3 things to know this week
By the numbers
Lead story · Money & Rules
The SEC Just Closed Comments on Ending Quarterly Reporting. What Controllers Need to Know.
On May 5, SEC Chairman Paul Atkins proposed optional semiannual reporting: companies could file one Form 10-S covering their first six months plus one annual 10-K, replacing three 10-Qs. The comment period closed July 6 after 60 days. SIFMA, Grant Thornton, and dozens of others responded — and the concerns weren't about the calendar. They were about the close.
Grant Thornton's comment letter flagged the absence of an assurance framework for quarterly earnings releases that semiannual filers would still be expected to provide voluntarily. That gap matters: if a company drops quarterly filings but still runs earnings calls and publishes releases, investors get numbers that are not subject to auditor review — and the auditor's involvement timing gets scrambled. PwC's audit committee memo raised a parallel issue: how DC&P certifications work for information that is furnished but not filed.
A final rule is unlikely before mid-2027. Calendar-year companies could first elect semiannual reporting for fiscal year 2028. If adopted, the compliance cost reduction is real — two fewer interim filings per year — but ICFR testing frequency, audit committee charter language, and trading-window policies all need rethinking.
Microsoft Rewired Copilot in Excel — Live ERP Data, Finance Skills, and a Partner Marketplace
Microsoft's June 26 update gave Copilot in Excel three new capabilities it previously lacked. First, reusable finance "skills": a controller can show Copilot a workflow once — say, the steps for a month-end variance commentary — save it as a skill, and have the same structured output on demand every close. Second, live ERP connectors to SAP, Dynamics 365 Finance, Workday Financial Management, and QuickBooks Online, letting a user pull AP aging or cash-flow data with a plain-language prompt without building Power Query connections. Third, a partner data marketplace: CB Insights, FactSet, Morningstar, PitchBook, and S&P Global are now callable from inside the spreadsheet.
Microsoft said its own finance organization uses Copilot across FP&A, accounting, tax, compliance, and treasury — and the features were pressure-tested internally before release. The move comes as Workday and other ERP vendors are building similar natural-language layers. The question for finance teams is not whether this category of tooling wins; it is which data flows to trust it with first.
The White House Is About to Formalize How Frontier AI Gets Released — Here's What That Means
Executive Order 14409, signed June 2, established the legal skeleton: a voluntary framework under which developers of "covered frontier models" give the federal government up to 30 days of access before release to other trusted partners, while the NSA develops classified benchmarks to determine which models cross the threshold. By August 1, agencies must have that framework in place.
The Financial Times reported last week that the administration is in advanced talks with OpenAI, Anthropic, and Google on formal standards — an announcement could come any day. The practical effect is already visible: GPT-5.6 launched to roughly 20 government-vetted organizations before broader access, and Anthropic's Fable 5 spent 19 days under Commerce Department export controls after a jailbreak was reported before access was restored July 1. Pre-release government review is operational; the framework formalizes what is already happening on a deal-by-deal basis.
CFOs Are Spending on AI. The Returns Are Not Keeping Up.
CFO Dive's July 9 deep-dive — the first of a two-part series — captures the paradox cleanly: 74% of finance frontline employees use AI at least several times a week, and 42% report saving a full workday or more per week. But BCG's finding is that the time savings is not necessarily yielding value. The productivity surplus is real; the business impact is not. KPMG's 2026 Global AI in Finance report found active AI use in finance more than doubled from 2024 to 2026, rising from 30% to approximately 75%, while data quality remains the most cited barrier and the most cited opportunity.
One CFO offered a counter-example. Pipedrive's CFO Regi Vengalil told CFO Dive his head of accounting built a close-management tool from scratch using AI. "My head of tax, my head of treasury can start taking it into their own hands," Vengalil said. The pattern in the data: organizations redesigning workflows before selecting technology report the strongest returns. Bolt-ons report the weakest.
