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Digits says its new AI agents can automate 95% of bookkeeping tasks

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Accounting platform Digits announced the launch of Digits Accounting Agents, which CEO Jeff Seibert said can — when running on its Autonomous General Ledger product — automate 95% of the entire bookkeeping workflow in a way that, according to tests the company performed, outperforms even human professionals in terms of accuracy and speed. 

Speaking during the Scaling New Heights conference in Orlando, Seibert heralded this development as true end-to-end automation with little to no need for human intervention or supervision beyond exception management and final approvals. The agents, he said, run 24/7 in the background, even “while you sleep,” to automatically do things like collect and reconcile bank statements; manage work papers; categorize, match and book transactions; book payroll; and clean up financial data, among other things. 

“The problem is there’s just too much manual work, and you have to balance between way too many apps to complete it. So an AI-native workflow is flipped. It’s actually a new mindset. It’s not time to close the books. The books are closed, and your close checklist is already almost complete, ready for your review and approval. So you can dedicate your time to advise and budget compliance. This is now possible thanks to technology, thanks to autonomous agents,” he said during his presentation. 

AI agent

In a follow-up interview, Seibert reiterated that the agents are capable of doing the vast majority of the bookkeeping workflow with virtually no need for human supervision. While humans can examine what the agents are doing at any given time, and view the data-driven insights they surface, it’s not strictly necessary: The bots can run completely independently. 

“It does 95% of it. You plug in your bank’s cards, payroll, almost everything is done. The things that the AI isn’t quite sure about, it surfaces for you in an inbox, and so you go in and categorize the remainder. Of course, if you’re doing advanced accruals, or project-based accounting or so on, you’ll still have to do those pieces, but we try to automate the 95% of the tedium that you’re just trying to do every month and save time,” he said. 

Digits emphasized the accuracy of their AI outputs. Regular users of large language models may be familiar with a concept called “AI hallucination,” which is a more artful term for “making things up wholesale,” but Seibert said that Digits’ autonomous Accounting Agents “never hallucinate” due to the nature of the product itself. 

He said that this is because the solution layers both LLMs and predictive models to do the work. The LLMs are not doing the calculations themselves, and in fact are specifically prevented from doing so. Instead it is the predictive models, trained on a massive amount of transaction data, that do the math. The role of the LLM is, instead, to orchestrate agent activity and communicate their results. 

“LLMs are generative. They hallucinate. Predictive models don’t, they can’t. They predict things like: Where should transactions go? We layer the two of them. So we use LLMs to orchestrate our agents. The agents have access to tools which are all predictive. And so when you look at Digits’ technology stack, we run 18 different models in production. Almost all of those are custom-trained prediction models, and then we use LLMs to orchestrate,” he said. 

He said during his presentation that the models are so accurate they not only outperform general models like ChatGPT and Claude by a significant degree, they also outperform human professionals. Digits pitted its agents against professionals from 12 outsourcing companies, with experience as CPAs ranging from a few years to over 30, to see who was faster and more accurate. He said that the humans were about 80% accurate versus 98% accuracy for the bots.

Meanwhile, in terms of speed, the humans took an average of 34 seconds per transaction, while the bots clocked in at 40 milliseconds per transaction. According to the Digits study, the transactions contained relatively fewer edge cases and incorporated a higher proportion of repeat transaction types compared to typical operational datasets. This composition contributed to an observable increase in accuracy rates across all evaluated systems, including both the Digits platform and the LLMs under assessment.

While he hesitated to call it a wholesale replacement for a professional accountant, he noted that it is a replacement in the case of the tedious tasks that accountants don’t like to do and that clients don’t necessarily value. 

“We do want it to take over the really low-value work that you’re just honestly wasting time on every month, and the clients don’t appreciate [because they just] assume the bookkeeping is accurate. They don’t appreciate all the time that takes to make it happen. And so we are trying to take over the tedium while leaving the meaningful work for you to really focus on,” he said. 

During his presentation, Seibert noted that the agents represent a third path that sidesteps the problems of both outsourcing and using LLMs. 

“It’s so painful to search for accountants with outsourcing. They need a lot of guidance, they make mistakes, and they don’t know the details or history of the business they’re working on … . GPT is exactly the same. You have to tell it what to do. It hallucinates frequently, and it doesn’t know that business at all. It’s just trained on general accounting knowledge from the Internet. Digits is completely different. Our agents know the accounting workflows. They run them 24/7, they’re based on predictive models, so they can’t hallucinate, and they have secure access to historical context with each business,” he said. 

When asked what’s next, he said Digits will be working on automating that remaining 5% of accounting tasks. This area represents use cases that are a little more tricky, such as splitting transactions, though he was confident in the future. 

“So we are constantly teaching the agents new skills, and so over the next few years, expect Digits to get better and better and better at getting rid of this tedium for you,” 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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