AI-Powered Collections: Introducing Agentic Procedures
December 11, 2025

Webinar: Cash Flow Predictability and Accounts Receivable Automation Trends for 2026

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Is your cash flow predictable? See how AI-driven AR automation creates certainty and helps you plan better.

Cash flow predictability has become the defining metric for finance and accounting leaders heading into 2026. Without it, you’re flying blind — unable to forecast confidently, manage capital costs effectively, or make strategic investment decisions with certainty.

Manual accounts receivable (AR) processes can’t deliver the visibility and control needed to eliminate surprises and stabilize working capital. AI-driven AR is already powering the predictability and efficiency that top-performing teams at leading finance organizations rely on today.

In a recent Controllers Council roundtable, finance executives Christine Gu, SVP Finance & Chief Accounting Officer at Clarify Health Solutions, and Michael Mance, VP Financial Operations at Dialysis Care Center, joined Billtrust CPO Lee An Schommer to discuss exactly that – using accounts receivable operations to make working capital more stable, reliable, and predictable.

The conversation went far beyond predictive AI trends, digging into innovation expectations, the metrics that separate high-performing AR functions from the rest, and how actual team structures support digital transformation and predictive finance.

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How Lean Teams Actively Manage Cash Conversion Cycles

Webinar panelists Christine Gu and Michael Mance run tight ships by necessity, not choice.

Mance oversees roughly 50 people across accounting, finance, FP&A, and tax for multi-region healthcare provider Dialysis Care Center. His AR department? About six people handle billing and collections. His priority is eliminating billing errors upfront. “It’s very important to ensure that billing is accurately done on the initial onset, because every rebill extends DSO,” he said.

Gu’s team at Clarify Health leverages offshore resources but operates on a similar principle: lean requires proactive. “We partner closely with our customer success team and legal team to align invoicing collections and contract terms,” she explained. “We embed AR tracking mechanisms into our broader revenue operation process. So, we’re not just reactive, but actively managing cash conversion cycles.”

Cash Flow Predictability: How AR Performance Metrics are Shifting

The session kicked off with a poll that yielded unsurprising results: 98% of the audience agreed that effective cash flow management is a top priority. Recent research confirms this sentiment. However, how that priority translates into daily AR performance metrics varies.

The big takeaway: DSO is table stakes. In the age of predictive AI analytics, other AR performance metrics take center stage.

DSO is Still King, but Cash Flow Predictability Metrics are Rising in Importance

Aside from DSO, here’s what else the panelists focus on:

  • Cash Conversion Cycle: Understanding the working capital dynamics between billing timing and payment timelines. 
  • Collection Forecast Accuracy: Christine Gu treats this with the same rigor as revenue forecasting: “We take a rolling cash forecasting approach, looking 13 weeks 13 weeks out on a weekly basis, and then tying that to pipeline velocity or bookings conversion.” 
  • Billing-to-Invoice Lag: A critical efficiency KPI, especially for milestone-based contracts. “This is key for us to understand how long it takes to operationalize a closed deal,” Gu noted. 
  • Unbilled AR: Essential for professional services companies or healthcare where services are rendered but not yet invoiced. 

Arriving at Predictive Finance: Accounts Receivable Automation

Here’s where it gets interesting. To arrive at the milestone of accurate cash flow predictability, AR operations must digitally transform. However, when polled, the vast majority of attendees have not reached full maturity in their AR automation journey.

The conclusion: Most AR teams have work to do before predictable cash flow can become a reality.

Why the maturity gap? Lee An Schommer pointed out that invoicing automation is most mature because it’s a function that lives in the ERP system. However, accounts receivable collections functions are typically still run on spreadsheets and manual email procedures.

Her advice: Don’t boil the ocean. “There’s no one right answer. It depends on what’s going on with your business. Companies may start by automating cash application, credit, and collections functions. First, they figure out what they want to improve. They set a specific target and create an AI sandbox where they work a process, and then they compare performance metrics to prove the value of their AI solution.”

Explore Billtrust’s collections automation capabilities.