AI, demystified
The Microsoft Copilot-in-Excel update — pulling live data from SAP or Workday at query time — is a form of what AI practitioners call RAG: Retrieval-Augmented Generation. The model doesn't know your ledger. It retrieves what it needs, then generates an answer. Here's the three-step mechanic.
The finance analogy: RAG is how you'd brief a smart new analyst. You don't hand them a copy of your brain; you hand them the specific report, the prior-period actuals, and the budget file. They work from those documents and answer your question. The difference from a standard LLM: without retrieval, the analyst is working from memory — and memory goes stale. With retrieval, they're reading the live file.
The risk to remember: RAG is only as accurate as what you retrieve. If the ERP connection pulls from a table that was last refreshed at 11 p.m. and your close is running at 7 a.m., the AI is confidently working from yesterday's data. Freshness, permissions, and source-of-record clarity are the governance variables that determine whether RAG helps or misleads.
Hype check
"AI can cut your month-end close in half."
The evidence base for dramatic close-cycle compression is real but narrow. Some organizations running AI-assisted reconciliation and automated journal entry posting have reduced specific task times significantly. The CPA Practice Advisor piece from July 1 makes the mechanism clear: AI deployed after a properly designed workflow can compress it. AI deployed into a messy workflow can replicate its errors across multiple periods before anyone notices — faster and at greater scale.
The KPMG data is instructive: 36% of organizations cite data quality as their greatest AI vulnerability. If your close relies on 50 entities with fragmented charts of accounts — like the controller profiled in the Journal of Accountancy in April — the AI's speed advantage is blocked by the mapping problem. The "half the time" claim is achievable for teams with clean, well-governed data and redesigned workflows. It is marketing for everyone else.
Sources: CPA Practice Advisor, Jul 1 · Journal of Accountancy, Apr 2026
Do this week · Prompt of the week
- 15 minRead the SEC's semiannual reporting fact sheet and flag one ICFR implication specific to your organization — even if you're private. The governance questions it raises apply broadly.
- 20 minPull up Copilot in Excel (if your org has M365 Copilot) and try one natural-language finance query. Document what it got right, what it hallucinated, and what data it couldn't reach. That three-point log is your governance baseline.
- 10 minAsk your largest AI software vendor: "Is your next major model update subject to government review under EO 14409?" If they don't know, that's your answer about their AI risk posture.
Number of the week
of organizations have real-time visibility into the cost of running AI at scale — meaning nearly three in four are flying blind on their AI spend, even as budgets accelerate
CFO Dive · Jun 25, 2026
Off the record
The Finance AI Gap That Nobody Is Measuring: The Cost of What Didn't Get Fixed
Every AI ROI conversation in finance starts from the same place: how much time did we save? It's the wrong starting point. The BCG data — 42% of finance employees saving a full workday weekly — ought to translate into something measurable at the business level. It mostly isn't, and the reason is rarely the technology.
What gets measured is hours recovered. What rarely gets measured is what those hours would have found if they had gone into the analysis the team didn't have time for before. The late reconciling item that became a material adjustment in Q4. The budget assumption that nobody stress-tested because the close took too long. The vendor contract that renewed on auto-pilot for three years. AI is supposed to buy the team time to catch those things. Most teams spend the time on the next close.
Personality of the week
Kevina Purmanund joined the FEI podcast this month at the FEI + MFM 2026 Financial Leaders Forum in San Antonio to talk about something few finance leaders are willing to say directly: she was afraid AI would replace her job. That candor makes what she built afterward more interesting than any "we deployed AI" press release.
Purmanund describes moving from that early anxiety to treating AI as a competitive edge — for herself and for the team she leads. The 1826 Group is a boutique advisory firm, which means there is no IT department to wait for, no change-management budget, and no vendor contract to hide behind. The AI adoption she describes is practitioner-built, close to the work, and directly tied to client outcomes. That's the pattern the BCG data says produces the strongest returns.
Until next Monday — keep a name next to every number.