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EY, Deloitte, Digits tout agentic AI partnership with Nvidia

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Big Four firms EY and Deloitte, as well as accounting automation solutions provider Digits, all announced partnerships with technology company Nvidia, which has gone from a company known mainly for its video graphics cards to a major player in the AI space within just a few years

EY and Deloitte’s respective announcements both centered around the launch of their own agentic AI platforms built on Nvidia’s technology infrastructure, including its new Llama Nemotron family of open reasoning models, which is adapted from the Llama LLM initially developed by Meta but used widely since it leaked in 2023.

Nvidia said that, through training and refinement, Llama can more effectively perform multistep math, coding, reasoning and complex decision-making.

Deloitte’s Zora AI

Deloitte announced the release of its Zora AI by Deloitte platform Monday, which offers a suite of ready-to-deploy agents that are said to perceive, reason and act, autonomously executing complex business functions, serving as a way for clients to augment their workforce as well as boost their effectiveness. The three agents offered by the platform are Zora AI for Finance, Zora AI for Procurement and Zora AI for sales and marketing. 

Deloitte said the agents can source, extract and interpret real-time, multimodal data from structured and unstructured sources; run analytical and mathematical models to define related insights and trends; translate insights into easily consumed formats; provide scenario analysis and recommendations on business-critical decisions; and coordinate and perform a set of actions—in collaboration with other agents—to execute complex, nuanced workflows, from beginning to end, including transaction processing, anomaly detection and resolution, and self healing. 

“We are entering the autonomous enterprise era where agents can transform work and business models, ushering in entirely new ways of working,” said Deloitte US CEO Jason Girzadas in a statement. “Our vision with Zora AI is to assist our clients in their transition into this new era, where agents and employees interact to reinvent business processes and unlock new sources of business value, growth and innovation for their organizations.”

Deloitte itself is using Zora AI for Finance internally to streamline and automate its finance processes, including expense management. The expense management agents monitor expenses across payroll, facilities, sales and marketing, and employee time and expenses, enabling finance leaders to identify expense outliers, compare expenses against industry and competitor trends, and drill down into specific budgets. Deloitte estimates Zora AI will reduce its costs by 25% and increase its productivity by 40%. Deloitte plans to implement Zora AI for thousands of users by the end of 2025.

EY.ai Agentic Platform

EY also announced Monday the deployment of its own EY.ai Agentic Platform on the full Nvidia AI stack to respond to real-time events, adapt to regulatory changes and drive smarter financial and risk decisions across global operations. The EY.ai Agentic Platform will run across client clouds, on-premises, at the edge, and the Nvidia Cloud Provider ecosystem. Nvidia is holding a conference in San Jose this week.

The platform is, for now, primarily for internal use as part of EY’s “Client Zero” transformation, in which EY tests AI deployments to guide clients as an example of effective and responsible use of the technology. This initial deployment will integrate 150 AI agents supporting 80,000 EY professionals across data collection, document analysis and review, and income and indirect tax compliance. EY.ai risk agents will also work with risk professionals to deliver new AI-native services. The third-party risk management agent will enable clients to manage risk more comprehensively and increase productivity.

The platform overall supports EY’s Responsible AI Frameworks as well as Nvidia NeMo Guardrails and EY SafePrompt software to more effectively mitigate AI risk at the agent level. It also supports a framework for agent creation and orchestration, which will use Nvidia Blueprints, including AI-Q Blueprints, to operate across third-party agent platforms. These frameworks will, in turn, support a collection of “fit for purpose” models chosen and designed for agentic solutions, such as indirect tax, income tax compliance, financial crimes, regulatory compliance and financial reporting, and targeted sector solutions for finance, marketing, cyber resiliency and supply chain, all powered by client-specific reasoning models. The platform also has a Model Development Suite that lets users create custom, enterprise-ready AI reasoning models using NVIDIA AI Foundry.

“With the EY.ai Agentic Platform, we are moving fast to help the world’s largest organizations transform their enterprises and streamline increasingly complex compliance requirements, while enhancing productivity and operational excellence across our own businesses,” said EY global chair and CEO Janet Truncale. “In collaboration with NVIDIA, we’re harnessing the collective knowledge of 400,000 skilled professionals, and the broad spectrum of EY services, to help shape the future with confidence in a fast-moving, highly competitive global economy.”

Digits AGL on NVIDIA Triton

Finally, accounting automation and solutions provider Digits, on the same day, also announced that its own complete solution, centered around the recently-released Autonomous General Ledger, successfully developed and deployed vertical-specific large language models (LLMs), achieved using NVIDIA accelerated computing and NVIDIA Triton Inference Server, which is optimized for AI models.

Digits said that, through using this optimized inference server, they were able to increase the number of requests it can process (a metric generally referred to as “LLM throughput”) tenfold to create its verticalized application of Accounting AI. By “vertical,” Digits means the models, rather than having generalized training like ChatGPT or Claude, have been trained only on relevant, domain-specific information, which focuses outputs and reduces the possibility of inaccurate information. This reflects an overall move in the industry away from generic one-size-fits-all models, of which there are now many, toward specialized applications that deeply understand specific business domains. 

“You can think of LLMs as very generic,” said Digits CEO Jeff Seibert in an email. “They train on substantially the entire internet, and they have a broad base of horizontal knowledge, but they are not specialized in any specific field. We have combined the power of LLMs with over a dozen custom-trained models that specialize in double-entry accounting and the related workflows [specific to the accounting industry].”

When asked about the development process, he said Digits both fine-tuned publicly available LLMs to be more accurate for given tasks and spent five years training its own predictive models from the ground up on a proprietary data set of $825 billion worth of transactions. 

“You can think of Digits AGL as a symphony: we orchestrate over a dozen models together in production, most of which are completely unique and created from scratch in-house,” said Seibert. 

While Digits has been providing solutions since 2018, Seibert said this will be the first time the company is launching the full set of products, including the Automated General Ledger. 

“Previously, only pieces of Digits have been available (Reporting, Dashboards, Bill Pay and Invoicing), and this is the first time we are launching the full ledger — the AGL — to actually automate the bookkeeping,” he said. “After a year of intensive testing with hundreds of businesses via our full-service accounting offering, we’ve now launched it self-serve for small business owners and startup founders to automate their finances.”

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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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