Modus, Current, or Independent: The Three AI Models Reshaping Accounting Firms

A client introduction call — a new 22-person company, eight-figure revenue, fast growth. They've been using an AI-backed accounting firm for six months. Their prior CPA, a two-partner shop, couldn't match the turnaround time. Not on pricing. On speed and advisory depth.

That story is playing out across the profession. And in the first two weeks of June 2026, two major AI-backed accounting models made moves that require every independent firm owner to understand their position.

Model 1: Modus — AI Infrastructure for an Ownership Stake

Modus raised $85 million in April 2026, led by Lightspeed, to do one thing: acquire ownership stakes in accounting firms and give them shared AI infrastructure in return.

The pitch is straightforward. Modus CEO Arush Jain (formerly at Palantir) projects that top-200 accounting firm partners who join Modus will double their organic growth rate. The firm handles the AI stack — the tools, the integrations, the maintenance. Partners keep running the client relationships.

The tradeoff is explicit: Modus takes an ownership position. This is not a vendor relationship. It's a structural change to who owns your firm.

For the right firm, this makes sense. If you've been reluctant to invest in AI infrastructure because of cost, complexity, or uncertainty about which tools will survive, Modus removes that problem — at the cost of equity.

Model 2: Current — Federated AI with Retained Equity

On June 2, 2026, Crete Professionals Alliance rebranded to Current. This is not a cosmetic change.

Current was already a Top 100 firm — ranked #28, with $428 million in revenue, 228 partners, and 1,800-plus staff. The rebrand came alongside new backing from Thrive Holdings and an expanded OpenAI partnership, with $500 million committed to acquiring independent CPA firms.

The key structural difference from Modus: acquired firms retain their own branding, their own leadership team, and their own equity stake. Current is building a federated AI infrastructure — shared technology, independent operations.

The results are already measurable. Current processed 7,000 tax returns in the spring 2026 season with a 31% reduction in preparation time and 98% accuracy. CEO Steve Stagner called it directly: "AI has created the opportunity for local firms to compete with large incumbents."

For firm owners who want AI infrastructure without surrendering control of the firm, Current is the middle path. The tradeoff is different from Modus — you're joining a network with shared technology governance, not selling to a platform — but you're still accepting outside ownership of some portion of the equity equation.

Model 3: Independent — Build the Stack, Keep the Firm

The third model is the one most accounting firm owners are currently living in: stay independent and build AI infrastructure yourself. This path has gotten significantly more viable in the past 18 months.

The accounting AI stack is no longer theoretical. As of June 2026, the tools are production-grade and used by named firms at scale:

Basis AI ($100M Series B, $1.15B valuation) handles end-to-end partnership tax workbooks. Thirty percent of the top 25 accounting firms are using it. For a 15-person firm, Basis gives you partnership tax AI that mid-market clients already expect.

WK CCH Axcess achieved 20-30% manual task reduction across production workflows (not pilots). Adoption in accounting firms went from 9% to 41% in one year. The early movers are a full year ahead in workflow efficiency.

Ramp Stack launched June 3. Tyler Otto at Specialized Accounting — 15 people — cut his monthly close time by 50% on some clients. No prompting required. The system learns from corrections and builds firm-specific SOPs.

Firm360's Claude Connector lets partners ask plain-language questions about WIP, realization rates, and client profitability. Setup takes minutes.

Karbon Kai automates email triage, period close checks, and analytics. Their 2026 data shows only 21% of accounting firms have formal AI governance policies — firms with documented AI deployment are already differentiating.

The independent path requires more work than either consolidation model. You're assembling and maintaining the stack yourself. But you keep all the equity, all the client relationships, and all the flexibility to exit, merge, or sell on your own terms later — with a demonstrated AI track record that increases your valuation rather than diluting it.

The Decision Framework

Three genuine questions to answer before deciding:

1. How much time do you have? The Wolters Kluwer data is clear: firms that adopted AI in 2024 are a full year ahead of firms evaluating in June 2026. If you've been deferring the infrastructure decision, the consolidation models (Modus, Current) accelerate the clock without requiring you to manage the stack. The independent path can catch up, but only if you start now.

2. What's your exit plan? If you're planning to sell or merge in the next five years, the calculus changes. An independent firm with documented AI results and a measurable efficiency track record commands a better valuation than one without. Joining a consolidation model now may simplify operations — or it may lock you into a structure that limits your eventual exit options.

3. What do your clients already expect? PwC's 2026 AI Performance Study found that 74% of AI value accrues to the top 20% of adopters — specifically because they redesigned workflows rather than overlaying AI on existing processes. If your clients are mid-market companies with sophisticated expectations, the question isn't whether to adopt AI infrastructure. It's which structure gives you the fastest path to demonstrable results.

The Only Wrong Answer

The wrong answer in 2026 is having no answer. Modus and Current are both making explicit bets that independent accounting firms will struggle to build and maintain AI infrastructure on their own.

They may be right for some firms. But the independent path is viable for firms willing to be deliberate about it. The tools are production-ready. The costs are manageable. The competitive disadvantage of waiting is real and compounding.

Pick a model. Document your AI deployment. Build the evidence base before someone else decides your options for you.

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