send a newsletter, ‘we want to update you,’ because people are reading the news [about new developments]” she said.
Similarly, DeMayo’s firm is also considering adding an AI section in their engagement letters and has in fact drafted verbiage himself for this specific purpose.
“It talks about the fact that we don’t use any public models. People within the firm can only use approved products: you cannot just go download an AI tool or go to Gemini, it won’t work. You have to use what we’ve specifically invested in, what we’ve specifically vetted as being secure and being private to us. Anything that goes into [our AI], we have strict assurances that that particular provider is not going to use our data to train their models, so that’s a very big important part we convey to our clients,” he said.
While PKFOD is still deciding whether or not to add this language, overall DeMayo predicted that firms will start taking more initiative to ensure clients are informed on how they use AI, as they will probably be asking anyway.
So, what do you talk about?
Regardless of how the conversation starts, Jackson from EY said it tends to center around the particular use case of the technology and what the firm is doing to make sure they’re doing so safely. On this, he said they make sure to emphasize the role of the human in the loop, ensuring no one comes away with the impression they’re letting an AI do all the work.
“We talk a little bit about the testing procedures that every one of our tools has to go through before we put it into production. But what it also then drives is the conversation around the importance that the human who reviews the output is able to adequately understand [it]. But everything I described there is with the net benefit of an improved quality output, because now you’re no longer just solely relying upon the human’s ability to understand it. You’re actually supplementing with capabilities from technology,” he said.
They also spend time going over specific client concerns about AI. Every single practitioner, when asked what clients’ chief concerns about AI use were, all said data privacy and confidentiality was first and foremost in their mind above all else. Practitioners take pains to set their clients’ minds at ease, as they would with any other concern about the engagement, and oftentimes they are successful.
“I wouldn’t want to suggest in any way that every conversation is always rainbows and unicorns. I think that clients have an understandable and a real set of questions that they want to understand. ‘Well, where are you using it? Have you?’ And then you get into the conversations of, ‘well, are you using my data or using technology with a large language model? How do I know that you’re not training back my information and insights to the large language model’ and so you absolutely go into these conversations,” Jackson said, but added that they ultimately “see it as hugely beneficial to what the auditor is trying to achieve.”
But sometimes even that is not enough. Hardy, from Creative Business, likened it to the days when people were still hesitant about online banking. To this day there are still clients who insist on paper checks. When a client truly and genuinely refuses to allow the accountant to use AI, Hardy said it may be time to refer them to another firm that is a better fit for them. Still, this is rare. Usually all that’s needed is some gentle diplomacy.
“I think if you start small, kind of tailor it to them and bring them along with you, then you’ll probably have more success changing their mind than if you send them a six page document outlining all the AI that you’re using everywhere,” she said.
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.