The American Institute of CPAs’ Auditing Standards Board is looking for feedback on its proposed strategic plan for 2026-30, as it develops guidance in areas such as sustainability assurance and fraud detection.

The board issues standards for auditing private companies, quality management standards for practitioners providing audit and attest services to private companies, and attestation standards. In addition, it creates practice guidance for performing audit and attestation engagements under AICPA standards.

The proposed plan revolves around five initiatives:

• Develop high-quality standards in the public interest.
• Enhance communications with our stakeholders.
• Think and operate strategically.
• Keep our standards relevant in a changing environment.
• Support the effective implementation and application of our standards.

“The feedback on the proposed strategy is incredibly valuable to the ASB,” said Sara Lord, chief auditor of RSM US LLP and ASB chair, in a statement Wednesday. “The board plays a vital role in serving the public interest by developing, updating and communicating auditing, attestation and quality management standards, and we need stakeholders’ input to help fulfill our mission.”

Comments on the 2026-2030 strategic plan proposal are due June 13, 2025, and can be made by completing a related survey or by sending them directly to [email protected].

Beyond the forward-looking strategic plan, the ASB is continuing to move ahead with its 2025 work plan, which includes:

• Working on standard-setting projects to address the growing demand for sustainability assurance and the significant public interest in strengthening the auditor’s responsibilities relating to fraud.
• Seeking feedback on an exposure draft, Proposed SAS External Confirmations, which proposes changes to various AU-C sections in AICPA Professional Standards. The comment period ends June 30.
• Seeking comment on an exposure draft, Proposed SSAE Scope Limitations in a Review Engagement, which would amend AT-C section 210 to permit issuance of a qualified or disclaimer of conclusion in a review engagement when a scope limitation exists. The comment period ends May 30.

“The ASB has several important projects underway, and we are looking forward to the public comments,” said Jennifer Burns, chief auditor of the AICPA. “Online surveys have been developed and comment periods have been staggered to facilitate the comment process.”    

For more information, check out the ASB’s resource page.

Estate planning, like any advisory service in the accounting world, is concerned with dollars and cents. But, like other advisory areas relatively resistant to AI disruption, it is also concerned with human relationships and feelings connected with what is typically understood to be a very emotionally sensitive topic: death. It’s not even a question of whether or not AI could do an estate planning engagement on its own but whether the client would even want it to. David Nelson, an estate planning specialist with top 25 firm Aprio, noted that the highly personal nature of estate planning means it would be difficult to consider AI taking over the process. 

“Some mathematically driven fields may see automation sooner. Estate planning, however, is highly personal. At the end of the day, you’re sitting down with someone to talk about their mortality. There’s intrinsic value in human interaction for discussions like that,” said Nelson. 

Nelson himself said he has been using AI primarily as a way to synthesize information sources in order to produce an analysis of the tax ramifications of a given plan, which in turn also helps with developing plans based on the data they find. He also uses it to analyze documents, particularly long and dense ones, that can help spot issues that the humans missed, such as contradictions in the plan itself or conflicting effects from its various provisions. 

Overall, Nelson treats AI as a research tool. Looking at his field overall, he said that the estate planning world has picked up the technology, but not as deeply or as fervently as other specializations. People use AI tools fairly regularly for analysis or plan development, but it’s not a dominant part of the practice. It is not even used in the calculations. While no one is using paper and pencil to determine estate tax implications, professions are still mostly using “legacy number-crunching software.” Part of this might be because, so far, he has not seen an AI model that can perform the level of analysis he and professionals like himself do regularly. “On our end, AI is still a tool to guide analysis. But as far as I’ve seen, AI can’t yet produce the kind of comprehensive analysis we need. For example, if a client comes in with an estate plan that includes various assets—an S corporation, marketable securities, a C corporation, and trusts to hold portions of those assets—the tax implications of each are different. The complexity increases when you factor in a trust as an owner. AI isn’t yet able to aggregate and synthesize all of those issues into a cohesive analysis,” he said. 

(See our feature story, “Staying ahead of AI.”)

Hanna Dameron, an attorney with law firm ArentFox who has spoken at accounting conferences on the role of AI in estate planning, added that AI is not at the point where it can understand the complex human relationships and social factors that drive many engagements. She said you could take two different clients with the exact same assets and the exact same number of children and there may be 15 different plans that could be appropriate for them depending on things like how they feel about their various family members, how they view future investments, how they want their children to access their money, and more. Walking clients through this requires the emotional intelligence to understand their goals and explain to them in plain language how they could make a plan to accomplish them. She did not feel confident AI would be able to handle these emotional complexities just yet. 

