$100M Is Flowing Into Accounting AI. None of It Is Built for Your Firm.
Basis AI raised $100M for large accounting firms. Here is what the funding wave means for independent CPA practices and how smaller firms close the gap.
Why the $100M+ flowing into accounting AI platforms bypasses independent practices, and the three-step path smaller practices can follow to close the automation gap without enterprise budgets or IT departments.
Agentic AI in accounting refers to AI systems that autonomously execute multi-step financial processes — tax returns, audit workflows, compliance checks, document intake, and client follow-up — by coordinating multiple specialized agents rather than performing a single isolated task. Basis AI and Intapp are the enterprise-tier examples; smaller firms need the same architecture scoped to their specific workflows.
Basis AI raised $100 million in February 2026 at a $1.15 billion valuation (SiliconANGLE). The platform already serves 30% of the top 25 accounting firms. Intapp launched its own agentic AI platform for professional firms the same week (CPA Practice Advisor). Neither product was built for an independent CPA practice.
This is the central problem with the current wave of accounting AI: the capital, the talent, and the product development are all aimed at the top of the market. The firms that need automation the most, mid-size and small practices struggling with staffing shortages and margin pressure, are watching from the sidelines while their larger competitors automate faster.
The Gap in the Data
Nearly 90% of finance leaders said AI will transform the profession within two years, but only 8% felt "very well-prepared" to adopt it, and only 24 to 27% report having adequate AI-skilled talent (AICPA and CIMA, Future-ready Finance survey of 1,446 leaders).
The AICPA and CIMA published a global study in February 2026 surveying 1,446 finance and accounting leaders (AICPA and CIMA). Nearly 90% of finance leaders said AI will transform the profession within two years. Only 8% felt "very well-prepared" to adopt it. Only 24 to 27% report having adequate AI-skilled talent, IT system readiness, or regulatory preparedness.
The gap is not about awareness. Every managing partner at a mid-size firm has read the headlines about AI transforming accounting. The gap is about readiness: knowing what to implement, how to implement it, and who is going to make it work.
That readiness problem hits hardest at firms without IT departments. About one in five workers use AI nearly every day (ADP Research) — a rate that says adoption is broad but shallow, and shallow adoption is what a firm without an IT department ends up with (CPA Practice Advisor). For the other four in five, AI remains something they read about in CPA Practice Advisor, not something they use before lunch.
What Enterprise Platforms Actually Do
Basis AI builds agent-based systems that execute multi-step financial processes: tax returns, audit workflows, compliance checks. The platform combines large language models with rules-based controls and domain-specific accounting logic. Basis recently demonstrated the first AI agent to autonomously complete an end-to-end 1065 partnership tax return (CPA Practice Advisor). Intapp targets professional services firms broadly, coordinating client data, engagement management, and AI-driven insights across large organizations.
Thomson Reuters and Wolters Kluwer have each embedded agentic AI into their tax and audit platforms over the past 18 months (CPA Trendlines). These platforms work. Basis reports driving 20 to 50% efficiencies across the practices using its system (CPA Practice Advisor). The question for smaller practices is not whether the technology works. It does. The question is whether it works at your size and budget.
Not sure where AI fits in your operations?
Take the Free AI Readiness Scorecard →Why Small Firms Get Left Behind
Enterprise AI platforms are designed for scale. Basis has raised $138 million total. That funding pays for engineering teams building features for firms processing thousands of returns annually. Their go-to-market targets firms with hundreds of employees.
An independent practice faces three specific problems with this approach.
The implementation timeline is wrong. Enterprise platforms require 6-12 months of integration: mapping data flows, migrating client records, training staff, configuring workflows. A smaller firm cannot absorb that disruption during busy season, and busy season covers nearly half the year.
The scope is wrong. An independent firm does not need an autonomous 1065 agent processing thousands of returns. It needs a system that handles the bottlenecks consuming the most staff hours: document intake and classification, client follow-up for missing information, data extraction into existing tax software, and first-pass review before the partner signs off.
