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Accounting Technology

Stop Losing Money on Cleanup Work by Automating the Parts That Don’t Need You

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Cleanup and catch-up work is among the most in-demand services accounting firms can sell, and among the hardest to deliver profitably. That was the starting point for a recent webinar led by Megan Reid, a 15-year accounting veteran who started in Big Four, moved through private industry, and now works on the firm enablement team at Digits.

In the webinar, Megan demonstrated how AI-native accounting tools can transform cleanup engagements from time-intensive projects into scalable service offerings. She built a client file from scratch, imported raw PDF bank statements, and walked through an entire cleanup workflow in real time.

Why cleanup work kills profit margins

“Cleanup is obviously valuable work and it’s hard to scale,” Megan said, framing the core challenge clearly. New clients almost always arrive with some sort of mess to clean up. Maybe you have 18 months of uncategorized transactions or transactions that haven’t been posted from the bank feed. You want to take the engagement, but you know it’s going to be hard to make it profitable.

“We always uncover more skeletons in the closet than we think,” Megan noted during the demonstration. If you’re billing fixed fees, you get squeezed by unpredictable hours. Clients want fast turnarounds. Your teams are leaner. “You’re asked to do more with less,” she said.

“Business owners need that work to be done,” Megan pointed out. But the question is “whether or not your workflow lets you take them profitably.”

Breaking down a traditional cleanup shows where the hours go:

  • Gathering data
  • Importing it or connecting feeds
  • Categorizing tons of transactions
  • Reconciling accounts
  • Resolving exceptions
  • Making adjusting entries
  • Reviewing everything with your client
  • Delivering the final report

“In a typical 12-month cleanup or catch-up, you spend the majority of your time categorizing and reconciling transactions,” Megan explained. These tasks are also “the most repetitive, pattern-based parts of the job, which is exactly what AI is good at.”

From blank file to categorized transactions

Megan started her demonstration with a completely blank client file, essentially just an empty ledger. She then showed how to handle a common scenario in which a new client hands over a stack of PDF bank statements with no bank login credentials.

She dragged and dropped the first PDF bank statement directly into Digits. “It is extracting all that data from the bank statement, booking it and categorizing it as well,” Megan explained as the system processed the document.

The AI extracted transactions, identified vendors and customers (called “parties” in Digits), populated company logos and descriptions, attached website links, and categorized each transaction into the appropriate account. Megan noted the system pulls from models trained on “more than 800 trillion dollars’ worth of transactions.”

After uploading statements for June through October, hundreds of transactions flowed in. When processing finished, only 12 were flagged for review. “Instead of manually clearing bank feeds,” Megan said, “come here and look at the exceptions.”

These were transactions that required confirmation. Megan clicked into one from Swift Courier Services. The AI suggested “contractors and consultants.” She confirmed it with one click.

From there, the system natively learned from that categorization. It immediately found two similar transactions and offered to update them together. The exception list dropped from 12 to 8 in seconds.

Bank reconciliation without the manual work

Megan demonstrated three ways to get bank statements into the system for reconciliation. You can connect directly to banks like Mercury, Wells Fargo, Chase, and US Bank, which pull statements automatically via API. You can drag and drop PDF statements anywhere in the product. Or you can use email ingestion, where each client gets a unique email address to forward statements.

She uploaded the June statement by dragging it onto the reconciliation screen. The system read the PDF, extracted every line item, and verified each against the ledger. Megan explained that the system uses “pixel bounding boxes” to match statement entries to ledger entries.

June needed one manual step: adding a beginning balance entry that the system couldn’t infer without a connected bank account. Megan created the entry directly in the reconciliation screen. “Unlike legacy systems, where you may have to have three different tabs open and make changes and then come back and refresh, everything can be done directly in here.”

Then she uploaded July’s statement and navigated away. When she returned, it was done. “The statement was uploaded by me. The auto reconciliation was kicked off by Digits and even finalized by Digits,” she showed in the timeline view.

For larger cleanups, Megan recommended uploading multiple statements at one time. Handle any beginning balances in the first month, then subsequent months often complete automatically.

Review tools that surface what matters

Even with AI handling categorization, accountants still need to review and sign off. “It doesn’t replace the accountant. It just removes that tedious work so that you can focus on those judgment calls,” Megan emphasized.

She demonstrated several review approaches. The general ledger view shows all transactions organized like a trial balance, including assets, liabilities, equity, revenue, and expenses. You can filter by status, amount, source, department, or location. Bulk updates work on hundreds of transactions at once.

Megan said the vendors and customers views are her favorite. They each flag two critical items:

  • New vendors or customers: Any vendor (or customer) the AI sees for the first time in your selected period
  • Split categorizations: Vendors (or customers) whose transactions appear in multiple categories

“I just need to have eyes on things it has not seen before,” Megan explained. Even if the AI categorized with high confidence, you have final review and say on how it was categorized..

For transactions needing client input, the collaboration happens in one place. Megan showed how to comment on any transaction: “Hey client, what is this for?” The client receives an email with a link, can respond directly in Digits or reply to the email, and the response appears on the platform. “All the collaboration is centralized in one location,” she said, “instead of you having to manage a ton of emails and download Excel files.”

Delivering professional reports, not data dumps

The final step Megan demonstrated was creating custom reports. While the financials inside Digits update live as transactions flow in, cleanup engagements need a formal deliverable, a static document that locks the numbers in place.

