Month End Close

The AI Trust Problem Accounting Can’t Afford to Ignore

Earmark Team · May 15, 2026 ·

Here’s a thought experiment. You ask ChatGPT to write you a research summary. It comes back 70% accurate. You tweak a few paragraphs, fix some facts, and you’re good to go. Now imagine that same 70% accuracy rate applied to your general ledger, audit workpapers, or financial statements.

As Mark Hickman, Sage’s Managing Director for North America, puts it bluntly, “You go to jail for that.”

That line from Episode 34 of The Unofficial Sage Intacct Podcast cuts straight to a tension every CFO, controller, and accounting professional grappling with AI needs to understand. The technology promising the biggest efficiency gains in a generation operates in a profession where approximate answers are a liability.

Hosts Doug Lewis, Matt Lescault, and Emily Madere sat down with Mark for their second annual Sage Future conference preview episode. Mark oversees Sage’s largest and fastest-growing region. He’s watched the Intacct acquisition grow more than 10x over the past 11 years. He’s in front of customers and partners constantly.

When he talks about what finance leaders say about AI, it’s field intelligence from someone who’s been in tech for nearly 25 years and has seen every major shift from dial-up internet to cloud computing.

He argues that while every corner of technology races to bolt on AI capabilities, accounting demands a fundamentally different approach built on trust, traceability, and human control. And the companies best positioned to deliver that are the established platforms sitting on vast reservoirs of trusted data.

Accounting AI Can’t Be a Black Box

Strip away all the marketing noise around artificial intelligence and you land on a simple question: where did that number come from?

In most industries, that question is nice-to-have. In accounting, it’s everything. And it’s why Mark frames Sage’s entire AI strategy around three pillars: trust, control, and accountability.

“When you type into ChatGPT, write me an essay on this or write me a paper on this, it can be 70% right and you can tweak it,” Mark explains. “You can’t be 70% right in accounting.”

Trust means AI outputs can’t disappear into a black box. Sage built what Mark calls a “trust label.” It’s a mechanism that lets users click into any AI-generated output and trace exactly where the data came from and how AI reached the conclusion. Think of it as an audit trail for the AI itself.
Control means humans stay in charge. “Accounting is different,” Mark emphasizes. “We can’t just have AI running everything behind the scenes. We need humans to control that AI and deliver what they need from those outputs.” The AI changes day-to-day workflows, but it assists rather than drives.
Accountability means everything is traceable. “We don’t want some large language model that somebody’s just pumping stuff into. It’s coming back. You have no idea where it came from, how that data was trained. Is it hallucinating? Is it not hallucinating? You need to be able to trust that that AI is credible, and you’re going to be able to use it in your accounting when you produce that to the auditors.”

Emily pushed Mark on a question many Intacct users ask: what about these new solutions flooding the market that claim to be “AI first”?

Mark’s response was diplomatic but pointed. New organizations saying “we’re AI native” and driving innovation are “good things for our industry.” But “how do you train AI? You train AI with data. We have a lot of data.”

Beyond raw data, Sage just kicked off what Mark calls its “Agentic AI marketplace.” This is a framework where partners build specialized AI agents that work across the broader Sage ecosystem. “We’re building hundreds and hundreds of agents that will be available to our customers,” he notes. The company is taking a platform approach where domain expertise gets layered onto trusted financial infrastructure.

The Adoption Paradox: Faster Than Cloud, Slower Than the Hype

Mark brings perspective from his 25 years in tech. He remembers when the internet arrived on dial-up connections that took five minutes to load. He watched the cloud evolve from radical concept to default infrastructure. Now he’s seeing AI reshape everything again.

“People thought it was going to move much quicker than it actually is,” he observes. “Adoption in these things is way more complicated than actually delivering the tech for it.”

In each major tech shift, people overestimate adoption speed. “The cloud is still being adopted in some places,” Mark points out.

The hosts brought up a perfect example of the hype-reality disconnect. Allbirds, a shoe company, rebranded itself as an AI organization and watched its stock rocket 600% in a single trading session before promptly crashing. “It’s reminiscent a little bit of the dot-com boom,” Mark says, “where people had a website and therefore their business was worth billions. And then everybody figured out they didn’t actually have a business case.”

But he distinguishes this moment from that bubble. “If you look at AI, it’s being driven predominantly by very large companies that are established with lots of customers and lots of money.” The recent tech stock dip “is just a reset on the adoption.”

So what are finance leaders actually saying when Mark sits across from them?

“We’re hearing this is game changing,” he reports. But it’s game changing in specific, practical ways:

Efficiency that enables strategy. “They look at AI to help them be more efficient so they can be more strategic,” Mark explains. The role of the CFO is becoming “significantly more strategic.”
Faster closes. “We’ve been talking for years about reducing time to close and eliminating the month-end close. AI is really going to speed that up.”
Immediate productivity gains. “When we let customers use our agents, they’re like, ‘I’m three times more productive. I cannot believe how much faster we’re getting things done.'”

But adoption takes time. “You can’t just inject things like that into your business overnight,” Mark cautions. “It’s got to be done in a way that makes sense to your workflows and your teams and how your processes roll.”