The talent gap is real. The AICPA/CIMA survey found only 24 to 27% of organizations report having adequate AI-skilled talent (AICPA and CIMA). For a firm without a dedicated IT person, the question is not just what to buy. It is who will make it work. The adoption gap across Canadian SMBs follows the same pattern: awareness runs far ahead of actual deployment.
What Works at Independent Practice Scale
The accounting firms pulling ahead at smaller scale are not replicating what Basis builds for the top 25. They are solving specific operational problems with AI systems scoped for their workflows.
Coordinated agents, not disconnected tools. The most common mistake is buying individual AI products: a document scanner here, a chatbot there, a data extraction tool somewhere else. Each creates its own silo. The value comes from connecting these functions into a single workflow. When a document arrives, it gets classified, the data gets extracted, the client gets notified about missing items, and the preparer gets a ready-to-review package.
A coordinated build scoped to one workflow like document intake is sized against the hours that workflow consumes today, and the assessment sets the target before any code is written. Basis reports 20 to 50% efficiencies at larger firms; the architecture is the same, the scope is what changes.
We covered why disconnected tools fail accounting firms in our guide to what Toronto accounting practices get wrong about AI__.
Scoped projects over full transformation. Start with the workflow consuming the most hours per return. For most practices, that is document intake and data extraction. The AICPA/CIMA readiness data reinforces this: a scoped project, one workflow automated well, builds internal competence without overwhelming the team.
External AI expertise instead of internal hires. An independent firm is rarely in a position to hire a Chief AI Officer. The firms that move fastest bring in external expertise to assess workflows, build initial systems, and train the team. Part-time, senior-level AI leadership without the full-time cost.
Measurable ROI within 60 days. Enterprise implementations can afford a year before measuring results. Smaller firms cannot. The right approach at this scale delivers measurable time savings within 30-60 days. For context on calculating this, see our AI ROI measurement framework.
The Two-Tier Market Is Forming Now
CPA Trendlines called 2026 the "tipping point" for agentic AI in tax and accounting (CPA Trendlines). The top 25 firms will use Basis, Intapp, and embedded platforms from Thomson Reuters and Wolters Kluwer. They have the budgets, the IT teams, and the return volume to justify enterprise infrastructure.
The remaining tens of thousands of accounting firms face a choice: find an approach that works at their scale, or watch the gap widen while the expertise shortage compounds.
The technology powering Basis AI, coordinated agents handling multi-step workflows, is not exclusive to billion-dollar platforms. The same architecture works at smaller scale when built for the specific constraints of an independent practice. The difference is in scope, implementation speed, and who guides the process.
The firms that act in 2026, while the gap is still about readiness rather than revenue impact, will have a structural advantage. The firms that wait will be competing against automated competitors with half the overhead.
The Action Path for Independent Firms
If you manage an independent practice, the path forward has three steps.
First, identify your highest-cost workflow. For most firms, this is document intake and data extraction during busy season. Calculate the hours spent and the staff cost. This becomes your baseline for measuring AI ROI. Our ROI measurement framework provides the specific calculation.
Second, evaluate scoped AI implementation, not enterprise platforms. A coordinated agent system built for your firm's specific workflows, integrated with your existing tax preparation and practice management software, costs $7,500 to $15,000 per agent for a single workflow (complex, multi-system workflows run up to $30,000), fixed price, with scope set in the AI Workflow Assessment. That is less than three months of a junior hire and delivers results within 60 days.
Third, sequence the rollout around one measurable workflow. A smaller firm does not need an enterprise platform rollout to prove value. It needs one implementation that reduces staff hours, clears a backlog, or speeds up client delivery enough to justify the next phase.
- $100M+ in accounting AI funding (Basis, Intapp) targets the top 25 firms with 6-12 month enterprise rollouts — none of it is built for independent practices.
- Only 8% of finance leaders feel "very well-prepared" for AI, and only about one in five workers use AI nearly every day (ADP Research) — the gap is expertise, not awareness.
- Scoped AI implementation for an independent firm costs $7,500 to $15,000 per agent for a single workflow (complex, multi-system workflows run up to $30,000), fixed price, with scope set in the AI Workflow Assessment and delivers measurable results within 60 days.