Megan built one on screen. She added a cover page, used AI to draft an executive summary, embedded links to the client’s checklist, and configured the financial statements with period comparisons and trend lines. The system includes “hover to discover” insights that show period-over-period changes and what drove them.

When you need to make adjustments after sending a draft, you create a new version. “Any adjustments you’ve made in Digits will then update directly to this report,” Megan explained. Publishing the final version removes the draft watermark and notifies the client.

The platform tracks everything, including when you created the report, when you published it, when the client viewed it, and all comments from either party. You have a complete record of the deliverable and the conversation around it.

“We’ve done 12 months of cleanup in an hour and a half instead of days,” Megan concluded.

What this means for your firm

The key takeaways from Megan’s demonstration show how cleanup engagements can become profitable:

  • AI categorizes the vast majority of transactions automatically, flagging only true exceptions
  • Bank reconciliations can run automatically when you upload statements
  • The system learns instantly from every correction without rules to build or maintain
  • Your time shifts to reviewing anomalies, making judgment calls, and delivering polished reports

One practical consideration came up during Q&A. When asked about importing messy QuickBooks Online data, Megan confirmed that direct QBO migration exists but cautioned, “You maybe don’t want the AI to learn off of really messy data. You maybe just want to start fresh.” The system uses imported data for baseline training, so starting clean might make more sense for particularly messy files.

For firms trying to grow, this changes the economics of client acquisition. Every prospect with messy books becomes an opportunity rather than a capacity problem. When you can handle cleanup work profitably, predictably, and consistently, you can say yes to more engagements while maintaining margins.

Watch the full on-demand webinar to see Megan’s complete demonstration from blank file to published financials. If you have cleanup engagements in your pipeline right now, consider what your workflow could look like when the repetitive work is automated.

Not All AI Is Created Equal and Your Next Software Decision Depends on Knowing the Difference

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When Jeff Seibert ran consumer product at Twitter, he asked the finance team for his budget to throw a team event. They said they’d get back to him in 45 days. So he just ran the event without them.

That gap between real-time data and 30-to-90-day delayed financial reports was frustrating, and it eventually led Jeff to build Digits, a new general ledger designed from scratch for the machine learning age. After raising $100 million pre-launch, testing 2,000 monthly closes, and getting 80% of clients closed in under an hour, Digits launched in March 2025. Now, just over a year later, hundreds of accounting firms are onboarding thousands of clients onto the platform.

Jeff launched Twitter’s algorithmic timeline in 2016, and it was one of the first global deployments of machine learning. Now, the AI revolution Jeff helped launch is flooding the accounting profession with claims that are hard to verify. Every accounting software company seems to include AI in its marketing copy, promising everything from “fully automated bookkeeping” to capabilities that don’t add up under scrutiny.

In a recent Earmark webinar, host Blake Oliver and Rob Hamilton, Head of GTM at Digits, pulled back the curtain on how AI in accounting actually works. He was joined by Megan Reid, Product Specialist & Firm Enablement at Digits, who fielded questions throughout the session.

Every AI claim in accounting software isn’t real. But accountants who understand the four core model types (plus one common lie) will make smarter investments, automate the right parts of their workflow, and position their firms for a shift Rob sees coming by the end of 2026.

The AI hype problem (and one question to cut through it)

Before making any technology decision, you need a filter for separating real capabilities from marketing fluff. Rob offered a simple one that cuts through the noise.

He showed screenshots from multiple accounting software companies making bold AI claims. One promised “fully automated bookkeeping.” Another asked, “Do you do AI bookkeeping or do you use a dedicated team of experts?” The positioning has gotten so confusing that firms can’t tell what’s real anymore.

The confusion isn’t new. About five years ago, tech investor Naval Ravikant tweeted, “In most pitch decks, AI stands for Anonymous Indians.” For a long time, that was literally true. Services like Botkeeper rose and fell using offshore labor dressed up as automation. Today, “AI actually means we just bolted on and sent all of your data to ChatGPT,” Rob explained.

Here’s your filter: “AI is the same thing as machine learning,” Rob stated. “If someone is talking to you about AI and they’re not referring to machine learning as the underlying premise, it’s just BS.”

But this filter only works if you understand what machine learning actually is.

Traditional software is straightforward. You write code that tells the computer exactly what to do. It’s tedious to build, but rock solid once it works. Machine learning flips this completely. You feed the system thousands or millions of examples, and the model learns the patterns itself. As Jeff explained in a clip Rob played, “You give the computer the goal state—I want this outcome—and then the computer itself is learning how to do it.”

These models are neural networks. Thousands of hidden layers mimic how neurons connect, based on Google’s 2017 “transformer” research paper (the “T” in GPT). It’s a massive matrix multiplication problem where the system figures out how variables relate to each other.

But machine learning isn’t one thing. Different model types have different strengths and uses in accounting. Understanding these distinctions helps you avoid buying the wrong software and shows you exactly where AI can save time and where vendors are overselling.

The model types that matter (and one that doesn’t)

Rob walked through five categories that get lumped under “AI,” but understanding the differences is what separates informed decisions from expensive mistakes.

Generative models

Large language models (LLMs) are the ones you hear about most, ChatGPT being the prime example. GPT stands for “Generative Pre-Trained Transformer,” and these models generate the most likely continuation of whatever prompt you give them. Rob showed a useful application: turning bullet-point close notes into polished client emails. His advice is to write a “job description” for the AI once. Tell it who it is, give context, specify output format, add examples. Then just paste in different client notes as needed.

