Your Client's AI Agents Could Start a Multi-Country Tax Fight

Usage-based and hybrid pricing models are changing how B2B companies generate revenue — and creating new headaches for the finance teams behind them.

Tabs co-founder Rebecca Schwartz and PwC Partner Amit Dhir sat down to unpack exactly what that means in practice: how pricing model decisions ripple into revenue recognition, forecasting, and financial ops — and what it takes to scale without piling on manual work.

Watch the on-demand recording to get practical frameworks, real-world examples, and a clear path to operationalizing usage-based revenue — including a forward-looking take on how AI will reshape financial workflows. If your team is navigating pricing complexity heading into the back half of the year, this is worth an hour.

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Intuit Adds AI Chat — Ask Books Anything

Summary: It lets you type a plain-English question like "why did margin drop in Q3" inside QuickBooks Online Advanced or Enterprise Suite and get an answer traced back to the vendor or transaction behind it, instead of you building a pivot table. Why it matters: For any client running multiple entities, it replaces a manual variance hunt across separate reports with one typed question — real time savings if the citations actually hold up. Catch: Intuit's own team is the only one who's tested this so far, and "traces back to specific accounts" means nothing until you've watched it correctly flag a real vendor on a messy general ledger. Unknowns: Intuit hasn't published a standalone price for Intelligence Chat, and there's no detail yet on what happens when it gets an answer wrong — pin both down on a demo call before you put a client's numbers in front of it. My take: This is worth ten minutes of your time this week — QBOA already sits on desks at three-person firms, and if the citations hold up even half the time, it beats teaching a client to read their own P&L. Just don't hand it a client-facing report until you've kicked the tires yourself. [Read more →]

Fully Integrated Firms See More AI Wins — Certinia's 2026 Global Service Dynamics Report found professional-services firms running a single connected system report AI success far more often than those with fragmented tech stacks. Why it matters: if your AI tools don't share data across practice management, billing, and workpapers, integration — not more AI spend — may be the bigger lever for actually seeing results. [Read more →]

Most Finance Teams Can't Measure AI ROI — Protiviti's 2026 Global Finance Trends Survey found AI use in financial forecasting jumped from 58% to 76% year-over-year, yet only 35% of finance organizations say they can actually measure whether it's paying off. Why it matters: assuming your clients are mid-size or larger, this is your opening to insist on a defined KPI before they sign off on another AI subscription, though the survey skews toward large finance departments rather than three-person shops. [Read more →]

Middle Market Confident, AI Barely Moves Needle — CliftonLarsonAllen's Heartbeat Index of 722 clients found 72% of middle-market leaders optimistic about the economy, while fewer than half report any real efficiency gain from AI/tech investments so far. Why it matters: if a client asks whether they're falling behind, this gives you real numbers to recommend one narrow pilot instead of a full rollout, though the sample is CLA's own advisory client base, not a neutral cross-section, and the survey doesn't isolate AI's effect from general tech spend. [Read more →]

Finance Pros Aren't Scared of AI Layoffs — An informal CFO Dive LinkedIn poll of just 26 finance executives found more respondents pointing to higher productivity than to job cuts as AI's biggest workforce impact, running counter to the broader public's anxiety about AI replacing workers. Why it matters: it's a useful line to raise if a client brings up AI layoff fears in a planning meeting, though with only 26 respondents this is closer to a straw poll than data — don't repeat the percentage as if it means anything statistically. [Read more →]

Every sales leader knows the feeling. You walk into a pipeline review with a number you believe in, and twenty minutes later, you're defending every line item to a CEO who just wants to know what's actually going to close.

HubSpot Sales Hub ends that conversation. Every deal, every rep's activity, and every buyer signal are all in one place and updated automatically. So your forecast is built on what's actually happening. And when you present that number, you can stand behind it.

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Before you turn Intuit Intelligence Chat loose on a real client, run it against last quarter's numbers where you already know the answer. If it can't correctly explain a variance you've already diagnosed by hand, it's not ready for a client meeting yet. [Read more →]

Tax Exposure: AI Agents Are Becoming a Transfer-Pricing Problem — Bloomberg Tax reports that multinationals sharing proprietary AI agents across subsidiaries are running into transfer-pricing disputes, because no IRS or international standard yet exists for valuing that internal use. Transfer-pricing specialists at Grant Thornton, PwC, Deloitte, and Mayer Brown quoted in the piece frame the core question as whether a shared agent counts as a service (lower-taxed) or an IP license (higher-taxed) — and say that distinction often turns on something as narrow as whether a subsidiary can retrain or recode the model, not just use it. One attorney points to 2025 Treasury cloud-computing regulations as a possible stopgap framework in the absence of AI-specific guidance. Why it matters: if a client operates in more than one country and has any team touching AI agents across entities, ask now whether anyone documented who built the agent, who paid for it, and who's allowed to change it — without that paper trail, multiple countries can each claim the agent's value was created on their side of the border. [Read more →]

AI Infrastructure: Thomson Reuters Builds Its Own Model, Doesn't Retire the Others — Thomson Reuters built its own AI model, called Thomson, on an open-source base for $40 million to reduce reliance on third-party frontier models across its legal and tax products. It's launching first inside CoCounsel Legal, which stays multi-model — Thomson handles some tasks, Anthropic and OpenAI's models still handle others. Why it matters: if your firm uses Checkpoint, don't assume this model is powering your tax research yet — Thomson Reuters hasn't said when (or how fully) it reaches tax-specific tools, and even in legal products where it has launched, it's supplementing rather than replacing the models you may already be relying on. [Read more →]

Audit Automation: Andera and RSM US Partner on AI Control Testing — Andera and RSM US announced a partnership to build an AI-enabled control-testing platform for internal audit, with RSM saying it will cut manual testing time and strengthen documentation. Why it matters: if you compete with RSM for audit clients, expect AI-driven control testing to become the baseline a prospect expects within a year or two — Andera's tech already has Fortune 500 clients, so the open question is how well it performs inside RSM's workflow, not whether it works at all. [Read more →]

Every tool this week promises to save you time, and not one of them tells you what happens when it's wrong. Test everything on last quarter's numbers before you trust it on next quarter's.

—Alex

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