Agentic AI at Heart of Zip's Accounting Solution

Zip has unveiled automation for procure-to-pay processes, offering AI agents designed to handle accounting workflows from purchase requests through to payment completion.

The company, which orchestrates more than US$500bn in spend for hundreds of companies, is extending its automation capabilities to finance and accounting teams.

Zip's clients include Anthropic, AMD, Discover, Dollar Tree, OpenAI and T-Mobile.

The CFO trust gap

According to Deloitte's Q4 2025 CFO Signals Survey, 87% of CFOs consider AI necessary for their 2026 operations. However, according to a Wakefield Research study, only 14% trust the technology to produce correct accounting data without supervision.

Finance operates on different success metrics compared to other industries. In most fields, 80% automation or 95% accuracy is considered acceptable. For a CFO, 80% automation means manual book closing remains necessary. Accuracy of 95% is insufficient for financial reporting standards.

AI lacks the contextual understanding required for financial reporting, with current implementations function as supervised technology. Teams must audit AI work and manage exceptions, and, without complete reliability, this is not automation but an expensive version of existing processes.

Most AI accounting tools target routine and high-volume transactions – struggling with complex scenarios such as mismatched purchase orders, multi-entity tax calculations or exception routing. When systems cannot handle line by line coding across hundreds of entries, reconciliation processes fail.

This creates openings for fraud and erodes trust between CFOs, CEOs and boards.

The stakes of accuracy

A miscoded purchase order creates errors across subsequent invoices. Late payments can result in immediate suspension of services.

Unapproved expenses that go unaccrued compromise financial statement integrity and a single incorrect invoice casts doubt on the entire system.

"The CFO trust problem with AI isn't a model problem, it's a data problem," says Rujul Zaparde, Co-Founder and CEO of Zip. "Most AI accounting tools get parachuted in at the invoice stage, working blind.

"Zip was built as a procurement platform first, which means that by the time an invoice arrives, we already have the purchase request, the approved purchase order, the contract terms, the budget position and the supplier history. That 360-degree context is what lets our AI get it right when 95% isn't good enough."

Zip was built as a procurement system before becoming an accounting tool. By the time an invoice arrives, Zip already has the purchase request, approved purchase order, contract terms, budget position and supplier history.

This context differentiates the system from tools that begin at the invoice stage.

How the system works

Zip's AI automation for procure-to-pay handles workflows from purchase request to payment across seven capabilities.

• Real-time budget enforcement automatically matches requests to budgets, alerts teams before consumption and syncs actuals to the ERP at close. Purchase order balance alerts catch overruns before commitment rather than during reconciliation review.
• Intake AI generates purchase orders and processes change orders within Zip's workflow. Purchasing data is structured, approved and policy-compliant before vendors submit invoices.
• The AP Inbox Agent monitors incoming vendor mail and extracts invoices. The invoice coding agent codes across general ledger, department and cost centre using contract and purchase order context already in Zip. It codes against the actual approved transaction instead of relying only on pattern matching.
• Invoice review and contract compliance functionality compares each invoice against historical patterns. The system flags pricing changes, duplicate charges and errors before reaching an approver. The contract compliance agent checks every invoice against underlying agreement terms.
• Exception automation places problem invoices on hold, routes them to the appropriate person with a specific task and releases them when complete. What teams typically manage in spreadsheets with more than 100 held invoices becomes a self-clearing workflow.
• Payment Risk AI runs risk rules on every invoice before disbursement. Bank account validation catches misdirected payments at the point of payment.
• The capitalisation agent classifies capital versus operating expenses automatically and handles prepaid amortisation. A tax and VAT agent handles multi jurisdiction compliance. Approved transactions sync to the accounting system in real time.

Early deployment results

According to Zip, users code invoices 40% faster, approve them 51% faster and process three times more per month without adding headcount.

Zip's payment risk AI has flagged more than US$200m in risky invoices throughout customer bases. Anomalies are nearly 15 times more likely to be fraudulent when surfaced. This includes vendor emails timed to arrive before invoices, manufactured to create urgency and override judgement.

Unifi Aviation is among the first enterprise customers to deploy the full suite. The company is North America's largest aviation services provider with more than 40,000 employees across more than 200 airports.

"Your financial statements are only going to be as accurate as your purchase order details and how you match invoices against them, and at our scale, with thousands of invoices across dozens of entities, there's no margin for that to go wrong," says Mark Hlavek, VP Controller at Unifi Aviation.

"Within six months of deploying Zip, we are coding a higher volume of invoices with 96% faster cycle times, with the same size team. We didn't need to choose between speed or accuracy, Zip allowed us to do both at once."

Gartner recently named Zip a Visionary in its Magic Quadrant for Source-to-Pay. The platform was built to handle the accounting complexity that enterprise finance teams face each month.

AI Automation for Procure-to-Pay is available now.