{"id":113296,"date":"2026-07-21T13:16:09","date_gmt":"2026-07-21T13:16:09","guid":{"rendered":"https:\/\/www.europesays.com\/ai\/113296\/"},"modified":"2026-07-21T13:16:09","modified_gmt":"2026-07-21T13:16:09","slug":"finance-leaders-are-racing-to-deploy-ai-agents-before-governance-is-ready","status":"publish","type":"post","link":"https:\/\/www.europesays.com\/ai\/113296\/","title":{"rendered":"Finance Leaders are Racing to Deploy AI Agents Before Governance is Ready"},"content":{"rendered":"<p class=\"wp-block-paragraph\"><a href=\"http:\/\/www.avalara.com\/\" rel=\"nofollow noopener\" target=\"_blank\">Avalara<\/a> have released new research revealing that while finance teams feel pressure to\u00a0 deploy AI agents as quickly as possible, governance, accountability, and internal controls are struggling to keep pace.\u00a0\u00a0<\/p>\n<p class=\"wp-block-paragraph\">The report, \u201c<a href=\"https:\/\/newsroom.avalara.com\/image\/Agents_of_Change.pdf\" rel=\"nofollow noopener\" target=\"_blank\">Agents of Change: How the Race to Deploy AI Agents is Outrunning Financial Governance<\/a>,\u201d surveyed more than 1,500 CFOs and senior finance leaders across the U.S., U.K., India, and Australia who have deployed, piloted, or actively evaluated AI agents in financial processes during the past year.\u00a0<\/p>\n<p>Key findings<\/p>\n<p class=\"wp-block-paragraph\">Pressure to show value is mounting.<\/p>\n<p>92%1\u00a0of respondents feel moderate or significant career pressure to demonstrate that AI agent investments are delivering ROI,with halfcalling that pressure significant.\u00a0<\/p>\n<p>Half say their AI agent initiatives have delivered only limited measurable ROI to date.\u00a0<\/p>\n<p>71%2\u00a0say the pressure to deploy agents is focused primarily on deployment speed.\u00a0<\/p>\n<p class=\"wp-block-paragraph\">Governance is falling behind the agentic AI rush.<\/p>\n<p>Only 7%3\u00a0say their organization prioritizes governance over speed.\u00a0<\/p>\n<p>30%4\u00a0have not updated internal controls within the last year to reflect AI agents taking or recommending actions.<\/p>\n<p>44%\u00a0are only somewhat confident they could explain an AI agent\u2019s actions to an auditor or regulator.<\/p>\n<p class=\"wp-block-paragraph\">The findings reveal a finance function caught between executive pressure to accelerate AI agent adoption and the operational reality that those AI agents need to be managed with care, particularly in tax and compliance, where decisions must withstand regulatory scrutiny.\u00a0<\/p>\n<p class=\"wp-block-paragraph\">Finance leaders are right to move quickly to capitalize on agentic AI opportunities, but speed without accountability creates new forms of risk, and speed without rethinking workflows limits ROI. The organizations that realize the greatest value from AI won\u2019t simply deploy more agents. They\u2019ll leverage agents with trusted data, governed workflows, and clear controls that enable automation with confidence.<\/p>\n<p class=\"wp-block-paragraph\">\u2013 Hugo Sarrazin, Chief Executive Officer, Avalara<\/p>\n<p>Pinpointing Accountability<\/p>\n<p class=\"wp-block-paragraph\">The research highlights questions about who is responsible for significant AI agent errors. For example, nearly one in four (23%5) say accountability for a significant AI agent error would be unclear or sit with no one, while 16%\u00a0believe the executive who approved the AI investment would ultimately be held personally accountable.\u00a0\u00a0<\/p>\n<p class=\"wp-block-paragraph\">One of the challenges is a lack of available knowledge: 76%\u00a0lack dedicated in-house expertise to understand how their AI agents work, relying on IT or vendors.\u00a0<\/p>\n<p class=\"wp-block-paragraph\">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. As AI agents gain access to financial and compliance workflows, organizations 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.<\/p>\n<p class=\"wp-block-paragraph\">\u2013 Frank Cirone, VP Commercial Strategy, Snowflake<\/p>\n<p>Finance Leaders Prioritize Trust Alongside Speed<\/p>\n<p class=\"wp-block-paragraph\">The survey makes clear that finance leaders aren\u2019t looking to slow AI adoption. They\u2019re looking to scale it responsibly. When asked what would most increase their confidence in expanding AI agents, respondents consistently prioritized capabilities that reinforce trust and accountability:<\/p>\n<p>AI agents operating within existing systems of record\u00a0(27%)<\/p>\n<p>Outputs grounded in verified tax, compliance, and financial data\u00a0(25%)<\/p>\n<p>Validation against known compliance requirements (25%)<\/p>\n<p>Vendor commitments around accuracy and accountability (24%)<\/p>\n<p>Audit trails documenting every AI action (23%)<\/p>\n<p class=\"wp-block-paragraph\">The capabilities respondents identified as most valuable were \u201caudit-ready documentation for every AI-driven action\u201d and \u201cmonitoring regulatory changes and applying updates in real time\u201d, each selected by 30%\u00a0of respondents.\u00a0<\/p>\n<p class=\"wp-block-paragraph\">AI agents are now moving into business processes that require trust, transparency, and governance by design. As enterprises scale agentic AI, the question becomes less about whether the technology can act and more about whether organizations can understand, control, and explain those actions. In finance, where workflows are auditable and outcomes carry real business consequences, governance and explainability will become essential requirements for adoption.<\/p>\n<p class=\"wp-block-paragraph\">\u2013 Jim Lundy, Founder, CEO, and Lead Analyst, Aragon Research<\/p>\n","protected":false},"excerpt":{"rendered":"Avalara have released new research revealing that while finance teams feel pressure to\u00a0 deploy AI agents as quickly&hellip;\n","protected":false},"author":2,"featured_media":113297,"comment_status":"","ping_status":"","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[6],"tags":[179,7493,24,1866],"class_list":["post-113296","post","type-post","status-publish","format-standard","has-post-thumbnail","category-agentic-ai","tag-agentic-ai","tag-agentic-artificial-intelligence","tag-ai","tag-avalara"],"_links":{"self":[{"href":"https:\/\/www.europesays.com\/ai\/wp-json\/wp\/v2\/posts\/113296","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.europesays.com\/ai\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.europesays.com\/ai\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.europesays.com\/ai\/wp-json\/wp\/v2\/users\/2"}],"replies":[{"embeddable":true,"href":"https:\/\/www.europesays.com\/ai\/wp-json\/wp\/v2\/comments?post=113296"}],"version-history":[{"count":0,"href":"https:\/\/www.europesays.com\/ai\/wp-json\/wp\/v2\/posts\/113296\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.europesays.com\/ai\/wp-json\/wp\/v2\/media\/113297"}],"wp:attachment":[{"href":"https:\/\/www.europesays.com\/ai\/wp-json\/wp\/v2\/media?parent=113296"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.europesays.com\/ai\/wp-json\/wp\/v2\/categories?post=113296"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.europesays.com\/ai\/wp-json\/wp\/v2\/tags?post=113296"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}