Trust in AI Fell. That's the Best News in The 2026 AI Report

By Vidya Peters, CEO at DataSnipper 

Trust in AI fell hard. A year ago, 78% of the profession trusted AI to deliver quality at scale. This year it is 55%. That is a 23-point drop in a single year, and most people would read that as a setback. But I read it as the profession growing up. 

Here is the detail that changes everything about how you interpret that number. Trust did not fall evenly. It fell hardest among the people using AI the most. Partners who review AI-assisted work trust it at 79%. The individual contributors who actually produce that work trust it at 50%. The closer you sit to the real output, the more skeptical you become. 

That is not cynicism. That is experience. The people closest to the rough edges of AI have seen where it breaks, and they are telling us exactly where the line sits between what AI can do and what still needs a human. When 73% of the profession says AI is essential while only 55% trusts it, that gap is not a problem to be solved with better marketing. It is the profession being honest in a way that very few industries are willing to be. 

I have always believed auditors and finance professionals are underestimated on this. They were never going to adopt AI for the thrill of it. They carry real liability for the results. They waited until they could see a path to doing it right. And the moment they started using it at sale, they got specific about what they trust it with. That is the behavior you want in a profession where getting it wrong has real ramifications. 

Access is not adoption. A pilot fails not because the technology is bad, but because the usage is ad hoc, there is no verification layer, no clear owner when something goes wrong, and no fit with how the work actually gets done. Our report found that only 56% of organizations have clear governance ownership of AI. In an industry built on the idea that every workpaper has a preparer and a reviewer and every engagement has a signing partner, letting AI in without an owner is the gap that sinks the pilot. 

The rest of the report points to the answer, and it is refreshingly unglamorous. When you ask professionals what matters most in an AI tool, knowledge of accounting standards comes first at 87%. General language capability comes last. They are not asking for smarter AI. They are asking for AI that understands how their work is done. Two in three say the audit-specific tools they need do not exist yet. 

And on the question everyone is anxious about, the profession is clear. About 80% are comfortable letting AI extract data, compare documents, and take a first pass. Only 38% are comfortable letting it make the final sign-off. That is not a limitation to engineer around. That is professional judgment drawing a line exactly where it should be. AI handles the processing. People inspect it and make the call. 

There is one more number I want leaders to sit with. When we asked what professionals would do if AI freed up 30 to 50% of their capacity, almost half said they would reinvest it into higher-value work. Only about one in nine mentioned reducing team size. The profession does not see AI as a way to cut people but as a way to grow into the work that has always mattered more. 

We are past the question of whether AI belongs in audit and finance. We are now in the harder and more interesting conversation: how do we build it, deploy it, and govern it in a way this profession can stand behind. The organizations that will define the next era are not the ones racing to automate everything. They are the ones automating what should be automated, verifying what must be verified, and keeping humans accountable for the outcomes that matter. 

The falling trust number tells me the profession is finally asking the right questions. That is not a step backward. That is the moment the real work starts.