QuickBooks is an accounting platform that supports dunning through automated payment reminders in accounts receivable. Those reminders follow template-based emails and preset timing rules, giving finance teams a consistent way to follow up on overdue invoices. As invoice volume grows, many AR teams need more than outbound reminders because late payment is often tied to issues such as missing POs, disputes, pricing questions, or invoice queries. Accounts receivable AI agents automate those high-volume billing and collection conversations in the finance inbox. Paraglide integrates with QuickBooks and provides AI agents for B2B finance teams to help them get paid faster and save time on repetitive, manual work.

On 24 March 2026, the UK government published a late payment reform package aimed at large businesses that pay smaller suppliers slowly. The key proposals are a 60-day hard cap on payment terms, mandatory statutory interest at 8% above the Bank of England base rate, and stronger powers for the Small Business Commissioner to investigate poor payment practices and fine persistent offenders. This is not yet a fully implemented law. It is a government reform package and consultation response setting out what ministers intend to legislate for. Although the reforms are not yet fully implemented, finance teams already have enough detail to start assessing where payment processes may come under pressure.

The next phase of finance transformation will not be defined by better dashboards or another round of system change. It will be defined by whether finance can improve execution in the parts of the process where work is still manual, fragmented, and difficult to scale. This is where agentic AI fits. In many organisations, the real pressure sits between invoicing and payment, where queries, disputes, deductions, and other exceptions take up time, delay cash, and create more work across finance teams. Used properly, it helps finance deal with that work more consistently and with less manual effort.

Debtor days, also known as Days Sales Outstanding (DSO), measures how long it takes to collect cash after an invoice is issued. It is one of the clearest indicators of how efficiently a business converts revenue into cash. This guide explains the debtor days formula, shows a step-by-step example, and outlines the operational issues that usually push DSO higher. It also covers common calculation mistakes, why a single headline number can be misleading, and what finance teams can do to bring debtor days down.

Discounts and allowances are usually reductions to revenue because they reduce the amount a customer actually pays. That means they should normally sit between gross sales and net sales, not in operating expenses. The key exception is when the payment is clearly for a distinct service, such as advertising or shelf placement, in which case it may be treated as marketing expense. The article explains this distinction, shows where these items belong in the P&L, walks through a practical example, and highlights the common mistakes that lead to weak net sales and margin reporting.

Most AR teams are still handling billing queries manually in shared inboxes or ticketing tools, even though this work often absorbs multiple FTEs and directly delays payment. AR helpdesk automation uses AI agents to read inbound billing emails, pull the right invoice or payment context, resolve routine queries automatically, and route only the exceptions that need human judgement. Unlike generic ticketing systems or legacy AR platforms built mainly for outbound reminders, purpose-built AI agents can handle the actual work of billing query resolution at scale. That matters because unresolved invoice questions, PO issues, disputes, and statement requests are often the real reason cash is delayed. By resolving these issues faster, finance teams can reduce manual workload, improve response times, and lower DSO.

Discounts and allowances can look simple on paper, but in practice they’re one of the most common reasons finance teams end up debating net sales vs gross sales, margin accuracy, and whether something belongs in marketing expense. In this article, you’ll learn what discounts and allowances really mean in accounting terms, how they should flow through the P&L (especially in FMCG), and when they should not be treated as marketing.

Promotional allowances sit at the centre of FMCG revenue management because they affect net sales, gross margin, accrual accuracy and cash collection at the same time. They are often negotiated as commercial growth levers, but the accounting treatment is more exacting than many teams expect. Most promotional allowances reduce revenue rather than sit in operating expense, and getting that distinction wrong can misstate both net revenue and profitability. They also create operational pressure inside Accounts Receivable. Short payments, billbacks, scan-down claims and co-op deductions all have to be validated, coded, accrued and resolved. When they are not, deductions age, disputes drag on and DSO rises. This guide explains what promotional allowances are, how they should be accounted for, how they differ from other forms of trade spend, and how FMCG finance teams can manage the deduction and collections impact more effectively.

