By Lisa Huang, SVP of Product – AI, Xero.
As automation rewrites the rules of business, the accounting profession stands at its own crossroads. AI isn’t just changing how accountants work – it’s redefining the foundation of the profession by eliminating the administrative tasks that once dominated the early years of an accountant’s career.
This shift is no longer theoretical – a new Stanford University study found that early-career jobs in AI-exposed fields like accounting have declined by 13% since 2022. However, the same study reveals that experienced professionals in similar roles have remained stable or even grown, demonstrating that strategic insights are still highly valuable to clients.
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These data point to a clear reality: The path forward isn’t resisting automation but reimagining the role of accountants across all levels to deliver more accurate, efficient, and highly valued strategy.
The Readiness Gap
While firms navigate this transition, the clients they serve—specifically small businesses—are facing their own AI learning curve. A correlation has already emerged between AI implementation and financial success. According to Xero’s recent AI for Small Business white paper, 65% of small businesses believe AI will soon be central to their operations, and small businesses using AI weekly were twice as likely to report revenue growth compared to those that don’t. This provides clear evidence that early adopters are already noticing tangible financial benefits.
Yet this early optimism in integrating AI is tempered by hesitation. Xero’s whitepaper also found that 53% of small business owners say AI’s disappearance would have no impact on their day-to-day operations, calling this contradiction a “readiness gap,” signifying that enthusiasm is outpacing execution, and business owners are stuck between curiosity and capability.
The Opportunity for Accountants
These insights underscore a critical opportunity for accountants to lead with both technical fluency and human judgement. Bridging the gap between a client’s optimism and their actual action requires strong leadership and full transparency from a trusted advisor.
Accountants can make the greatest difference here: translating AI’s promise into practical outcomes by advising clients on where to start, which tools to trust and how to measure real value from adoption.
To capitalize on this, firms must adapt their approach based on experience level. On the one hand, entry-level accountants should be prioritizing learning how to interpret data, advise clients and apply professional judgement from the get-go, elevating their careers from task execution to insight generation at the jump. As for mid-level and senior-level accountants, their focus amongst this shift should be on deepening their advisory expertise while also leading the thoughtful integration of these technologies into firm workflows to ensure AI enhances the professional judgment and strategic insight clients rely on.
Moving From Experimentation to Foresight
The goal is to shift the perception of AI from a tool that completes tasks to a partner that collects deeper data and insights. With accounting platforms making AI more accessible—such as Xero’s financial superagent, JAX (Just Ask Xero)—the profession is on the verge of redefining its value from executing admin to using data for strategic foresight.
By helping clients take action to become financially stronger, accountants not only build trust in AI but also solidify their own reliability. Those who embrace AI as a trusted collaborator will future proof their firms and strengthen their role as indispensable advisors guiding businesses through this next era of growth.
About the Author
Lisa Huang is SVP of Product – AI at Xero, where she leads global strategy and development for AI products, platforms, and mid-market solutions. Lisa built Xero’s AI product organization from the ground up, overseeing the launch of JAX, the company’s financial superagent designed to help small businesses and their advisors unlock deeper insights and save hours on manual tasks. A former AI product leader at Google and Meta, Lisa brings over 15 years of experience advancing responsible innovation across artificial intelligence, machine learning, and financial technology.
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