Compliance professionals at top 10 firm Grant Thornton will now be making use of the newly-enhanced CompliAI platform, which has gone from a largely spreadsheet-driven classic automation solution to one infused with generative AI from end to end to streamline and enhance service delivery. 

The platform uses advanced AI capabilities, including GenAI Assistants and a GPT Model Series to automate key tasks such as risk and control rationalization, question and procedure generation, and document request list creation. For example, it will suggest questions for the professional to ask, and based on the answers, generate additional followup questions and tasks. The software also features a suite of tools, including dashboards, task management, in-app commenting, notifications, a methodology document library, and a centralized file repository. This is so professionals can conduct tasks in minutes that would have traditionally taken days or weeks. 

Mike Kempe, chief information officer of Grant Thornton Advisors, noted that beyond efficiencies, another major intention with this solution was to create a more consistent experience for their clients. Different professionals approach things in different ways, both in and out of the accounting world, and so the client experience can vary widely depending on who is working on an engagement at a given time. It is hoped that this new platform can smooth out some of that variation so clients can get a better idea of what to expect. 

“We’re providing a better service to our client and a much more consistent one as well because we’re no longer relying on the quality of individuals, we’re relying on AI… In the past, the issue was that if I was providing a service I would do it one way, and [if] John was providing the service, he would do it a different way, so clients would get inconsistent quality. With this, we increase the quality, and it’s going to be much more consistent,” he said. 

Paradoxically, though, he believes this will actually serve to create a more, not less, personalized experience for clients. By using AI to get through the routine processes that the accountant would ordinarily be doing themselves, they have more time and energy for close collaboration with the specific client and so can take on a more strategic role in compliance engagements. 

“Our professionals right now [are focused] on how to use AI and on building that relationship with the client and making this a much more personalized service than we have had in the past,” he said. 

The newly-enhanced CompliAI platform is just one more step in GT’s wider AI ambitions. Kempe said they plan to replicate this approach across many more service sectors. The firm has a roadmap for at least five more AI-based solutions released over the next year and a half as part of its vision to incorporate the technology throughout its numerous practice areas. When pressed on the particulars he declined to be too specific, but said people can expect many different solutions. 

“There’s a lot of productivity solutions that we’re building at the moment, and we’re working with our partners and some startups as well [to roll it our internally.] There’s a couple more AI solutions in the audit space as well as in the tax space that we’re currently working on… But suffice to say, we’re investing heavily. We’re on a very significant roadmap to put AI into everything we do. That’s our mission,” he said. 

Wall Street has learned the hard way that black-box models can wreck balance sheets. Enron’s off-ledger special-purpose entities fooled analysts because auditors lacked the tools, or the will, to probe opaque structures. 

Two decades later, AI presents an even thornier transparency challenge, yet the accounting profession already owns the mindset to fix it. We can turn the audit playbook into an AI assurance framework that policymakers have been groping for.

A year ago, the Center for Audit Quality surveyed partners across industries and found that one in three companies has already embedded generative AI in core financial processes. That wave is cresting before governance rules are in place. The CAQ warned that model drift, undetected bias and hallucinated explanations could all distort financial statements if engagement teams rely on AI without documented controls.

The National Institute of Standards and Technology released the AI Risk Management Framework 1.0 in January 2023 after input from more than 240 organizations. A generative-AI profile, added in July 2024, provides detailed guidance for managing risks like prompt logging, hallucination and bias in generative models. Big adopters, including Microsoft and Workday, have already mapped their internal controls to the NIST RMF.

Regulators are starting to echo that warning. The Public Company Accounting Oversight Board issued a spotlight last July that could not be clearer. Humans remain responsible for any work product produced with AI assistance, and auditors must document how they evaluated the tool. It is accounting’s Sarbanes-Oxley moment for neural nets. If we seize it, we can shape a pragmatic oversight regime.

What would that look like? Start with the three legs every auditor knows: evidence, materiality and independence. Evidence means logging every prompt and output so reviewers can replicate the conclusion. Materiality means setting quantifiable tolerances for algorithmic error, not hand-waving about “low risk.” Independence means assigning a separate team, ideally with data scientists who hold no stake in the model’s success, to challenge assumptions. None of these ideas requires a new federal agency. They require extending time-tested audit standards to predictive code.

Europe has fired the opening shot. The EU AI Act classifies AI used in finance and education as “high risk” and mandates conformity assessments before deployment. U.S. firms operating in both markets will soon discover that the cost of exporting software can dwarf the cost of exporting widgets if documentation is sloppy. American regulators need not mimic the EU AI Act clause for clause, but they should embrace the Act’s insight: riskier models deserve stricter audits.

The National Telecommunications and Information Administration agrees. Its March 2024 report sketches an AI accountability ecosystem built on third-party audits, incident registries, and benchmark datasets. That is music to accountants’ ears; it sounds like GAAP for algorithms. Auditors have spent a century refining peer review, work-paper retention, and inspection cycles; they can transplant those muscles to model assurance with minimal retooling.

