In the recent Controllers Council and Zip webinar, From Manual to Strategic: How AI Is Transforming Finance and Accounting Operations, finance leaders examined a reality many accounting teams now face daily: the pressure to modernize operations without compromising control, accuracy, or capacity. As organizations pursue automation initiatives at a faster pace, the discussion centered on a more consequential question. Which AI initiatives actually improve finance operations in a meaningful and sustainable way?
Moderated by Neil Brown, Executive Director of the Controllers Council, the session featured Sameer Syed, Chief Accounting Officer at Zip, and Ken Liu, Director of Accounting Operations at Huntress. Together, they explored how finance organizations are beginning to rethink operational design, month-end workflows, policy management, and reporting through the lens of agentic AI and automation.
Why Finance Teams Are Reconsidering Traditional Workflows
Sameer Syed framed the current environment as a transitional period where many teams are “trying to apply AI today to yesterday’s technology and yesterday’s workflows.” Rather than layering automation onto fragmented processes, he argued that finance leaders must reconsider how work itself is structured. The discussion repeatedly returned to the idea that AI should not simply accelerate isolated tasks. It should improve the connected process surrounding those tasks.
The operational strain placed on finance teams served as a recurring theme throughout the conversation. Syed noted that “accounting and finance individuals always feel the pressure to do more with less,” adding that AI has intensified expectations around productivity and efficiency. Yet despite growing interest in automation, polling conducted during the webinar revealed that most organizations remain in the experimentation phase with AI adoption.
Huntress’ Early Approach to AI Adoption
For Ken Liu, the shift toward AI adoption at Huntress accelerated rapidly over the past year. “A year ago, nobody on our operations team knew exactly what AI was or how to embrace it,” Liu explained. “And then all of a sudden it felt like a huge wave just came upon us.”
That abrupt transition forced accounting operations teams to evaluate how AI could realistically support lean departments already managing expanding workloads. Huntress currently supports a rapidly growing employee base with a relatively small accounting operations team, making workflow efficiency a necessity rather than a convenience. Liu described how his team began identifying repetitive operational bottlenecks that consumed hours each week but added limited strategic value.
Using AI to Reduce Repetitive Operational Work
One of the earliest use cases involved employee policy questions related to travel and expense management. Rather than relying on manual Slack responses from the AP team, Huntress implemented an AI-driven help desk capable of answering routine policy questions automatically. “A lot of time was spent on answering things that are fairly basic and fairly standard,” Liu said. The automation reduced interruptions for the accounting team while also improving response times for employees across multiple countries and time zones.
The conversation also highlighted how AI is beginning to reduce friction across accounts payable and receivables processes. Liu described how invoice coding and approvals are increasingly automated through embedded AI capabilities. “Now Zip basically handles it,” he explained, referring to invoice processing workflows that previously required manual review and coding.
The same principle extended to customer communications and employee follow-up tasks. AI tools now identify missing receipts, monitor overdue invoices, distribute account statements, and respond to repetitive documentation requests. Liu acknowledged that allowing AI to communicate externally initially required a level of trust adjustment within the team, particularly when automating outbound emails. However, he noted that repetitive, rules-based interactions have proven well suited for automation.
A Framework for Evaluating AI in Finance Operations
Throughout the discussion, Syed encouraged attendees to think about AI implementation through a two-part framework. The first involves accelerating work already being performed manually today. The second involves enabling entirely new capabilities that finance teams previously lacked the time or resources to pursue.
The second category generated some of the webinar’s most forward-looking discussion. Liu described how his team has begun building new dashboards and analytical reporting tools that previously would have remained low-priority projects because operational work consumed too much time. “Now, these days I’m doing a lot of more strategic things and building,” Liu said.
Moving Finance Teams Toward More Strategic Work
That strategic shift represents one of the more consequential implications of AI adoption in finance. Rather than eliminating the need for finance professionals, both panelists argued that AI is repositioning accountants closer to operational decision-making and business strategy. Syed explained that accounting teams are increasingly expected to engage earlier in business processes and provide broader analytical support across the organization.
The discussion eventually expanded into the future possibility of continuous close and continuous audit environments. Syed acknowledged that such concepts once sounded unrealistic even a year ago but noted that current advances in connected workflows and AI-enabled exception handling are beginning to create the foundational infrastructure necessary for those models to emerge.
Liu reflected on how dramatically accounting operations have already evolved during his tenure at Huntress. “When I first started at Huntress six years ago, I was the first and only accountant and took 45 days to close the books,” he said. “A couple of years ago, we finally got it down to five days.” The prospect of continuous close may still feel ambitious, but both panelists agreed that finance organizations are moving steadily toward more real-time operational models.
AI Adoption Begins with Practical Steps
Perhaps the clearest takeaway from the session was that AI adoption in finance does not begin with advanced engineering expertise or enterprise-scale transformation programs. Instead, it begins with identifying repetitive work, reducing unnecessary friction, and creating capacity for more analytical and strategic contributions.
As Liu summarized near the conclusion of the webinar: “If you haven’t started on AI yet, just dabble in it. Start today doing something.”
To watch the full webinar here.
ABOUT THE SPONSOR:
Zip is the world’s leading procurement orchestration platform, providing an intuitive starting point for any employee to initiate a purchase or vendor request. Zip helps businesses gain clear and timely visibility across all business spend and consolidates all the steps and tools used across finance and procurement processes. Learn more at https://ziphq.com.