But generative models have serious limits. They’re “super eager” and always want to complete prompts, making them prone to hallucinations, or making things up that sound real. They’re bad at math because they generate text rather than calculate numbers. And they’re trained on the internet, not your specific clients. “The ways that it is hallucinating is stuff that maybe even is hard for humans to catch sometimes,” Rob warned. Always review the output.

Agents

These are LLMs with help. You give them a job description, a task, and tools, like computer programs they can use to generate reports, list accounts, or run calculations. The agent makes a plan, uses its tools, checks if the task is done, and loops until complete. Rob showed Digits’ agent answering “I want to hire 20 software engineers next year. Can I afford to?” with a data-backed response.

Guardrails are critical. Microsoft’s early agent “started asking people on dates in the chat,” Rob noted. “You don’t want your accounting agent dispensing dating advice.” Agents work well for updating schedules, running quality checks, and answering analytical questions, but they’re slow and need careful boundaries.

Predictive models

These got Rob visibly excited, and for good reason. These models take an input and predict an output from known options. When the model sees a $5 Starbucks charge, it considers the client’s location, history, and chart of accounts. For a local client, it’s meals and entertainment. For a New York client in California, it’s travel. A $157 Starbucks charge is probably an event, regardless.

What makes predictive models perfect for transaction categorization is they can’t hallucinate; they only choose from existing options. They’re deterministic (same input, same output), include confidence scores, and run fast and cheap once trained.

Digits built a “layer cake” of predictive models:

  1. Client-level (learns each business)
  2. Firm-level (encodes your best practices)
  3. Global (trained on 180 million transactions worth nearly $1 trillion)
  4. An LLM fallback for completely new transactions

The result was over 97% accuracy, compared to standalone LLMs that plateau below 80%, which is about the same as outsourced bookkeepers.

Document extraction models

These combine OCR with layout-aware language models that understand document structure. Previous tools used Amazon’s Mechanical Turk, which relied on humans manually extracting data and took hours. Modern extraction models work in seconds. Digits’ bank reconciliation automatically pulls PDF statements, matches transactions to the exact spot in the PDF, and generates audit reports.

Data analysis

This model is where Rob pulled the rug out. Financial reporting and analysis is “actually just math. It’s not ML.” Computers have done statistical analysis for decades. Could you build an agent to do it? Sure, but it would be slow, expensive, and probably wrong. “If anyone says their AI does reporting and statistical analysis, please ask them what they’re talking about.”

Here’s how the right models map to your month-end close:

  • Book transactions: Predictive models (with LLM fallback)
  • Reconcile statements: Extraction models plus matching algorithms
  • Update schedules: Agents
  • Review and correct: Agents with quality checklists
  • Analyze and report: Statistical analysis plus agents for questions

“Shoehorning an LLM in to solve a problem and just sending a bunch of information is fundamentally incorrect,” Rob emphasized. Each step needs the right model. No single AI approach handles everything.

The 2026 prediction

Understanding model types is just the foundation. The urgency comes from how fast everything is converging.

“Across a large client set in different industry types, it’s highly likely that the month-end close process is looking to be completely automated by the end of 2026,” Rob predicts. Even his “95% automated” hedge probably sounds aggressive. But his logic follows directly from the technology.

If predictive models hit 97% accuracy on transactions, extraction models automate reconciliation in seconds, agents handle schedules and quality control, and statistical analysis covers reporting, then manual work drops to a fraction. Rob’s goal is to see accountants doing “1/20th of the work you’re doing today.”

He acknowledged limits. Construction firms with complex job costing might not hit that threshold. But for firms serving professional services, cash-basis businesses, and straightforward accrual clients, the automation curve is steep.

An AI-native firm will focus on value instead of tedium. Deeper industry expertise. Stronger client relationships. Higher margins. You’re not reviewing every transaction, you’re supervising the system and handling exceptions. Those hours saved on reconciliation become advisory time clients actually value.

But this is also a competitive necessity. “AI won’t replace you. Someone who’s good at using AI is going to,” Rob said, quoting a common warning. And he was direct about the stakes. Firms that don’t adapt will face “a cascading effect on business models” as early adopters pull ahead.

For overwhelmed firms, which Rob acknowledged includes most firms, he offered practical starting points:

  • Map your processes first. If you use workflow tools like Karbon or Keeper, you’ve probably documented your steps. If not, start there. You can’t identify where AI fits until you know what you’re actually doing.
  • Start small and low-stakes. Don’t tackle your biggest challenge first. Try drafting emails, testing categorization, or visualizing data. Build your intuition gradually.
  • Get hands-on with new tools. Rob mentioned being impressed by Claude Opus, which could build HTML dashboards from his data (something he couldn’t do as a non-engineer). The specific tool doesn’t matter; hands-on experience builds judgment.
  • Know your business before choosing where to start. As Rob put it, “You need to know the details of your business to know where you can start and where the right places to poke and prod are.”

The “wait and see” window is closing. Firms that develop AI literacy now by asking questions about models, data handling, and use cases, will be ready for the rest of 2026 and beyond.

Your next move: Better questions, smaller steps, faster action

Let’s turn Rob and Megan’s insights into actionable takeaways:

  • Not all AI is equal. Four real model types plus one fake (data analysis) get lumped together. When vendors pitch “AI-powered reporting,” you now know to dig deeper.
  • Each close step needs a different model. Predictive for transactions. Extraction for reconciliation. Agents for schedules. Statistics for reporting. Anyone claiming one solution does everything deserves scrutiny.
  • Predictive models beat LLMs for categorization. Layered architectures that learn your clients and firm patterns dramatically outperform chatbots. Bigger isn’t always better.
  • Ask vendors the hard questions. What model type? Where does data go? Are you training your own models or sending financial data to third parties? This is due diligence.
  • The tipping point is closer than you think. Whether Rob’s 2026 prediction proves exactly right or directionally right, the trajectory is clear. Understanding these distinctions now positions you to take action.

