The collections landscape is undergoing a fundamental architectural shift that determines whether your AR investments produce linear efficiency gains or compounding ROI as volume scales. Traditional automation uses static workflows and predefined templates, while agentic collections use AI agents to automate and coordinate collections outreach across channels while escalating exceptions and disputes when human attention is appropriate. Understanding this distinction is critical for B2B sellers who want to reduce DSO, improve recovery rates, and preserve customer relationships simultaneously.
Rules-based automation represents the first generation of accounts receivable technology that moved businesses beyond spreadsheets and manual tracking. These systems use static workflows that route orders matching predefined templates and escalate exceptions to humans for resolution.
Traditional automated collections follow predictable patterns:
The value proposition is straightforward: reduce manual data entry, ensure consistent follow-up timing, and create audit trails for compliance. Most ERP systems include basic dunning functionality, and dedicated AR automation software extends these capabilities with better reporting and workflow customization.
Rules-based systems deliver real efficiency gains for organizations moving from manual processes:
However, rules-based systems can still create significant manual work when disputes, unusual payment behavior, or other exceptions fall outside predefined workflows.
Agentic AI represents a different approach to collections automation, allowing AI agents to coordinate outreach, respond to buyer behavior, log interactions, and escalate situations that require additional review.
A defining characteristic of agentic collections is more adaptive handling of collection workflows. Resolve Pay's agents can:
This creates a different operational profile. Traditional automation requires additional staff as exception volume grows. Agentic systems can handle more collection volume with existing resources by automating routine touchpoints and adapting to buyer responses.
The gap becomes clear when comparing how each approach handles the same scenario:
Scenario: Buyer disputes invoice due to missing PO reference
Rules-Based Response:
Agentic AI Response:
The efficiency difference becomes more meaningful as transaction volume grows. Rules-based systems primarily automate predefined scenarios, while agentic approaches can adapt sequencing and communication based on buyer responses while escalating situations that require additional judgment.
The application of AI in finance extends beyond simple automation into predictive analytics and adaptive decision-making. Modern B2B collections software leverages machine learning to anticipate payment behavior and optimize outreach strategies.
AI credit engines analyze thousands of data points to assess buyer behavior patterns:
This analysis enables proactive collection strategies. Rather than treating all 30-day past-due invoices identically, AI systems identify which accounts need immediate attention versus which will likely self-cure.
Resolve Pay's AI Credit Engine evaluates buyer creditworthiness using AI-supported underwriting and business data, with decision timing depending on the buyer and verification requirements. Separately, Resolve Pay's agentic collections capabilities coordinate outreach across email, SMS, voice, and the payment portal, with sequencing and channel use adapting to buyer responses.
The evolution from basic automation to AI-powered collections follows a clear progression:
Level 1: Scheduled Automation
Level 2: AI-Enhanced Workflows
Level 3: Agentic Execution
The progression from scheduled automation to AI-supported and agentic collections can increase the amount of collection activity handled automatically while allowing finance teams to concentrate on higher-value exceptions and customer situations.
The historical arc of AR collections reveals why current approaches often underperform expectations. Manual processes created inconsistency and scale limitations. Rules-based automation addressed consistency but created new bottlenecks at exception handling.
Each generation of AR technology solved specific problems while revealing new limitations:
Manual Era (Pre-2000s)
Basic Automation (2000-2015)
Cloud AR Platforms (2015-2022)
AI-Enhanced Tools (2022-2024)
Agentic AI (2024+)
The shift to agentic AI fundamentally changes the economics of collections. Organizations that previously needed additional staff for every increment of revenue growth can now process higher volumes through automated workflows that adapt to buyer behavior and escalate exceptions appropriately.
For B2B sellers offering net terms, this evolution matters enormously. Extended payment periods create more touchpoints where exceptions can occur. The faster and more autonomously those routine touchpoints are handled, the better the cash conversion cycle performs.
Understanding when each approach fits best requires examining their operational characteristics across multiple dimensions.
Traditional automation works well in specific contexts:
For businesses matching these criteria, rules-based systems like basic ERP dunning or entry-level AR platforms deliver solid ROI. The key is recognizing when you've outgrown these capabilities.
Agentic AI becomes valuable when:
Resolve Pay's agentic collections platform addresses these scenarios with multi-channel automated sequences including email, SMS, and voice AI, plus intelligent escalation based on buyer response patterns.
Days Sales Outstanding (DSO) remains the critical metric for AR performance, directly impacting working capital availability and cash flow predictability. The connection between collection approach and DSO outcomes is measurable.
DSO reduction strategies vary by automation tier:
Rules-Based Approach
AI-Enhanced Approach
Agentic AI Approach
The cash flow impact of DSO reduction can be substantial. Reducing the average number of days required to collect receivables can release working capital that would otherwise remain tied up in unpaid invoices, supporting needs such as inventory purchases, operating expenses, or reduced reliance on external financing.