AI in Accounts Receivable: Build It into the Fabric of Daily Work

The buzzword of the century remains AI, but we are seeing a shift toward practical implementation. A webinar poll showed that while only 18% of attendees have fully implemented AI, 55% are currently exploring or evaluating it. That demonstrates the excitement for AI’s advanced automation and predictive capabilities.

Gu shared a candid look at her AI roadmap. While her team is already using AI for FP&A modeling and expense analysis, applying AI in accounts receivable is the next frontier. She is specifically looking for tools that can handle tailored collections outreach at scale and predictive collections.

During the panel, Lee An Schommer introduced the concept of AI Everyday. The industry is moving past the novelty phase where AI is a separate project. It’s about building it into the fabric of the daily workflow. “Instead of pulling reports, I can ask Billtrust Autopilot questions like ‘Give me my top 10 customers that have recently flipped their payment methods from ACH to card,’” she explained.

When AI works to improve collections forecast accuracy, it also works to improve the precision of cash flow predictions. The practical example she gave: If a customer pays at 45 days religiously, maybe you don’t contact them with a payment reminder anymore. But someone who’s consistently late? They get prioritized. AI stack ranks your list of collections actions based on behavior patterns, not just outstanding invoice balances.

Predictive Cash Flow: Overcoming Implementation Paralysis

A common concern raised during the Q&A was the fear of lengthy implementations. One attendee asked about timelines, recalling ERP integration rollouts that dragged on for years.

Schommer was firm: “The days of implementation taking years are over. You should expect more. Clients should demand that implementation be completed in matter of a few months – not years.”

The #1 Barrier to Speed? Data

The speed of implementation is almost always dictated by the state of your data. Schommer advised that if you want to move fast, you need to have a handle on two things:

  1. Clean, accessible data
  2. Clear credit and collections policies

“If you get those two things locked down, your partner should be able to innovate AR fast,” she advised.

2026 Predictions: The Strategic Controller

The panel concluded with predictions for the finance function in 2026. The consensus? The “bean counter” stereotype is officially dead. The future belongs to the “Business Wisdom Thinker.”

  1. Finance Leaders as AI Leaders: Christine Gu predicts a shift in skill sets. Finance teams will become product owners for a lot of internal technologies and AI strategies. Thus, teams will need to configure tech stacks and connect AI tools and information. 
  2. Retention through the Elevation of Work: Michael Mance acknowledged the common fear that automation eliminates jobs. He argued the opposite: it saves them. “I think it provides opportunities to move away from mundane tasks and make their work more efficient. This leads to better employee retention,” he said. 
  3. The Controller as Cash Strategist: Gu believes the controller will evolve into a cash strategist position. Controllers will increasingly manage cash flow levers like renewals and billing, understanding how they trigger cash acceleration. 

Why Cash Predictability Matters More Than Ever

Christine Gu framed it clearly when asked why AR automation and cash flow are a priority versus other functions:

Michael Mance echoed this, adding that the downstream impact that AR efficiency is having on the entire balance sheet: “Liquidity, the cost of capital, and getting cash receipts in, are obviously very important. Then you can manage your buyers’ payments on the flip side much easier.”

The tools to make cash flow predictable exist. The question for 2026 is how fast you can start using them.

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Frequently asked questions

What is the role of AI in accounts receivable for 2026?

AI is shifting from a novelty to a practical tool embedded in daily workflows. It allows for predictive collections, tailored outreach, and dynamic credit management, helping teams prioritize actions based on customer behavior rather than just balances.

Automation reduces the gap between invoicing and payment by eliminating manual errors and speeding up processing. It provides real-time data on cash conversion cycles and billing-to-invoice lags, allowing finance leaders to forecast cash availability with greater accuracy.

Clean, accessible data is the number one requirement for fast implementation. Without accurate data and clear policies, automation projects can stall; however, with organized data, modern implementations can be completed in a few months rather than years.

Beyond DSO, finance leaders track the Cash Conversion Cycle, Collection Forecast Accuracy (rolling 13-week forecasts), and Billing-to-Invoice Lag to understand operational efficiency and capital dynamics.

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