DSO, DPO and DIO are three of the most important metrics in working capital management because they show how quickly a business turns trading activity into cash. DSO measures how long it takes to collect from customers, DPO measures how long the business takes to pay suppliers, and DIO measures how long cash sits in inventory before stock is sold. Together, these metrics determine the cash conversion cycle and give finance teams a clearer view of operating cash flow, liquidity and capital tied up in day-to-day operations. They are useful not just for reporting, but for diagnosing where cash is getting stuck across receivables, payables and inventory. For AR and finance operations teams, DSO is often the most immediate lever. Slow collections are rarely just a chasing problem. They are often caused by billing queries, disputes, missing remittance, weak follow-up discipline or poor finance inbox management. Understanding DSO, DPO and DIO properly helps finance leaders connect operational friction to cash performance.

Finance operations teams are being asked to do two things at once: protect control and move faster. That is getting harder as invoice volumes rise, customer queries pile up, and more of the order-to-cash process gets pushed into shared inboxes, spreadsheets, and disconnected workflows. The pressure is most visible in accounts receivable. Collections stall because a customer is waiting for a copy invoice, a corrected billing contact, a missing PO number, a remittance clarification, or a dispute response. None of that sits neatly inside the ERP. It sits in email threads, handovers, notes, and manual follow-ups. That is why many finance teams still struggle to improve DSO even after investing in billing systems, dunning tools, or dashboards. AI agents are starting to change that. Not by replacing the finance function, and not by simply drafting better emails, but by taking ownership of repetitive operational work across the finance inbox, collections follow-ups, dispute handling, promise-to-pay tracking, cash application support, and credit workflows. For finance operations leaders, the opportunity is practical: reduce manual workload, tighten execution, and remove the day-to-day friction that delays cash collection.

Order-to-cash automation has evolved in stages. RPA handled structured data tasks and legacy platforms automated outbound payment reminders, but neither addressed the conversations. Inbound billing queries, collections follow-ups, dispute notifications, and remittance questions still land in a shared inbox and get handled manually, one email at a time. This was not possible to automate with templates. Agentic AI closes this gap. Unlike RPA or reminder platforms, AI agents read unstructured emails, understand intent, retrieve live account data, reference full conversation threads, and act across the entire O2C cycle, from invoice inquiry management and collections to cash application and credit decisioning. They can automate replies to invoice queries, autonomously take actions across systems, and manage end-to-end collection conversations. Paraglide is the only AI-native agentic AR platform built for the full O2C conversation. Customers reduce DSO by an average of 34%.

Many AR teams only automate the outbound side of collections. Reminders go out automatically, but invoice queries, disputes, statement requests, missing PO issues and payment follow-ups still sit with the AR team. That is often where payment delays begin. Teams can invest in AR automation and still spend too much time in the finance inbox handling work manually. The real issue is not just sending reminders, but clearing payment blockers quickly. AI agents help by handling routine queries and passing on more complex cases with the right context. Paraglide covers both outbound remind

Deductions and disputes are major blockers to getting paid in B2B, especially across FMCG, retail, wholesale, logistics, and manufacturing. Most AR teams manage them through a shared inbox, where claims get buried under routine queries, sit unresolved, and end up blocking payments far larger than the disputed amounts. Resolving these issues often depends on input from teams outside AR—such as sales, operations, or logistics—and without proper tracking, requests easily fall through the cracks. Traditional pre-AI tools improve visibility but don’t do the work, leaving teams to manually triage, input data, and chase follow-ups. AI agents change this by automating the entire process—from reading and routing to summarising, challenging, and resolving claims. By handling routine queries, they free AR teams to focus on the disputes that truly block cash. Paraglide stands out as the only AI-native AR platform that not only tracks deductions and disputes, but actively resolves them.

Invoice inquiry management is the day-to-day work of handling customer billing emails, from invoice copy requests and missing PO numbers to statement requests, disputes, and payment queries. Most finance teams still manage this manually in a shared inbox, which is why it so often becomes a bottleneck. This article explains why that work has a bigger impact on collections than most AR software accounts for, and how agentic AI solutions like Paraglide improve invoice inquiry management with accounts receivable AI agents that automate the finance inbox.