Resolve Pay's AR automation platform provides real-time dashboards showing DSO, aging buckets, and portfolio health. Combined with agentic collections capabilities, sellers gain both visibility into AR performance and the automated execution power to improve it.
Implementing agentic collections requires thoughtful integration with existing financial systems. The technical architecture determines how effectively AI agents can access the context needed for informed decision-making.
Successful agentic deployments connect multiple data sources:
Core Integrations Required
Effective collections automation depends on keeping invoice and payment information synchronized with core financial systems so outreach reflects current account status.
Resolve Pay supports integrations with major platforms including Shopify, BigCommerce, Magento, QuickBooks Online, Xero, Sage Intacct, and NetSuite, along with API-based implementations. Integration functionality and synchronization behavior vary by platform and configuration.
Advanced collections platforms can combine several capabilities:
Resolve Pay combines these capabilities with ERP, accounting, ecommerce, and API integrations, with functionality depending on the system and implementation.
A common concern about automated collections is the potential to damage customer relationships through impersonal outreach. Agentic AI can actually support relationship preservation when properly configured.
Not every collection scenario should be handled autonomously. Effective agentic systems recognize situations requiring human judgment:
The key is that AI can handle routine collection activity at scale, freeing human collectors to focus on strategic accounts, disputes, legal matters, and other situations where judgment adds genuine value.
Resolve Pay's agentic collections approach preserves customer relationships through several mechanisms:
This approach differs from traditional factoring by keeping Resolve Pay's collection workflows integrated with the seller's broader credit-to-cash process. Sellers can use configurable, branded communication while benefiting from automated execution.
The business case for agentic collections extends beyond operational efficiency into strategic competitive advantage.
The financial impact spans multiple dimensions:
Direct Cost Reduction
Revenue Enhancement
Risk Mitigation
For B2B sellers, collection capability directly affects competitive positioning. The ability to offer Net 30/60/90 terms confidently, knowing that AI agents will handle follow-up professionally and effectively, enables sales strategies that competitors with manual AR cannot match.
Resolve Pay combines net terms financing with agentic collections to create a complete solution. Sellers can offer extended payment terms to approved buyers, receive advances on invoice value within 1-2 days, and rely on AI-powered collections to manage the buyer payment process. This integrated approach, originated as a B2B payments spinout from Affirm, delivers technology sophistication in a platform accessible to mid-market B2B sellers.
The competitive advantage compounds over time. As Gartner predicts, at least 15% of day-to-day work decisions will be made autonomously through agentic AI by 2028. Organizations building these capabilities now will have years of learned business logic embedded in their systems while competitors are still implementing basic automation.
Resolve Pay's agentic collections integrate with credit decisioning, invoicing, and payment processing to help B2B sellers support growth while managing cash flow.
Key capabilities include:
By automating routine collection workflows, finance teams can support higher transaction volumes without proportional headcount increases while preserving professional customer relationships.
Resolve Pay also reduces the complexity of managing separate vendors for credit checks, invoicing, collections, and payment processing. B2B sellers can offer competitive payment terms, automate collections, and maintain the customer relationships that support long-term revenue.
Automated collections use static rules to trigger predefined actions, such as sending a reminder email on Day 7 of an unpaid invoice. When something falls outside the rules, the system escalates to a human. Agentic collections can adjust workflows based on buyer responses and account context, coordinating multi-channel outreach while escalating exceptions when appropriate. The practical difference is how the systems respond to changing situations.
AI agents can maintain context across collection interactions and adjust outreach based on buyer responses. For example, Resolve Pay coordinates email, SMS, voice, and payment-portal interactions, logs touchpoints automatically, and can pause or escalate workflows when a payment, dispute, or other buyer response requires a change in the collection sequence.
Resolve Pay's agentic collections are designed to support professional, relationship-conscious communication while automating routine collection outreach. The system uses configurable, branded communication that maintains business tone. Human interaction becomes necessary for strategic accounts, complex negotiations, and situations requiring judgment beyond programmed parameters, but these represent a smaller fraction of total collection interactions.
AI agents can use account status, payment information, buyer responses, communication history, and other available account context to coordinate collection outreach. Resolve Pay also uses separate AI-supported credit decisioning to assess buyer creditworthiness. This analysis enables predictive prioritization, identifying which accounts need immediate attention versus which will likely self-cure. Channel preference data helps determine whether email, SMS, or voice outreach will be most effective for each buyer.
Implementation timelines vary based on integration requirements, data quality, workflow configuration, and the financial systems involved. Businesses should evaluate how invoice data, payment status, buyer information, communication channels, and escalation rules will connect with the collections platform. Resolve Pay supports integrations with major ERP, accounting, and ecommerce systems, along with API-based implementations for businesses with custom requirements.
This post is to be used for informational purposes only and does not constitute formal legal, business, or tax advice. Each person should consult his or her own attorney, business advisor, or tax advisor with respect to matters referenced in this post. Resolve assumes no liability for actions taken in reliance upon the information contained herein.