For those interested in going deeper, Rob mentioned resources like the AI Native Accounting Foundation and the AI-Native Accounting podcast hosted by Kacee Johnson, where industry leaders discuss the latest developments.

The accounting profession is at a real inflection point. Smart firm leaders will develop the literacy to ask smart questions, experiment in the right places, and redirect time from tedium to advisory work clients value.

Rob noted this might be one of the few professions with such clear AI use cases, putting accountants at the forefront of innovation. That’s an opportunity to shape how technology serves the profession, not the other way around.

Watch the on-demand webinar for complete details, including live demonstrations, security architecture specifics, and audience Q&A covering nonprofits, inventory clients, and platform migrations. The future of accounting is being written now. Make sure you’re part of the conversation.

Inside the Innovation Circle: Three Days of Conversations at Intuit Connect

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After three days of walking around the Innovation Circle at Intuit Connect and filling 27 pages of Field Notes, it’s clear that QuickBooks is transforming from accounting software into a complete business operating system.

That’s the takeaway from a recent episode of The Unofficial QuickBooks Accountants Podcast, where hosts Alicia Katz Pollock, MAT, and Dan DeLong wrap up their three-part series covering Intuit Connect, where Alicia skipped the workshops to spend her time talking directly with developers in the Innovation Circle.

Keep in mind that these conversations occurred three months before the episode aired. So Alicia notes, “A lot of the things they said are coming soon might have already been released. So the timelines are kind of vague on a lot of these.”

What isn’t vague is where Intuit is heading. From AI-powered construction project management to sophisticated bill-approval workflows, the platform is expanding across every corner of business operations. For accounting professionals, understanding this evolution is the difference between being a bookkeeper and becoming a strategic business advisor.

Construction Gets Industry-Specific Tools in Enterprise Suite

Alicia’s conversation with Uttam Ramamurthy, Principal Engineer – AI Builder at Intuit, revealed how Intuit Enterprise Suite is tackling construction accounting, one of their key mid-market targets. They’re building specialized tools that actually understand construction workflows.

The familiar project list with profitability stripes is becoming a full dashboard designed for construction companies. You can set default margin goals, such as 25% profit on all projects, and the system alerts you when profitability falls below your threshold. As Alicia explained, “If you fall below your profit margin settings, it alerts you and gives you a heads up when your profitability is too low.”

The AI capabilities show real promise. Upload your project notes, and the system auto-populates project details and phases. It pulls from your documentation and uses what Intuit calls “AI product knowledge from similar projects” to suggest project structure.

Other construction features in development include:

  • Upload spreadsheets directly into project budgets (finally bridging the gap between estimating spreadsheets and QuickBooks)
  • Create product and service lists with quantities and unit costs, grouped by phases and cost groups
  • Show collapsible estimate views where customers see clean phase summaries while you keep line-item detail
  • Build graphic proposals with text blocks, photos, before/after images, and testimonials
  • Take deposits from estimates with proper liability accounting

That deposit feature comes with a warning. Alicia tested it three times during a recent class. It worked once but failed twice to properly subtract the deposit when converting to invoices. “I’m not sure if it’s still in development or not working, or if it’s just my cookies on my computer preventing it from working,” she admitted.

The platform now supports AIA progress billing, addressing a major gap for firms with architect and government contracts. As Dan observed, “The devil is always in the details as far as how it actually looks, but they understand those workflows.”

You can even mark project phases as complete via text message to automatically generate invoices. When projects close, Intuit Enterprise Suite creates a summary with lessons learned, profitability reports, and outstanding transactions, essentially a built-in project post-mortem.

For construction companies with multiple entities (common with separate LLCs for different projects), Intuit Enterprise Suite offers consolidated views across companies with shared charts of accounts, vendors, dimensions, and customers. You can create entity groups and filter views to specific business segments.

Mailchimp Integration Powers Marketing from Your Financial Data

The Mailchimp integration shows how seriously Intuit takes the connection between accounting and marketing. After all, your QuickBooks already knows who your customers are and what they buy. So why not use that for targeted marketing?

Alicia shared an example from her own business. When Intuit announces price increases, she needs to notify clients on wholesale QuickBooks plans where she pays for their subscriptions. She creates a Mailchimp segment where “product or service equals wholesale QuickBooks,” finds everyone affected, and sends targeted emails, all driven by her accounting data.

Stephen Yu, CPA and Product Manager at Intuit, walked Alicia through upcoming enhancements that will connect additional platforms. Soon, you’ll see email campaign success alongside data from Shopify, Stripe, PayPal, Square, and Wix on a single dashboard.

Other Mailchimp features coming soon include:

  • Click maps showing where recipients engage in your emails
  • Audience dashboards tracking growth by channel (Meta, Google, website forms, manual imports)
  • Revenue attribution connecting sales to specific campaigns
  • Journey tracking from page views through cart additions to checkout
  • Send time optimization revealing best days and times
  • AI-generated performance digests with recommended actions
  • Drag-and-drop templates that auto-generate newsletters from blog content (targeted for 2026)

ProAdvisors get Mailchimp discounts based on their tier level. The higher your tier, the better the pricing. Though Dan noted these discounts do expire.

