As the UAE prepares for mandatory e-invoicing, finance operations teams face a critical shift. The next phase of automation won't be about processing standard invoices faster - it's about tackling the exceptions that still consume most of the team's time and budget, according to UiPath's SVP finance Ionut Valentin Sas.
Exception handling remains the missing link
While straight-through processing has become standard, automation breaks down when invoices don't match purchase orders, need multiple approvals, or have missing data. "The reality is that processing a standard invoice has become relatively straightforward. The real challenge has always been the exceptions," Sas said. Those exceptions often move outside structured workflows into emails and spreadsheets, forcing finance teams to manually investigate, coordinate with procurement, and chase approvals.
The hidden cost of being 'almost automated'
Partial automation can create a false sense of digital maturity. "'Almost automated' often means you've automated the lowest-value work while leaving your people with the most complex and time-consuming tasks," Sas said. Delayed approvals lead to missed early-payment discounts, weaker cash management, and prolonged supplier disputes. Governance also suffers when work disappears into emails and spreadsheets, making it harder to spot bottlenecks or financial risk.
AI moves from detection to decision support
Sas believes AI for Finance is moving beyond spotting invoice mismatches to actively supporting decisions. AI can now gather supporting documents, analyze past resolutions, recommend actions, draft supplier communications, and route cases to the right people. "The biggest shift is that AI can now assist with the work that follows identification," he said. The goal isn't to replace human judgment but to accelerate investigations while keeping significant financial decisions governed and transparent.
Traditional metrics like processing time and cost per invoice still matter, but Sas argues CFOs should measure business outcomes: how quickly exceptions resolve, how predictable cash flow becomes, whether working capital improves, and if finance professionals are spending more time on commercial decisions rather than transaction processing.
Why this matters for Operations
For operations teams, AI for Operations will mean a shift from reactive firefighting to proactive management. Sas expects the AP function to become far more proactive, with routine transactions processing autonomously and AI resolving today's manual exceptions. That frees up finance professionals to focus on supplier performance, spending analysis, and working capital optimization. "Ultimately, I don't see AI replacing finance professionals. I see it allowing finance teams to operate at a much higher level, using their expertise to guide the business while routine operational work happens increasingly in the background under appropriate governance," Sas said.
Your membership also unlocks:
