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Managing expectations key to AI implementation for CAS

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AI implementation at a CAS practice is hard enough, but it becomes even more so when people don’t fully understand what AI can and cannot do. 

Speaking during the Information Technology Alliance’s spring collaborative in Memphis, Tennessee, Jessica Barnas, the partner leading the finance and accounting solutions advisory group for top 25 firm Wipfli, lamented that public discourse around AI has given people the impression it’s some sort of magic wand that can fix anything, which then leads to unrealistic expectations around its capabilities. 

“I talked to a lot of clients, I think they think that AI is like an elf that jumps out of the box and does things magically. They just say, ‘Can’t AI do that?’ I even had one of our partners [tell me this recently], we’re working on a five year revenue prediction—he said, ‘Well, can’t you just upload that to Copilot and have it spin up the business plan and everything?’ and I’m like, ‘Do you have any idea how generative AI works? It doesn’t do that.’ But I think that there’s just this misconception [that], oh, technology it is just this magic wand that’s going to make all of my accounting problems disappear,” Barnas said. 

Chris Gallo, director of outsourced business accounting services with Kansas-based firm Creative Planning and another one of the panelists, made a similar point, saying that it’s important to be realistic about what technology can do. While it can do a lot, he echoed Barnas in saying that some people seem to think it is magic. 

“If we believed everything that everybody told us you would be flying around in flying cars right now. I think we need to kind of take it with a grain of salt at some point. Because why wouldn’t we just say ‘ChatGPT build me a flying car,’ and then the bot people that you know Tesla’s building will just go do that. Right? It becomes a little bit ridiculous at some point too… There’s a lot of expectation, or unaligned expectations,” said Gallo. 

Misconceptions about AI capabilities also serve to drive fear on the part of accountants. Barnas said that a big part of the change management process when it comes to implementing AI is allaying fears from staff that they’re not going to fire everyone and replace them with bots. While there have been major improvements in AI over the years, she does not believe it is in the position to wholesale replace human accountants just yet. Instead, it has become a great way to augment those humans and make them more competitive against the humans who are not using AI. 

“They think ‘AI will eliminate my job!’ So we talk about our philosophy. We’re looking to adopt these tools to help you get bigger and better and embrace the advisory role, but the only way AI will replace you is if a person using AI will replace you. You need to give that level of comfort to your teams so that everyone knows we’re just trying to get better, we’re just picking up new tools, this is not a replacement for you,” Barnas said. 

There is a similar fear when it comes to billable hours, also explored in another panel (see other story), of what happens when a process that normally takes 8 hours now only takes 1. Barnas first described the billable hour as “the enemy of all of us here in the room” but also conceded it is a real anxiety for practices that have built their foundation on it. She suggested, in response to this concern, to take a page from Google and encourage people to develop pet projects using AI and rewarding them if it turns into something useful for the entire team; and if it really does lead to a reduction in billable hours, don’t punish people with less money when they’ve done what you wanted them do in the first place. Overall, a firm’s business model should not be one that punishes efficiency: a practice should value results, not burning hours. She conceded that, for certain firms set in their ways, this might need retraining. 

“Okay, I took this process down from seven hours to half hour every week. Now what? Teach me how to do advisory. Because being a CFO, doing modeling and projections, it is not something [you learn] from reading a book or sitting in on one webinar. We would all be doing that if that were the case. So how can we train our teams on what to do next? All of that is involved in change management: being a guide and providing the safety for each step,” she said. 

Gregg Landers, the last panelist and managing director of client accounting and advisory services and internal control services with Top 10 firm CBIZ, talked about how a lot of the misunderstandings and misconceptions regarding AI can be allayed from people just experimenting with it themselves, which not only lets them get a better impression of its current capabilities but will train them in using those capabilities to their fullest potential. 

“I’ve been encouraging some of my teams to use their personal generative AI a little Black Mirror-like, [where you] keep talking to it, and it talks back. You get accustomed to how to give a context, how to get better answers. Sometimes, if you’re nice to it, [you get] a tighter answer than if you’re not. So experiment around with it. 

He gave an example from his own life, where he needed to learn more about digital services taxes. Through an extended conversation with an LLM  he was able to understand what the DST is and how it works and how accountants manage it. He was able to get good outputs from the model, though, because previous experience taught him that he needs to provide more context and information for a decent answer, because these models can get tripped up by ambiguities. He compared it to a fortune cookie that could be interrupted in many ways, people should be clear and concise when prompting AIs. 

“We’ve become a society of fortune cookies. I may ask ‘how is that project going’ and you tell me ‘it’s going good’ but what I mean is ‘is it on time?’ and what you might mean is ‘I had this hiccup that put me two weeks behind but now it is resolved so it is good.’ We can’t have fortune cookies when interacting with generative AI. You need clear, concise, contextual communication,” 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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