What impressed Dan was Intuit’s patient approach to integration. “They’re not taking Mailchimp things and putting them in QuickBooks or taking QuickBooks things and putting them in Mailchimp. They are truly putting them on the same level. It’s a lot more polished than what we’ve seen in the past.”

The platform is also adding SMS messaging capabilities and, potentially, WhatsApp integration, expanding beyond email to meet customers where they communicate.

Customer Hub Becomes a Real CRM System

Christina Stansbury, Principal Product Marketer at Intuit, showed Alicia how the Customer Hub is evolving into a true customer relationship management system. Alicia already covered this development extensively in a previous episode, Customer Leads Hubba-Hubba.

You can now embed contact forms directly on your website and route inquiries into QuickBooks. The AI “customer agent” scans your Gmail to surface inquiries about your services and automatically convert them into leads.

The lead management system offers both list and Kanban views that visualize your pipeline from inquiry through discovery, negotiation, and closing. The system suggests next steps: draft an email, create an estimate, or book a site visit.

Other communication features built into Customer Hub include:

  • Emails sent through your Gmail (appearing completely natural to recipients)
  • Calendar integration for appointment scheduling
  • Self-scheduling links for customers
  • Video calls with automatic transcription (no recording, but searchable transcripts)
  • Mobile app integration for site visits with voice recordings, images, and notes

The mobile app deserves special mention. Dan highlighted how Intuit overhauled it to mirror the desktop experience. “The terminology changes on the web version found their way pretty quickly to the mobile app, which I appreciate.”

Coming soon: a proposal builder that pulls from your lead notes, emails, and conversations to generate polished documents connected to customer data. As with Intuit Enterprise Suite proposals, professionals can collect signatures and deposits directly from the proposal.

Bill Pay Gets Enterprise-Level Sophistication

The bill pay evolution addresses both processing efficiency and compliance requirements. You can email bills to a custom intuit.com email address or drag multiple documents into the business feed.

The current limitation is line-item detail. As Alicia explained to Abby Chu, Staff Marketing Manager at Intuit, the system reliably captures vendor names and dates but struggles with individual line items. Intuit is building machine learning to address this. Eventually, it will prompt you to create rules.

This creates what Alicia called a chicken-and-egg problem. “If it doesn’t work, people can’t use it. But if we don’t use it, then they can’t build the AI generator to make it work.”

Fees vary by payment speed:

  • Standard: 3 days (free)
  • Faster: 1 day ($10)
  • Instant: Minutes (1% fee, $100 maximum)

That instant option with the capped fee is noteworthy because you can pay a large urgent bill for just $100.

Bill Pay Elite introduces sophisticated approval workflows with full segregation of duties. You must have different people as bill clerk, approver, and payer—no overlap allowed. Approval conditions can stack up to seven levels deep, with complex if/then logic based on vendor, amount, and products.

Future enhancements include group approvals (any team member can approve), delegation for out-of-office situations, and audit history tracking workflow changes.

For bookkeepers managing multiple clients, Intuit Accountant Suite provides an eagle-eye view of bills across your entire client base. You’ll soon see available cash balances to prevent bounced payments.

But Alicia offered an important caveat about high-level views. During year-end cleanup, she discovered a client paying both personal and business electricity bills from the company card—something only visible at the transaction level. “There are some times when the eagle eyes still don’t give us the details on the ground view,” she noted.

Lending Services Leverage Your Financial Data

QuickBooks now incorporates Credit Karma’s embedded lending capabilities. Think of it like LendingTree built into your accounting software.

For loans under $250,000, Intuit offers direct lending. Above that, they connect you with third-party lenders. The system evaluates your credit score and business history to provide terms with no origination fees or prepayment penalties, although interest rates vary based on creditworthiness.

For customers, there’s a toggle in settings (currently defaulted on) that offers financing on large estimates. As Alicia explained, “If one of your potential customers turns down your bid because they have cash flow issues, then you may be able to win the engagement by offering them financing.”

On the collections side, you can now require auto-pay for recurring invoices. Looking ahead, customers will have their own dashboard to manage payments across all QuickBooks-using vendors. Update a credit card once, and it applies everywhere.

The Platform Evolution Continues

After three episodes covering Intuit Connect, Alicia concludes, “Intuit is really true to their mantra of powering prosperity around the world. They’re trying to help us increase revenue and improve cash flow. Having the data and insights to see what’s happening beyond just running a P&L and balance sheet is really super helpful.”

The challenge for accounting professionals is keeping up. Even Intuit’s own sales teams struggle to understand the full platform. Dan shared his frustration with telesales agents who don’t realize what Intuit Enterprise Suite offers, requiring multiple handoffs to get clients the right information.

But the opportunities are substantial for those who embrace the platform’s evolution. You can offer advisory services around marketing analytics, design approval workflows, guide construction clients through industry-specific tools, and advise on embedded lending options.

QuickBooks will continue transforming. Will you be the advisor helping clients navigate these new capabilities or the one still explaining why they need separate software for everything?

Listen to the full episode to learn more. And remember, as Dan and Alicia noted, they’re “almost ready for the next Intuit Connect to do this all again.”

Alicia Katz Pollock’s Royalwise OWLS (On-Demand Web-based Learning Solutions) is the industry’s premier portal for top-notch QuickBooks Online training with CPE for accounting firms, bookkeepers, and small business owners. Visit Royalwise OWLS, where learning QBO is a HOOT!

