Sequence Collect 2026: AI Innovation in CPA Practices
Vishal Thakkar runs partnerships at CPA.com, Jordan Fladell leads technology advisory at Aprio after years on the other side of the table as a client, and Elinor Litwack spent 19 years making partner at GRF and now leads the firm's AI strategy. On September 9th, at Sequence's Collect 2026, they compared notes on what AI is really doing inside accounting firms, from why data is the thing gating automation to how firms evaluate vendors now, and which generation in the firm is actually using the tools.
What finance should outsource when the work is changing
At Collect 2026, Vishal from CPA.com sat down with Jordan Fladell, Partner at Aprio, and Elinor Litwack, Partner at GRF CPAs & Advisors, to talk through how accounting firms are changing as more of the underlying finance work gets automated.
Don’t outsource the finance function all at once
For Elinor, the question isn’t whether finance should be outsourced or kept in-house. It’s which parts belong where.
She separates the work into three layers: core tasks like payroll, AP and monthly close; controller work around controls and safeguarding assets; and the CFO layer covering strategy, FP&A and technology decisions.
As more of the first layer gets automated, finance teams can look at the talent they already have and decide where an outside firm fills a real gap.
For larger companies, that often means a hybrid approach rather than outsourcing or insourcing everything. The systems an outside firm builds should scale with the business and eventually be easy for an internal team to take over.
AI makes experience more useful
GRF expected its younger employees to use AI the most. Instead, Elinor found that usage was highest among leadership.
Jordan thinks experienced people have an advantage because they know what to do with the time AI gives back. If an agent takes work off someone’s plate, the value isn’t just doing the same job faster, but using that time to advise the client on something the technology can’t.
He’s already seen that happen at Aprio. One junior member of the audit team was promoted two levels after using AI and FieldGuide to change how they worked with a client.
As more of the underlying accounting work gets automated, the industry knowledge and judgment around it become a bigger part of what clients are paying for.
Bad data is holding AI back
For Jordan, the biggest barrier to AI adoption in finance is data.
A company can upgrade its software and still get disappointing results if the information underneath it was never structured properly. Finance has made that harder through years of correcting problems with journal entries: the financials can end up right while the underlying data becomes increasingly difficult to automate against.
That matters more as AI moves from helping with individual tasks to taking actions itself, because an agent needs the same context, access and understanding of what good looks like as the person who would otherwise be doing the job.
Better models can’t fix the information underneath them, which means finance teams expecting AI to automate more of the function need to get the underlying data in shape first.
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