AccountsIQ

If you can’t trace a number back to its source, you can’t stand behind it. That’s as true for AI as it is for anything else in finance. Our new research over 1,000 finance leaders across the UK and Ireland backs that up. 81% already trust what AI produces. Yet 82% feel pushed to adopt it faster than they’re comfortable with, and 76% worry about becoming too reliant on it for decisions that used to be theirs. So the gap isn’t about accuracy. It’s about seeing the workings. What finance leaders asked for is reasonable: a person approving entries before they post, an explanation for each decision, and a trail from any number back to source. That’s how we’ve built AI in AccountsIQ. AI drafts the work and people decide. Nothing posts without approval, customers choose which agents run, and their data is never used to train public AI models. Once finance teams can check it, the conversation moves from “should we?” to “where do we start?” Automate the work, not your judgement. Full findings: https://lnkd.in/ekPFNfME

How many of this month's journals are copies of last month's? For a lot of finance teams, month-end still means rebuilding the same postings by hand - re-keying payroll every period, entering adjustments line by line, and working out prepayment spreads in a separate spreadsheet. In the next Finance in Focus session, Andrew Faulkner, Sales Manager at AccountsIQ, shows how to cut that repetition: re-using regular journals, setting up recurring accruals and deferrals, and spreading prepayments as you process the invoice. He’ll also cover a quicker route for journals your team prefers to prepare in Excel. 20 minutes. Wednesday 4 November, 10:30am. Register here 👇 https://lnkd.in/ecWr7EGy

My signature goes on the number whether a person calculated it or an algorithm did. That’s the part of the AI conversation I think gets missed. We surveyed over 1,000 finance leaders across the UK and Ireland for our CFO AI Paradox research. 82% feel pushed to adopt AI faster than they’re comfortable with. But the technology isn’t the problem: 81% already trust AI-driven outputs, and 96% trust their financial data. The hesitation is about accountability. 76% worry about becoming too reliant on AI for decisions that used to be theirs. Before I’d trust AI with my team’s work, I’d want to see three things: → A person approving entries before anything posts → Decisions I can explain → A clear trail from any figure back to its source None of that asks for less AI. It asks to see the workings. If you’re weighing up where AI fits in your finance team, the full finding in the report is worth a read: https://lnkd.in/ePTMtsnb

When AI gives you an answer, it needs to be auditable. That’s the standard finance has always held itself to. A number without a source doesn’t make it into a board pack. AI shouldn’t get a lower bar just because it’s faster. Our research with more than 1,000 finance leaders backs this up. Most already trust what AI produces. What they want is to see how it got there: an explanation for each decision, clear labelling of what AI touched, and an audit trail from any number back to its source. As a CTO, I see that as the brief. In AccountsIQ, AI drafts the work and people decide. Every suggestion shows its reasoning, nothing posts without approval, and customer data is never used to train public AI models. Speed matters. But in finance, being able to prove the answer matters more. Read the CFO AI Paradox findings: https://lnkd.in/egdgnWVB

Ask a finance leader if they trust their numbers, and the room doesn't hesitate. Ask about if they trust AI with those numbers, and it goes silent. Today, our third CFO Mindset Report goes live. It sets out to explain that hesitation around AI. Finance leaders aren't skeptical about their data. 96% trust its accuracy. They don't have doubts about the technology either. 81% trust what AI produces. Yet 82% feel pushed to adopt AI faster than they're comfortable with. What's missing is clarity. On how to use it, where to start, and when to rely on it. Inside the report: → Where finance teams really stand on trust today → What they're still deciding without the full picture (68% say big decisions are made without enough data) → What they told us would give them the confidence to go further and faster with AI Huge thanks to every finance leader who took part, and to the team who brought this together. If you lead a finance function, I'd love to know: what would give you more confidence to move faster with AI? Read more here: https://lnkd.in/eTJU57GT

Could you tell a real AI statistic from a fake one? → Only half of finance leaders trust what AI produces → 82% feel pressured to adopt AI faster than they’d like → Less than 1% of finance leaders don't trust AI at all Our new research, The AI Trust Paradox, looks at how finance teams really feel about AI, and where trust and adoption don’t line up.