From Data Entry Nightmare to Automated Workflow in One Demo Session

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You’re ten days away from the 1099 and W-2 deadline, and you’re still wrestling with QuickBooks, fielding a flood of W-9 request emails, and dreading the inevitable data entry marathon. Sound familiar?

You’re not the only one. As David Leary admitted during a recent Earmark Expo webinar, “I’ve been procrastinating on issuing 1099s. It’s just not a great experience.” He described the dual frustration that many accountants know all too well. “It’s annoying work on both sides. I need to do my 1099s, but then, as a business that receives them, I get a slew of emails from other companies asking for a W-9.”

In the webinar, David and co-host Blake Oliver took TaxBandits for a test drive with Nikita Sullivent, the company’s Support Specialist, to explore how this IRS-authorized e-file platform handles over 70 tax forms. The live demo included the authentic technical hiccups we all face with real-world software and shared practical solutions for the compliance challenges that hit every January.

Getting your data in: from hours to minutes

Manual data entry for hundreds of 1099s is a bottleneck that keeps you from serving more clients. TaxBandits tackles this with multiple import options that meet you where your data lives.

The platform offers three main paths for getting data in. You can:

  1. Enter forms manually one at a time (perfect for that forgotten contractor),
  2. Use bulk upload templates for larger volumes, or
  3. Connect directly with accounting software (current integrations include QuickBooks Online, Xero, Sage Intacct, and Zoho, with Karbon integration coming soon).

The bulk upload process stands out for its simplicity. As Nikita demonstrated, “You’re reviewing the columns at the top and inputting the data beneath them. Once we have all of that data input, we’ll just download it as a CSV and drag and drop it in.”

David particularly appreciated one detail. “I like how on your templates, in the header of each column, you give the instructions for the values you accept in that field.” No more guessing whether to use “CA” or “California,” or whether TINs need dashes.

The workflow breaks down like this:

  1. Download the Excel template with clear column headers
  2. Fill in your data following the built-in instructions for each field
  3. Drag and drop the file into TaxBandits
  4. Review the automatic error check that flags issues like missing digits in EINs or duplicate records
  5. Fix any problems by either editing in the app or exporting just the error records for correction

For QuickBooks users wondering about the process, David confirmed you can export your vendor list, filter for 1099 vendors, and use the “upload your own file” feature. The first time requires mapping your fields to TaxBandits’ fields, but that mapping saves for future uploads.

One webinar attendee asked whether they needed to re-enter last year’s payees. “Absolutely not,” Nikita answered. “Everything stays in your account and rolls over year after year.” When you import this year’s data and the system finds a duplicate, you can either delete it or update the existing record with any changes.

The platform also distinguishes between importing only recipient data and importing both payer and recipient data. If you maintain TaxBandits throughout the year, importing just recipients during filing season works best since you’ve already set up your payers. But if you’re adding everything at once, the combined import saves steps.

With data flowing smoothly into the system, the next challenge is ensuring that data won’t bounce back from the IRS.

TIN verification: the new compliance reality

Getting data into the system efficiently matters only if it passes IRS validation. The agency’s transition from the FIRE system to IRIS (Information Returns Intake System) brings stricter requirements that every accountant needs to understand.

“The IRIS system is going to be far stricter on TIN matching than the FIRE system was,” Nikita warns. “Which means if the SSN, the EIN, the TIN, and the recipient name don’t identically match the IRS database, it’s going to kick the form back to you as accepted with errors, and you have to file a correction.”

The keyword is “identically.” A contractor who goes by “Mike” but whose Social Security card reads “Michael” could trigger a rejection. Even punctuation differences in business names can cause problems.

TaxBandits builds TIN verification into multiple touchpoints:

  • When collecting W-9s throughout the year
  • When adding recipients to your address book
  • During the 1099 workflow as a final check

The smart approach starts early. “When you get a W-9, when you get a new employee or contractor, you go ahead and do the TIN matching on that prior to the filing season,” Nikita advised. This prevents last-minute surprises when deadlines loom.

Verification typically returns within two to four hours during normal periods. But during peak season “it can be up to 24 hours,” Nikita warned. If you’re verifying TINs within the 1099 workflow itself, the system waits for results before transmitting, which is potentially problematic if you’re filing on January 31st.

For those worried about the cost of corrections, TaxBandits offers some protection. Their “TaxBandits Commitment” covers correction filings at no additional charge. But even free corrections cost you time and stress.

The platform also streamlines W-9 collection. Instead of chasing paperwork, you can send electronic W-9 requests. Recipients complete them online, and the data flows directly into your TaxBandits account, ready for immediate TIN verification if desired.

Once your forms are prepared and verified, you still need to get them into recipients’ hands compliantly.

Distribution flexibility that actually works

The old choice between hours at the post office or forcing everyone into electronic delivery is over. Modern distribution needs flexibility, and TaxBandits delivers exactly that.

“Everything is very customizable to your needs,” Nikita explained when asked about mixing delivery methods. “You can choose some postal mail, some online access, and some want both.”

The three distribution paths each serve different needs:

  • USPS postal mailing handled entirely by TaxBandits
  • Electronic recipient portal requiring just an email address
  • Both options for recipients who want backup

The electronic portal solves a critical compliance issue. The IRS requires formal consent for electronic delivery, so you can’t just email a PDF. TaxBandits automates this. Recipients receive a secure link, enter a PIN for verification, and provide documented consent.

If someone ignores that email, the system tracks everything. You can see who consented, who declined, and who never responded and then handle postal delivery for the holdouts.