“Estate administration is a very emotional process. If you have the family members squabbling over who gets grandma’s painting, you can certainly see a need for a human to come in and help mediate those disputes. But it’s also just the emotional process of ‘somebody’s got to go through the boxes and figure out where this asset might be’ or ‘there’s an insurance policy we never heard about. How does that make me feel that this family member never told me about that insurance policy?’ So, it’s not just dealing with the administration of dollars and cents. You’re looking at a deep financial portrait of somebody’s life and what they’ve left behind. And there can be a lot of emotions and questions that come up in that,” she said. 

(Read more: “AI in advisory: What work is at risk?“)

She noted that she speaks from experience, having shifted into estate planning after the death of her own mother and being the executor of her will, which was a difficult experience both emotionally and administratively. 

 “It made me feel very passionate about helping families set up a plan and then administer the plan with compassion and emotion. So, I think, when somebody is in a grieving state, of course, they want somebody to talk to, not just about sorting out what they’re dealing with, but also dealing with a legacy,” she said. 

Artificial intelligence has brought new efficiency and productivity to the valuation field, particularly where it concerns data entry, processing and analysis, which is a major part of the process, as well as generating the reports to explain what the data says. Lari Masten, who heads valuation advisory firm Masten Valuation, said that working the technology into her own processes has saved countless hours, turning tasks that were once an interminable slog into relatively quick jobs that can be completed in minutes. 

One of the biggest use cases in the valuation world, said Masten, is data entry and processing. Valuation tends to require a lot of data inputs that can take hours or even days to complete, but recent AI advances have allowed her to sort through literally thousands of documents to find data patterns. This not only aids her own insights but also thwarts those who want to hide those insights in massive piles of unstructured data. 

“Recognizing patterns [means] you can dump a ton of PDFs into a model and it can quickly summarize what is going on and put things in order a lot of times. I do a ton of litigation, and it’s so helpful there because for valuation purposes generally it’s not somebody who wants somebody looking at all their financial records and it comes in a big old pile, and so it helps organize it — ‘Here’s 4,000 pages; organize it by date and by financial record first and then underlying quantitative data second, etc.,'” said Masten. 

Her firm also uses AI for coding support when creating new macros, some of them quite complex and developed for specific clients for evaluation purposes. Instead of having to constantly test and retest an ineffective macro, professionals now can describe what it is they need to do and why, and the AI can provide assistance. 

“We’re not having to go out to Microsoft or Google and ask how to do a particular task. We can just go to one place and not be distracted by it,” she said. 

But while these might seem like purely quantitative processes, Masten said there are uniquely qualitative elements that make it difficult to imagine AI ever completely taking her place, saying professional valuation is both a science and an art. While valuation involves a lot of calculations, what exactly is calculated, and how, can come down to the holistic judgment of the professional. This has been the case, she said, even before AI came onto the scene. 

(See our feature story, “Staying ahead of AI.”)

“For decades, valuation has had software out there. You can dump a bunch of numbers in there and churn, but it doesn’t mean that it gives you a good output. I don’t have confidence that if I put in a bunch of information into a tool that it’s going to be able to understand how Lari Masten would reason through and solve that problem. It can do the math, but did it do the math in the way that when I do valuations? When anybody does a valuation, there’s three or four dozen decisions that they make and each decision gets them to a different place,” she said. 

There are reasons she does the things she does that a computer can’t necessarily understand at this point in time. While the calculations can be automated, according to Masten, the thinking behind them cannot, particularly where it concerns the ultimate conclusion of a valuation engagement. She has yet to find an AI model that can do that. 

“They’ll say, ‘Here’s three ways to solve it’ but they don’t understand if this one is more reasonable than that one. If you work on it you can automate a lot of portions … but the bigger picture of, what is the problem I’m having to solve? What standard of value do I have to follow based on that problem? How is the valuation date going to make a difference? What was known or knowable on a date? AI is not going to be able to really sift through that depending on what the inputs have been already. It’ll just pull information and it may not know when something became known or knowable, so there’s that professional judgment. The good reasoning, the backbone really behind any valuation, can’t be automated,” she said. 

Overall, she is supportive of AI and believes it will be of great benefit to the profession, but noted that there are some cons, particularly the need to vet information and not automatically trust what the AI says. Further, she expressed concern that even though AI cannot replace a valuation expert, professionals over time might lose some of those inherent human qualities that prevent this from happening now. 

(Read more: “AI in advisory: What work is at risk?“)

“There’s some measure of responsibility on the valuation people to go in and make sure that they’re vetting that information, that they’re still applying their logic, overlaying their skills, knowledge, expertise, training, that kind of stuff because [no matter] how great it is as a tool, it can’t use that logic that we have, it’s not a replacement for the interactive qualitative piece that the valuation analyst knows and tie that necessarily to the quantitative art that it does,” she said. 

This ties into communicating to clients the value of a human valuation expert: Yes, a computer can crunch the numbers, but that’s not all there is to an engagement, and not even necessarily why someone might hire a human professional in the first place. 

“It’s not [just] how to do valuation. The value ad is that you understand the problem,” she said.