Connect with us

Accounting

Small firm AI plans must balance budget with ambition

Published

on

Some firms, the ones that constantly grab headlines, are spending billions of dollars to create bespoke artificial intelligence systems to service their Fortune 500 clients who need complex compliance and advisory services to support their global footprint. 

In contrast, the vast majority of firms are spending maybe a few thousand dollars to license commercially available models, and perhaps a few thousand more to train staff and integrate systems. Overall, if someone is not building billion-vector custom models housed on a massive server farm, AI is actually quite cheap, especially considering the capacity upgrades it can present. 

Firms with about one to 200 people are mostly engaging with the subscription model products right now, according to TJ Lewis, innovation strategist with Rightworks, an accounting-specialized cloud provider. “They’re not building out their own models,” he added. “They’re not securing a bunch of server time or things like that to spin up their own things by and large.”

AI money balance budget

Andrey Popov/stock.adobe.com

Part of this is because smaller firms don’t have the resources to construct their own custom AI models, especially the oceans of data to feed them, as well as the technical experts to bring it all together, according to Donny Shimamoto, head of IntrapriseTechKnowlogies, a tech advisory practice specializing in CPA firms. 

“It kind of makes sense,” he added. “In order for AI to work to a good extent, you need a high volume of data, and smaller firms just don’t have that volume. They need to teach the AI. And they also don’t have simply the teams to be able to build that out cost effectively.”  

Another reason is they really don’t need to, he added. Huge sophisticated AI models are generally used for highly complex tasks for highly complex companies, which is why the international-scale firms tend to invest in them. Conversely, the tasks most local accountants are handling for their clients are simpler by many orders of magnitude. In the majority of cases, said Shimamoto, a commercially available model will work fine for their purposes. 

“There’s personal AI or personal LLMs that, if a practitioner had a decent amount of content that they wanted to have readily searchable, they could use those LLMs like [Google’s] Notebook [LLM] or something. Those personal LLMs are designed to run off of a laptop, so you won’t see these huge incremental costs coming along,” he said. The cost of commercial AI solutions has also been going down over the years, he added, and many of the ongoing costs of these products are now at the vendor level. 

Furey Financial Services, a 38-employee firm in Hoboken, New Jersey, that was also named one of this year’s Best Firms for Technology, can relate. A highly tech-focused firm, with IT taking up 29.5% of its total operating budget, Furey has been an enthusiastic adopter of AI, making sure to equip all its staff with the latest available tools. It invests in both its own proprietary AI solutions as well as AI-enabled commercial products. However Chip Waller, the firm’s chief operating officer, said Furey aims to be judicious in its AI spending. While Furey’s tech ops team is “focused on building for the future,” he conceded it’s “a balancing act of investment versus being too reactionary.” 

“From our perspective we’re not trying to build our own LLMs or infrastructure,” he said. “It was really about how do we from a low-cost perspective leverage some of these models out there and plug them into our workflow, so you can differentiate AI into that platform component. … We’re going to really focus on the application layer and see where we can put these things to use while not trying to build the new AI model ourselves.”

This falls in line with the general advice Shimamoto had for smaller firms looking to invest in AI. It is the same as it is for any other major tech purchase: Firms must start with the use case, then find technology to fill it. Too many firms, he believes, do it the other way around, much to their detriment. 

“It’s the same way we’ve prioritized IT spend for the last two decades at least,” he added. “It comes down to where is the business value? What is the business strategy? And how will AI contribute to that? We do have to be careful of AI being a solution looking for a problem, but I have been seeing that a bunch.”

Waller said that when Furey was first thinking through its approach to AI, it considered building its own proprietary model, or to train one using an open source model like Llama as a base. However the firm calculated that this would carry not just a significant one-time cost for development but ongoing expenses such as server space. “We decided not to go that route and really just say ‘Hey, let’s get it plugged into our workflow but let’s hold off on running our own model,'” said Waller. This has helped the firm gain efficiency and productivity bonuses from AI while keeping IT costs low. 

However, Furey is more than just a consumer of AI products. While it’s not prepared to drop millions of dollars on custom systems, it has found great cost savings in the form of creating its own API access point for OpenAI’s models. During the development process, Furey estimated its expenses would be hundreds of dollars per month, but as time went on and OpenAI introduced new capacities, the cost began to drop. While the cost savings are nice, Waller said the real benefit is in better quality client services. 

“That cost has gone to near zero,” he added. “Once we got our whole team up and running on it, all the clients, we’ve got thousands of [API] calls, [but] we’re in no more than 10 bucks a month. But the investment really is on our team knowing which way to go and connecting the API client to the API gateway in a secure way, doing all that dev work to plug that into our templates on a daily basis and go through that.”  

Doug Schrock, managing AI principal for Top 25 Firm Crowe, said small firms should be actively experimenting with AI beyond just buying or licensing a commercial solution, which he called “the homeowner level of AI.” While the investment is much less, there is an upper limit on the value it can create because it does not enable more significant redesigns to processes and tasks that are offered by more complex solutions. Overall, he said, firms should be seeking to innovate and make strategic relationships with some of the larger AI players out there. 

While it’s fine for now to stick mostly with what’s on the market, he warned that smaller firms will need to increase their AI capacities soon, or else be outcompeted by other firms. Smaller players who can’t or won’t make these investments, Schrock predicted, will start falling behind. They might need to do things like hire consultants to help get them to that next stage of AI development. “The market is moving and folks like us get a higher level of value allowing us to get more cost competitive and deliver value and speed they maybe can’t,” he added.

“In the next six to 12 months, get your people using the tools tied to your existing system,” Schrock said. “If everyone is running MS Suite, turn on Copilot. It’s $30 bucks a month per user. Have your people start using the AI features built into your core system, then maybe get some spot LLM tools like ChatGPT or some AI-based research tool. They need to get in the game now if they haven’t already.”

Continue Reading

Accounting

Continuous Auditing Transforms Corporate ERPs

Published

on

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.

Continue Reading

Accounting

U.S. Imposes New 50% Tariffs on Canadian Imports Under Rare Legal Provision

Published

on

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.

Continue Reading

Accounting

Automated Continuous Auditing: Transforming Compliance and Real-Time Financial Oversight

Published

on

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.

Continue Reading

Trending