For returning recipients, the portal builds value over time. “If you file for that same recipient next year, they’ll use the same link, and they’ll access all of the documents from the same portal,” Nikita noted. Recipients get their own organized tax document archive without any extra work from you.

State filing adds another compliance layer, but TaxBandits simplifies this, too. The platform tells you exactly what each state requires:

  • States requiring direct filing (you handle separately)
  • Combined Federal/State Filing participants (automatic forwarding)
  • States requiring no 1099 filing

Throughout the process, you get real-time status updates so you can see which forms were transmitted to, received by, and accepted by the agency. For postal mail, statuses are submitted to USPS and en route to the recipient. When a client claims they never received their form, you have documentation. After transmission, watermarks disappear from your copies, and you can reprint professional versions anytime.

For firms with multiple preparers, the platform offers even more control through team management features.

Scaling with teams and support

Larger firms need more than just bulk upload; they need workflow management. TaxBandits’ team management features let you maintain control while delegating the actual work.

The system offers three permission levels:

  1. No roles: Any team member can prepare, approve, and transmit
  2. Two roles: Preparers create forms, approvers review and transmit
  3. Three roles: Preparers create, approvers review, transmitters handle payment and filing

You can also create location-based groups. Nikita shared an example. “Say you have a group in Indiana and a group in Tennessee. Anytime you add a new payer and assign them to the Tennessee group, then all of the team members included in the Tennessee group have access to that payer.”

Support is critical when things get complex. During busy season, TaxBandits extends hours to 8 a.m. to 8 p.m. Eastern. They offer phone, email, and chat support, plus an AI assistant that pulls from both their knowledge base and IRS guidelines.

The platform’s YouTube channel provides step-by-step videos for specific workflows. For Sage Intacct users who asked about integration, Nikita recommended checking their channel for detailed walkthroughs showing the complete process from Sage to TaxBandits.

Pricing works on a credits system with bulk discounts. Buy more credits upfront, pay less per form—and credits never expire. As Nikita confirmed when asked about rollover, “Your credits will never expire. So if you want to purchase for the next five years now and get the best price we can give you, go for it.”

Making next year easier starts now

The strategies demonstrated in this webinar show a fundamentally different approach to information returns. TaxBandits treats compliance as a year-round process rather than a January panic.

The IRS’s push toward e-filing mandates and stricter validation isn’t slowing down. The IRIS system is just the beginning of modernization efforts that will continue tightening requirements. But the webinar demonstrated real workflows you can adopt immediately, from template imports to electronic W-9 collection to role-based team permissions.

Ready to transform your 1099 and W-2 workflow? Watch the full Earmark Expo webinar to see TaxBandits in action, including the complete demo of bulk uploads, error checking, and team management features. The platform offers over 70 tax forms beyond just 1099s and W-2s, making it a comprehensive solution for year-round compliance needs.

The End of Data Entry and What It Means for Your Tax Practice

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Elizabeth Beastrom left public accounting 30 years ago because she was sick of rekeying data into tax returns. Now, as President of Tax and Accounting Professionals at Thomson Reuters, she works to make sure no accountant has to do that mind-numbing work ever again.

“I was a lazy CPA,” she admits with a laugh during this episode of the Earmark Podcast. “I didn’t want to spend my time doing work that I didn’t think was necessary.”

In this conversation with host Blake Oliver, Elizabeth and Kirat Sekhon, Thomson Reuters’ Head of Technology, map out their vision for automating the entire tax workflow, from gathering documents to delivering returns. They want listeners to know that AI-enabled firms are going to outcompete everyone else, and the shift from compliance to advisory isn’t optional anymore.

Why Tax Firms Can’t Keep Doing Things the Old Way

The numbers tell the story. Fewer people are taking the CPA exam while more accountants retire every year. Meanwhile, tax complexity keeps growing, which means more demand for services with fewer people to do the work. Throw in private equity firms buying up practices and pushing for efficiency, and you’ve got a perfect storm.

But it’s not just about headcount. The new generation of accountants expects modern tools that actually work together—not the clunky desktop software their predecessors put up with.

“They expect to use intuitive and connected tools,” Kirat explains, “so they have a better experience while they deliver value to their customers.”

So why has tax software stayed stuck in the desktop era while cloud accounting tools have taken off? Kirat points to two reasons. First, tax calculations are hard to get right, and once you build something that works, nobody wants to break it. Second, accountants themselves haven’t pushed for change. When you’re working 80 to 100 hours during busy season, the last thing you want is to learn new software.

“The term SALY—same as last year—still comes through,” Elizabeth notes. “You found a way to do it and you like to replicate that. Change is hard, especially when you have to introduce that to the firm when you’re working 80 to 100 hours a week.”

But resistance to change is becoming dangerous. Elizabeth’s own exit from the profession 30 years ago shows what happens when the work becomes too tedious. Back then, she discovered she loved the advisory side, including talking to clients, understanding their businesses, and making recommendations that actually helped them improve. But she was stuck doing data entry.

“I would spend time talking to my customers,” she recalls. “Some of my best inputs came from the people in accounts payable or accounts receivable. I would get a detailed understanding of their process.” But then she’d have to go back to rekeying tax data, and the contrast was too much.

Building the “Bookends” Around Tax Prep

Thomson Reuters isn’t trying to fix one piece of the tax workflow; they’re automating the whole thing. Their strategy focuses on creating what Elizabeth calls “strong bookends” around their core tax engines (GoSystem Tax, CST, and UltraTax).