The conservative pace of AI adoption in finance is an essential feature in a profession where errors carry legal consequences.

Beyond the AI Headlines: What Else Is Changing

Matt asked for more insight into some other things happening at Sage that might not get as much attention because of how much focus is on AI.

Mark shared several initiatives that may have immediate impact:

Speed to market and faster implementations. “How are we going to implement faster? How are we going to get customers’ time to value reduced?” Mark asks. Matt reinforced why this matters. “If we have implementations that take three, six, eight months, we’re going to lose on that side of things.”
Vertical and micro-vertical specialization. “Our solution addresses the needs of those businesses within those verticals, which is something we’ve always done, but we’re doubling down on that,” Mark explains.
Strategic acquisitions filling gaps.
- Expense management. “We’re about 12 months into it and it’s done incredibly well. Overachieved all targets. Customers love it.”
- Sage HCM (payroll and HR). “It’s a great technology that’s really going to help us grow our business and deliver for our customers in a complete solution.”

Emily confirmed these acquisitions address real needs. “That was a big gap. In the past, a lot of clients asked for an expense management solution and wanted it all in one.”

What to Expect at Sage Future 2026

The Sage Future conference runs April 28-30 in San Francisco. Based on last year’s feedback, Sage restructured the entire event.

The new three-tier structure includes:

Keynotes now feature primarily external voices. Mark will interview Scott Krug, CFO of the New York Yankees. “He closes the books and does audits just like everybody else,” Mark says. Kara Swisher will discuss AI trends.
Super Sessions are new, product-specific deep dives.
Breakout sessions provide the next level of detail for features that caught your attention.

Matt made an important observation: “I’ve seen a lot of clients implement Intacct and then don’t go back to reconfigure over their lifetime. They’re not getting the full feature set out of the product.” The Super Sessions directly address this education gap.

Other highlights include:

Three embargoed announcements that Mark calls “very exciting and game changing for customers and partners”
CPA.com as titanium sponsor, validating Sage’s positioning as “accountants who serve accountants”
Monday night at Oracle Park (Giants stadium) and Thursday’s Sage Fest at an undisclosed “top” San Francisco venue
Post-event content distribution through webinars for those who can’t attend

“We want people to leave understanding where we’re going as a business and how we’re supporting them,” Mark says.

The Question Every Finance Leader Should Ask

The thread running through Mark’s conversation reframes how accounting professionals should evaluate every AI pitch landing on their desk.

A 70% accuracy threshold works for drafting marketing copy, but it’s a non-starter when the output feeds financial statements and regulatory filings. That constraint reshapes everything about how we build and deploy AI in accounting.

Whether you’re a CFO weighing technology investments, a controller separating AI substance from hype, or a partner building around the Sage ecosystem, listen to the full discussion. And if you’re heading to Sage Future 2026 in San Francisco, you now know exactly what to look for.

The Month-End Close Is Accounting’s Biggest Bottleneck. Here’s How AI Is Dismantling It

Earmark Team · May 7, 2026 ·

The day before a tax deadline, and accountants from Miami to Vancouver, Portland to New York, logged into a CPE-eligible webinar to learn something that could fundamentally change how they work. The webinar showed how these professionals can shrink the most time-consuming part of their month-end close, like reconciliations, transaction coding, and bank statement chasing, from days to minutes.

Megan Reid, product specialist at Digits, led the session, and she brings a unique perspective. She’s an accountant with 15 years in the trenches, starting at a Big Four firm, moving through banking and construction, and now helping firms build what she calls an “AI-native” practice. As she put it to the audience, “As accountants, we want to be able to serve more clients, provide better service, and do so quickly and efficiently.”

The traditional month-end close is accounting’s biggest bottleneck. It’s that manual grind through booking transactions, reconciling statements, updating schedules, reviewing anomalies, and (if there’s time left) analyzing the numbers and creating the reports clients care about. “It’s a manual, tedious, time-consuming process that honestly leaves a lot to be desired for both the business owners and the accountants,” Megan said bluntly.

But what if you could flip that entire workflow? What if instead of reviewing every transaction, you only touched the ones AI couldn’t confidently handle? That’s exactly what Megan demonstrated live, showing how AI-native platforms transform the close from a compliance chore into an opportunity for real advisory work.

The bottlenecks killing your efficiency

Before diving into solutions, Megan mapped out where the traditional close breaks down. You start in QuickBooks or your ledger of choice, but quickly find yourself bouncing between Excel, browser tabs for vendor research, your close management tool, and who knows what else. “Not only are you managing the work across all these multiple platforms,” she explained, “you’re also spending time validating sync accuracy, troubleshooting issues, and making sure the data moves seamlessly throughout the various systems.”

Each phase has its own special frustrations:

Manual data entry and rule management introduce human error
Fighting with bank access and chasing clients for statements
Disconnected tools for AP, credit cards, and close management
Team members use different processes, causing rework and confusion
Manual journal entries pile up at period-end

As a result, most of your time goes to necessary but low-value tasks, leaving little room for the analysis and insights your clients actually hired you to provide.

