Capterra's 2026 Accounting Software Trends survey of 500 accounting managers just confirmed what we hear every week from accounting firms: AI is no longer a trend to watch — it's the operating baseline. More than half of accounting professionals now use AI within their core software stack.
That's a milestone worth acknowledging. But buried inside the same report is a finding that should give every payroll-focused accounting firm pause: 43% of accounting teams are still running payroll manually, at least some of the time — making it the fourth most manual process in the profession, behind only financial reporting, accounts payable/receivable, and billing.
43% of accounting professionals still manage payroll manually at least some of the time — despite widespread AI adoption across the rest of their stack. Source: Capterra Accounting Software Trends Survey 2026, n=500
Think about that for a moment. In a profession actively embracing AI for fraud detection, invoicing, and predictive analytics, payroll — the highest-stakes, highest-frequency, most compliance-sensitive workflow an accounting firm manages — remains stubbornly manual for nearly half of practitioners.
This is the payroll paradox. And it's not a technology problem. It's an infrastructure problem.
The Capterra research is clear: 89% of accounting professionals using AI report positive ROI, with gains in productivity, error reduction, and faster reconciliation. AI is delivering. The firms benefiting most aren't necessarily the ones with the most AI — they're the ones with workflows structured to absorb it.
Payroll is a workflow built on deadlines, remittances, and reconciliation — exactly the kind of repeatable, rules-driven, high-consequence work where AI creates the most value. But that value evaporates when the underlying payroll data lives in a different system than time and attendance, which lives in a different system than HR records. You can't automate a workflow that doesn't exist in one place.
This is why generic accounting software with AI bolt-ons isn't solving the payroll problem. The AI is only as useful as the data architecture beneath it.
The Capterra data lands another uncomfortable truth: 73% of accounting managers have struggled to retain staff in the last two years, and payroll specialists rank among the three hardest roles to fill — tied with staff accountants and behind only financial analysts and specialized accountants like tax professionals.
24% of accounting firms say payroll specialists are among the hardest roles to source — a direct signal that payroll expertise is becoming a competitive asset, not a commodity. Source: Capterra Accounting Software Trends Survey 2026, n=500
The research frames this as an HR challenge. We'd argue it's a platform challenge in disguise. When payroll runs on fragmented, manual-heavy systems, it demands more specialist hours per client, increases burnout exposure, and makes it nearly impossible to scale without proportional headcount growth. The firms that solve the infrastructure problem are the ones that get more from the talented payroll professionals they already have.
Capterra's own conclusion aligns: "AI changes who firms need, not how many." Purpose-built payroll infrastructure amplifies your specialists — it doesn't replace them.
When asked what challenges they expect to face in the next 12 months, accounting managers ranked "determining how to leverage AI" tied at the top alongside budgeting and forecasting — ahead of cash flow management, new software implementation, and financial reporting accuracy.
Notably, 33% specifically flagged managing payroll and employee benefits as a top anticipated challenge. These aren't concerns about whether AI will work. They're concerns about choosing the right tools and trusting them with sensitive, high-stakes workflows.
That trust problem is compounded by a real security gap in the data: fewer than half of firms using AI have specific guidelines for entering employee and payroll data into AI tools. In a world where 52% of accounting professionals have experienced a financial data breach, that's not a minor compliance footnote — it's a liability.
At Nooma, this is a design constraint, not an afterthought. Compliance guardrails, audit-ready records, and default-secure policy settings are foundational — because payroll data is some of the most sensitive information a firm touches on behalf of its clients.
We built Nooma for the accounting expert who manages payroll on behalf of clients — not for the business owner who runs payroll once a month. That distinction shapes every architectural decision we've made.
Payroll, Time & Attendance, and HR live in one unified platform. AI automates deadlines, remittances, and year-round reconciliation — not as features layered onto a general accounting system, but as the native intelligence of a platform designed around payroll workflows from day one. The accounting firm and their client see the same data, in real time, with full auditability.
The Capterra research validates something we've believed since founding Nooma: the firms that will win the next decade of payroll aren't the ones that adopt the most AI. They're the ones with the infrastructure that makes AI actually work — unified, compliant, and built for the experts who depend on it.
The payroll paradox is solvable. But it requires purpose-built infrastructure, not general-purpose tools with AI features stacked on top.
Nooma — Payroll, Time & Attendance, and HR, unified for accounting firms and their clients.