What Happened
Avalara published a report titled "Agents of Change: How the Race to Deploy AI Agents is Outrunning Financial Governance" in late July 2026, drawing on surveys of more than 1,500 CFOs and senior finance leaders across Australia, the US, UK and India. The Australian cohort numbered 250 respondents.
The headline finding is blunt: 88 per cent of Australian finance leaders reported feeling moderate or significant career pressure to demonstrate that their AI agent investments are delivering ROI. Globally, that figure reaches 92 per cent, with half of all respondents worldwide describing the pressure as significant. The gap between regions is notable. In the US, 57 per cent called the pressure significant; in Australia, 32 per cent did.
Speed is driving the agenda. In Australia, 59 per cent of respondents said the push to deploy agents is focused primarily on getting them into production quickly. Only 12 per cent said their organisation prioritises governance over deployment speed. The global picture is sharper still: 71 per cent of respondents said the pressure they feel relates entirely or mostly to speed, and just 7 per cent reported their business is putting governance first.
Why It Matters
Finance functions are not a neutral testing ground for AI. They sit at the intersection of sensitive data, regulatory obligation and material financial risk. When agents gain access to reconciliation, validation and compliance workflows, the question of what those agents can see and what they can do becomes a compliance matter, not just a technology one.
The Avalara report captures a tension that is already visible in Australian enterprises. Boards and executives are pushing for deployment. The governance infrastructure to match that pace is not keeping up.
As one contributor to the report put it: "Finance leaders are being asked to move quickly with AI, but governing agents requires a new combination of domain, AI, IT and data governance expertise." That combination is hard to assemble quickly, and the report suggests most organisations have not yet done so.
The risk is concrete. "As AI agents gain access to financial and compliance workflows, organisations need to know what those agents can see, what they can do and when human approval is required. That kind of control has to be built into the architecture, not added after the fact."
Key Details
The report identifies delegation of authority as a specific concern. "Organisations are increasingly exploring how to use AI to do reconciliations, validations and much more," one contributor noted. "The risk comes from the delegation of authority that happens when those things start to be infiltrated by AI. You may be indirectly giving an agent access to data that you do not want them to have."
Tax functions drew particular attention. "You can't give a tax team an AI tool and expect transformation, just as you can't ask AI engineers to solve complex tax problems on their own. The strongest results come when tax professionals and AI specialists work together to build solutions that are accurate, practical and scalable."
The report's framing of the ROI question is also worth noting. While 90 per cent of Australian respondents said their AI agent initiatives are delivering at least some measurable ROI, the global picture is described as more nuanced. The report argues that organisations realising the greatest value "won't simply deploy more agents. They'll leverage agents with trusted data, governed workflows and clear controls that enable automation with confidence."
Background and Context
Agentic AI, where software systems take sequences of actions with limited human intervention, has moved from concept to production across Australian enterprises faster than most governance teams anticipated. The finance function has been an early target because the use cases are clear: automated reconciliations, tax calculations, compliance checks and audit trails all suit agent-style automation.
The pressure on CFOs is not abstract. Career stakes are attached to AI ROI in a way that was not true of earlier enterprise software cycles. The Avalara data puts numbers to something finance leaders in Australia have been describing informally for the past year.
SecurityBrief Australia has reported separately on the broader enterprise AI readiness question, noting that AI is already running inside Australian organisations and that governance frameworks are struggling to catch up with the pace of deployment.
What Comes Next
The Avalara report calls for governance to be built into AI agent architecture from the start, not retrofitted once agents are in production. That is a structural argument, not a process one. It implies that organisations currently racing to deploy will need to revisit their architectures, not just add policy documents.
For Australian CFOs, the immediate practical question is whether the career pressure to show ROI is being balanced against the institutional risk of deploying agents without adequate controls over data access and decision authority. The survey data suggests, for most, it is not.