The front bookend came through their acquisition of SurePrep three years ago. Practitioners dump all their client documents into the system, and SurePrep automatically classifies them, pulls out the relevant numbers, creates a binder for review, and fills in the tax software. No more manual data entry.

“That’s a huge time savings when you don’t have to spend time doing all of that manual data entry,” Kirat says, “and they can actually focus on the return.”

The back bookend arrived with SafeSend, acquired earlier this year. It handles return delivery, e-signatures, and payment collection, eliminating what Elizabeth remembers as the nightmare of printing, mailing, and faxing documents back and forth 30 years ago.

What’s different about Thomson Reuters’ approach is they’re keeping these tools open to work with competitors’ software too, not just their own tax products.

“It is an open, curated ecosystem,” Elizabeth emphasizes. “If customers find value in part of their workflow, we want to make sure we connect to it.”

Beyond just automating existing steps, they’re trying to eliminate unnecessary work entirely. Take the client questionnaire—that paper organizer Blake’s mom still fills out by hand every year. Thomson Reuters wants to “kill the questionnaire” by using AI to pre-populate information from prior returns and only ask for what’s actually new or missing.

The next frontier is what Kirat calls “agentic AI,” systems that don’t just handle one task but orchestrate entire workflows. These AI agents can use multiple Thomson Reuters products in sequence, making decisions along the way to get a return from start to finish with minimal human intervention.

But everything the AI does needs to be auditable. Kirat stresses that any AI handling tax work must show exactly what decisions it made and why.

“Our customers expect the work product of an accountant to be 100% accurate,” she explains. “Without providing that audit log with the decisions and choices and confidence levels, we’re missing the mark.”

Blake agrees enthusiastically, sharing his frustration with current AI tools that don’t show their reasoning. “I want to know why it matched this transaction,” he says. “There’s an AI conversation for each one of these transactions. Why not give that to us?”

The Shift to Advisory Can’t Wait

If machines can prepare returns faster and more accurately than humans, what exactly are clients paying for? Two-thirds of Thomson Reuters’ customers say they want to shift to advisory services, but most don’t know how to actually do it.

Enter Ready to Advise, launched in June 2024. The tool takes everything from a completed return and analyzes it against potential tax strategies based on that client’s specific situation and goals.

“It will quantify the savings,” Elizabeth explains. “It will ask for more information to get to a range. It will allow you to have that discussion where you can say, ‘Hey Blake, I noticed from your 1120-S filing some potential strategies you should take.'”

Then it walks you through implementing those strategies and produces client-ready documentation. For firms struggling to move beyond compliance, this is huge.

But technology alone won’t fix the business model problem. Clients have been trained to expect strategic advice for free. “I might call my accountant and say, ‘Hey, tell me what this big beautiful bill does for me this year?,’ which is code for don’t charge me for this,” Elizabeth says, capturing the conundrum perfectly.

That’s where Practice Forward comes in. It’s Thomson Reuters’ tool for helping firms understand their worth and develop advisory pricing models. The goal is shifting from hourly billing for returns to year-round advisory subscriptions.

Ready to Advise also solves a talent problem. Traditionally, you needed years of experience before you could offer meaningful tax advice. But with AI assistance grounded in Checkpoint’s content (maintained by over 4,500 subject matter experts), newer staff can contribute to advisory work much sooner.

“That junior associate’s experience, paired with all the knowledge that there is available in generative AI today, is incredibly powerful,” Kirat notes.

Blake shares a personal example that drives home the value of advisory over compliance. His tax preparer advised setting up a C-Corp to potentially qualify for QSBS treatment, which could save millions in taxes someday.

“I can’t even quantify the value of that,” Blake says. “But that’s why I’m willing to pay thousands of dollars for a tax return. It’s that insight, not the return.”

Meanwhile, DIY tax software keeps getting better. Blake describes doing a business return himself using consumer software with ChatGPT open for research. The same process would have taken hours of manual work just a few years ago.

Firms that stick to just preparing returns are going to get squeezed from both ends.

“AI-enabled professionals and firms, they’re going to outcompete and outperform,” Elizabeth warns, “because they’re going to be able to do it faster, better and get to this advisory, which our clients want.”

What to Do Right Now

So where should a traditional tax firm start? Elizabeth recommends figuring out what you hate doing.

“What are your pain points that you hate to do?” she asks. “There’s a pretty high likelihood that I or a talented person on my team is going to be able to say, ‘This is how we can solve that for you.’”

The technology exists today. SurePrep can handle document gathering. SafeSend can automate delivery. Ready to Advise can help you identify tax-saving opportunities. CoCounsel can answer complex questions using curated, expert-verified content. The audit logs are there to verify everything the AI does.

The harder change is mental: accepting that the compliance work that defined the profession for decades is becoming commoditized, and the future belongs to firms that embrace automation as the foundation for higher-value advisory services.

Elizabeth even suggests bringing these concepts into accounting education to attract new talent. Currently, tax courses focus on rules and calculations rather than strategy. After all, accounting is still “the language of business,” as Elizabeth was told as an undergraduate. The difference is that AI can now handle the grammar and spelling, freeing professionals to focus on telling the story.

The transformation won’t be easy, but it’s not optional. As Elizabeth learned when she left the profession out of frustration with mundane tasks, talented people won’t stick around if the work doesn’t engage them. The good news is that automation finally makes it possible to eliminate the drudgery and focus on what really matters: helping clients succeed.

Listen to the full conversation with Blake, Elizabeth, and Kirat for more insights on preparing your firm for the automated future of tax.