How AI learns your way of doing things

The shift to AI-native platforms involves intelligence that learns and adapts. When Megan pulled up the demo client in Digits, she showed hundreds of transactions the AI automatically categorized. Only eight were flagged for review.

“How does it know how to categorize transactions?” she asked, anticipating the obvious question. The answer lies in three layers of learning.

First, there’s client-level learning. When you correct a categorization for a specific client, the system learns instantly. “If you review something for a brand new client and you say, ‘nope, you categorized this to software, but I actually want it to be cost of revenue,’ Digits learns from that instantly,” Megan explained.

Second, there’s firm-level learning. The system recognizes patterns across your entire client base. If the system does not have the client-level layer of knowledge, it falls to the firm-level. “How has my firm done this across all of my clients? It automatically applies your firm’s unique value to your client base.”

Third, when a transaction is entirely new, proprietary models trained on billions of dollars’ worth of transactions make the call.

During the live demo, Megan reviewed a U.S. Patent and Trademark Office transaction the AI thought might be taxes. She looked at the suggestions (taxes, legal, or a new intangibles account), selected “Legal,” and clicked save. The system immediately found two similar transactions and updated them automatically. The review queue dropped from eight to five in seconds.

But what really eliminates busywork is the AI agents run 24/7 in the background, researching vendors and populating details. “None of this has been populated manually,” Megan showed, clicking through a vendor profile complete with name, logo, description, and related websites. “We’re essentially researching them and populating all of the data for you.”

Bank reconciliation without the chase

If transaction categorization is tedious, reconciliation might be even worse. You know the drill: fighting for bank access, emailing clients for statements, then manually comparing the ledger to the statement line by line.

Megan demonstrated the “happy path” first. Digits pulled a Mercury bank statement via an API, automatically kicked off reconciliation, matched every transaction with pixel-level precision on the PDF, confirmed the ending balance, and finalized everything. Zero human touches required.

“Some firms we work with actually say, ‘I uploaded six months of bank statements and just watched them finalize one by one. And I didn’t do anything,'” Megan shared.

When auto-reconciliation can’t finalize completely, it doesn’t leave you guessing. The system flags specific issues, such as:

Missing transactions that exist on the statement but not in the ledger (one click to create)
Date mismatches where something cleared May 31 but hit the ledger June 1 (one click to adjust)
Unsettled items like checks that haven’t cleared yet

For banks without API access, such as small credit unions, you simply drag and drop a PDF statement. During the demo, Megan dragged a statement into the system and watched it extract data and start reconciling in seconds.

She took it further with a cleanup scenario. Starting with a brand-new bank account, she imported a PDF statement. Within moments, 14 transactions appeared as uncategorized. Seconds later, the AI had populated every vendor name and category without a single manual input.

Turning saved time into client value

Speed alone isn’t the point. As Megan emphasized, “the compliance and the month-end close is really just a means to an end,” the end being insights and value for clients.

The dashboards in Digits default to the current month because, as Megan noted, “knowing something two months late doesn’t usually help.” Every metric is live and drillable. Click into gross income, and you see the definition, calculation, and every underlying transaction. Your clients finally understand how you arrived at the numbers.

Each client gets customized dashboards. “Maybe you have a client that’s like, ‘we’re spending so much money on travel,'” Megan explained, showing how to add customized metrics that are specific to each client. A profitable client with ten years of runway might swap that widget for gross profit or vendor analysis.

Collaboration happens right on the platform. On any transaction, category, or report, you can leave a question. The client receives a notification and can respond directly from email without logging in. “One of the biggest pain points is transfer of knowledge,” Megan said, “making sure that you have everything that you need from your clients and vice versa.”

Custom reports become interactive stories rather than black-and-white PDFs. The AI generates insights like “You earned 33% more in March compared to the prior month” with drill-down capability to see exactly why. Important insights can be pinned to the executive summary so they’re the first thing clients see.

What this means for your firm

During the Q&A, attendees asked practical questions. One wondered if this integrates with QuickBooks or replaces it entirely. “Digits is a complete ledger system. So it’s a complete replacement,” Megan answered. They can migrate QuickBooks data in about two minutes, but this is a ground-up rebuild, not a bolt-on tool.

Another attendee asked about company scale. The focus is on small and medium-sized businesses, which is the client base most firms serve.

The shift from reviewing everything to reviewing only exceptions makes the close faster and more consistent across your team, less error-prone, and it frees up capacity to serve more clients without hiring proportionally.

“It’s a very exciting time to be an accountant while also a little bit scary,” Megan acknowledged near the session’s end. “I think it’s a time to really lean in and be excited.”

She’s right. The firms embracing AI-native tools now will deliver premium advisory services while their competitors are reconciling bank statements at midnight.

To see these workflows in action, watch the full webinar. Every accountant who signs up gets access to a sandbox demo environment where you can test these workflows with real data. And if you attended live or watch the recording, you can earn CPE credit through the Earmark app. Just search for the course and complete the quiz.

The close is changing. Will you lead that change or follow it?