Skeptics worry about talent shortages, yet firms once trained auditors in statistical sampling when that was new. Tomorrow’s audit associate will need R or Python alongside pivots, but the pedagogy remains: test controls, document exceptions and issue an opinion. The pipeline problem is solvable if higher education integrates AI ethics and assurance modules into accounting curricula now.

A second objection is competitive secrecy. Companies say revealing model internals will hand over trade secrets to rivals. Audit protocols offer a compromise: confidentiality agreements for reviewers plus public summaries of findings, akin to key audit matters. Investors care less about the recipe than about the assurance that the chef followed food-safety rules.

History offers a precedent. When Congress created the Securities and Exchange Commission in 1934, financial statements suddenly had to meet public standards. Far from stifling growth, transparency fueled the longest bull run in history by lowering information risk. AI assurance can do the same. Markets crave clarity more than ever as algorithms move from back-office helpers to decision makers that allocate credit, price insurance and flag Suspicious Activity Reports.

The next 12 months are decisive. The PCAOB is weighing whether to update its audit standards explicitly for AI. Instead of waiting, firms should pilot voluntary algorithm audits and publish the results. The first mover will earn reputational capital that no marketing budget can buy, and the blueprint will help regulators draft proportionate rules.

Trust has always been accounting’s export. In the AI era, the ledger expands from debits and credits to tokens and weights. The discipline that once tamed creative bookkeeping can now tame creative code, and that, more than any flashy demo, is what will keep capital flowing. Audit survived spreadsheets; it will thrive on silicon.

President Donald Trump on Tuesday pushed back on demands from Republicans who have threatened to sink his giant tax bill if the legislation does not significantly boost the state and local tax deduction, said Representative Mark Amodei of Nevada. 

In a private meeting with House Republicans, Trump singled out the lawmakers from New York, New Jersey and California who have rejected the $30,000 deduction limit — three times the current cap — contained in the legislation moving through the House.

“He wants to leave it where it is, that’s basically what he said,” Representative Bruce Westerman of Arkansas said of the SALT provision in the bill after the meeting. 

The confrontation came moments after Trump told reporters the SALT deduction benefits Democratic states and politicians, signaling that the tax break, which predominantly benefits high-tax states like New York, New Jersey and California, isn’t a central concern of Republicans.

“It’s not a question of holdouts. We have a tremendously unified party,” Trump said Tuesday before meeting with lawmakers. “There’s some people that want a couple of things that maybe I don’t like or that they’re not going to get.”

Still, Trump has repeatedly pledged bigger SALT deductions, which were limited in his first-term tax cut bill. A faction of Republicans from high-tax states have threatened to sink Trump’s agenda over SALT. Trump, however, shrugged off those concerns. 

“There are one or two points some people feel strongly about, but maybe not so strongly,” Trump said ahead of the meeting. 

House Speaker Mike Johnson met with those SALT holdouts late Monday, but left without an agreement.

Representative Nick LaLota, a New York Republican, said House leaders offered a SALT proposal that would temporarily raise the cap higher than the $30,000 in the draft bill, before reverting back to the lower level. 

“Any proposal that has the cap falling off a cliff is unacceptable to me,” LaLota told reporters Tuesday morning. “Now is the time to get it right.”

Another New York Republican, Mike Lawler, told reporters there is no SALT deal and a vote on the bill — planned for as soon as Wednesday — will fail without one.

Johnson was more positive about the chances for a deal. He still plans for the House to vote on the package by the end of the week. 

“We’re going to get an agreement on everything necessary to get this over the line,” he said Tuesday.

The bill approved last week by the House tax committee sets a $30,000 cap for individuals and couples. That draft called for phasing down the deduction for those earning $400,000 or more, a plan quickly rejected by several lawmakers who called it insultingly low. The current writeoff is capped at $10,000.

Stephen Miran, who chairs the White House Council of Economic Advisors, said he was confident Trump would be able to quickly reach a deal on SALT with House Republicans.

“The president will deliver SALT relief to American households. I don’t know exactly what the number will shake out,” Miran told Bloomberg Television on Tuesday. “The president is one of the best negotiators in history and he’s shown over a career spanning decades that he can forge hundreds of deals and I think he’ll forge another one right in front of us now.”

The holdout lawmakers — who also include New York’s Andrew Garbarino and Elise Stefanik, New Jersey’s Tom Kean and Young Kim of California — have threatened to reject any tax package that does not raise the SALT cap sufficiently.

Garbarino said Johnson made the group several offers and that they’re awaiting more analysis Tuesday morning. 

“I’m just happy we’re having the discussion and they’re working with us,” Garbarino said.

Republicans are also squabbling over spending reductions in the bill, including weighing cuts to Medicaid health coverage and nutritional programs for low-income households.

They are trying to keep revenue losses from their tax-cut package down to a self-imposed limit of $4.5 trillion over 10 years. The current package has a $3.8- trillion revenue loss.

— With assistance from Jamie Tarabay, Jonathan Ferro, Skylar Woodhouse, Catherine Lucey, Jack Fitzpatrick, Steven T. Dennis and Ari Natter.