This was my second year at the Finance and Accounting Technology Expo, and the difference from last year was dramatic. In 2024, many tools were early, overstated their AI capabilities, or were still figuring out where they fit. This year, the floor felt fully formed. The automation is real, the claims match what teams are seeing, and every major category is now crowded.
That maturity is both an advantage and a challenge. The tools work, but they also look increasingly similar. Demos blur together, accuracy numbers repeat, and integration lists overlap. It’s no longer obvious why one vendor costs twice as much as another or what truly sets them apart.
So the real question for CFOs isn’t whether the technology works — it does. The question is whether it will work in your environment. And that depends on conditions vendors rarely surface in demos. This edition breaks down the patterns behind the crowded market and then looks at the prerequisites that actually determine success.
⚡ TL;DR
Finance tech has matured in a real way: the automation works and results are predictable
Five core categories dominate, but most tools inside each look almost identical
AI agents are moving from demos to actual deployment
Success still depends on prerequisites that vendors rarely discuss
Paid section: When AP, AR, FP&A, close, and spend tools actually deliver ROI
What 100+ Vendors at FATE Reveal About the Market
More than a hundred finance-tech vendors came together at FATE, and the landscape has started to follow predictable patterns. You can finally see what’s maturing, what’s converging, and where differentiation has all but disappeared.
How the Market Clusters
Across the floor, six categories dominated:
AP Automation: Examples include BILL, Tipalti, Yooz, Hyperbots
Spend and Expense: Examples include Ramp, Brex, Navan, Expensify
AR Automation: Examples include Versapay, HighRadius, Billtrust
Month-End Close: Examples include FloQast, Trintech, NetSuite, Campfire
FP&A and Planning: Examples include Anaplan, Planful, Cube, Datarails
ERP and GL: Examples include SAP, NetSuite, Intuit, Campfire
Two patterns stand out. AP automation remains the most crowded category. And many vendors now operate across multiple categories, signaling a shift toward platform strategies rather than point solutions. Bill.com spans AP, AR, spend, and ERP. HighRadius shows up in AP, AR, and close. SAP tries to play in almost every category.
This expansion introduces a decision point: whether you want a broad platform that touches everything or a specialist that does one workflow exceptionally well.
The Similarity Problem
Once you look inside each category, the similarities become even more obvious.
AP tools promise high OCR accuracy, automated coding, routing, matching, and fraud checks.
Spend tools offer cards with controls, receipt matching, policy enforcement, and vendor analytics.
FP&A platforms highlight forecasting, scenario modeling, driver-based plans, and chat-driven querying.
The overlap isn’t superficial. Many vendors brag about identical accuracy numbers, identical implementation timelines, and nearly identical integration partners. When fifteen AP tools all claim 95 percent coding accuracy, you’re no longer choosing features. You’re choosing implementation quality, customer support, and how well the vendor understands your specific workflows.
The Pricing Models
Three pricing models dominated the conversation, and each creates a different financial profile.
Per-seat: Simple, predictable, and familiar. Works well for stable teams. Most ERP and FP&A tools are here.
Per-transaction: You pay per invoice, expense, or payment. Great for low volume, less attractive as you scale. Popular in AP and AR automation.
Savings-based: You pay a percentage of identified savings. Sounds aligned with value, but it’s hard to validate. Vendors count everything from reduced FTE hours to avoided fraud and early-pay discounts. It’s rarely clear which savings come from the tool versus improved processes.
AI Agents Enter the Picture
The biggest shift to me was the emergence of agents that complete entire workflows.
Traditional AI assistants help you work faster. Agents actually do the work.
Examples from the conference included:
Bill’s W-9 Agent, which collects vendor documents and enters data autonomously
Bill’s Receipt Agent, which reconciles and codes transactions at scale
Ramp’s Policy Agent, which reviews transactions and recommends actions
Hyperbots’ agent suite handling invoices, accruals, tax checks, and payments
FloQast agents managing approvals and answering policy questions
Campfire’s accounting model powering reconciliations across systems
Most of these agents run on deterministic logic rather than generative AI. That’s essential for finance, because it ensures consistent, audit-ready outputs. The agent model shifts how teams think about capacity, because the work genuinely moves off someone’s plate.
What This Structure Means
The tools work. That part is settled. What’s less obvious is which tool will work for your environment. Platform depth, pricing models, implementation approach, and data requirements now matter far more than the feature list.
The maturing market is a positive development. It means CFOs can confidently adopt automation that used to feel experimental. But it also means the buying process has become more complex, because differentiation now lives in the details: the quality of your data, the consistency of your processes, and the scale of your transactions.
If you walk into demos expecting the software to show you whether it’s the right fit, you’ll miss what actually matters. Demos reflect perfect conditions. Real results depend on the environment the software lands in. The question isn’t whether the automation works — it’s whether it will work for you.
In the subscriber-only section, I break down the conditions that determine success: when AP automation actually pays off, when FP&A forecasting becomes meaningful, when close automation makes a real impact, and when spend management delivers. I’m also sharing a decision-making questionnaire to help you assess which workflows in your own team are truly ready for automation. These factors matter far more than any feature list.
Closing Thoughts
The market has reached a point where the technology is no longer the uncertainty. The question now is how well your own environment supports it. Clean data, stable processes, and clear ownership matter far more than any single feature on a demo screen.
As automation becomes a standard part of the finance stack, the teams that get the most value won’t be the ones that pick the flashiest tool. They’ll be the ones that understand the conditions that make these systems work. That’s where the real advantage is, and it’s where finance leaders can set the tone for 2026.
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Until next Tuesday, keep balancing!
Anna Tiomina
AI-Powered CFO