Odoo is an ERP that helps finance teams manage the core parts of accounts receivable, including invoices, outstanding balances, and scheduled follow-ups on overdue accounts. Many overdue invoices are delayed by billing questions, disputes, missing PO numbers, deductions, or requests for documentation, all of which usually end up being handled manually in the finance inbox. This article explores how AI agents for accounts receivable work with ERP systems like Odoo to help finance teams manage dunning, disputes and invoice queries better. Paraglide is an Agentic AI solution that integrates with Odoo to automate that layer of work, including payment reminders, replies, invoice queries, disputes, deductions, and other conversations that block payment.

Shared Services has spent years improving efficiency through ERP systems, offshoring, workflow tools and robotic process automation. Those investments have helped standardise transactions, lower costs and strengthen control. Even so, a large share of daily work still depends on people reading emails, checking several systems and manually resolving routine service issues. That is why agentic AI is gaining attention. Its value is not simply that it automates tasks, but that it can help handle whole service cases under defined rules. For Shared Services leaders, that has implications for service quality, cost-to-serve, team design and governance.

Collection rate measures how effectively a company converts invoices into cash during a defined period. For finance teams, it provides a direct view of how well collections are performing and whether overdue receivables are likely to increase. Unlike metrics such as Days Sales Outstanding (DSO), which measure the average time it takes to collect payments, collection rate focuses on the proportion of invoices that are actually recovered. When tracked consistently, it helps finance teams identify early signals of payment delays, disputes or weakening credit control. This guide explains how to calculate collection rate using the most common formulas, how to interpret the result in a real accounts receivable workflow and which reporting mistakes frequently distort the metric.

Remittance parsing is the process of extracting and interpreting remittance advice so payments can be matched to the correct open invoices before cash is applied. When this is done manually, finance teams spend too much time searching inboxes, reviewing attachments, chasing missing references, and working out how deductions, short-pays, and credit notes should affect allocation. That slows cash application, increases unapplied cash, and creates extra work across receivables. AI agents are useful here because they can understand remittance details in context rather than simply reading text from a document. Paraglide is an agentic AI platform that supports this process by identifying remittance advice in the finance inbox, extracting the relevant payment details, checking them against open invoices, and helping finance teams move the work forward faster.

Deductions are one of the most persistent operational challenges in the Order to Cash (O2C) process. When customers pay less than the invoiced amount, finance teams must determine whether the deduction is legitimate, investigate supporting evidence and either recover the remaining balance or approve the claim. For many organisations, this process remains highly manual. Deductions arrive through shared finance inboxes, customer portals, remittance files or ERP exceptions, and Accounts Receivable teams often spend significant time sorting emails, gathering documents and coordinating with internal teams before a case can be resolved. As deduction volumes increase, the impact becomes visible in delayed cash collection, higher Days Sales Outstanding (DSO) and increased operational workload across finance and shared services teams. A structured deduction process improves visibility, reduces investigation time and prevents revenue leakage. Increasingly, finance organisations are introducing automation and AI agents to handle the repetitive administrative work involved in deduction management while enabling AR teams to focus on investigation and resolution. This guide explains how deductions arise in the O2C process, how the deduction workflow operates in practice, the most common deduction categories, the metrics finance leaders should track and how automation can improve deduction resolution and working capital performance.

Inventory valuation determines how businesses assign cost to goods sold and to the inventory that remains on the balance sheet. The method used influences profit reporting, tax liabilities, working capital levels and how efficiently capital is deployed across the business. The most widely used inventory valuation approaches are First-In, First-Out (FIFO), Last-In, First-Out (LIFO) and the Weighted Average Cost method. Each method determines which inventory costs are recognised when products are sold and which costs remain recorded as inventory. Because inventory is usually one of the largest current assets on a company’s balance sheet, valuation choices affect financial statements and operational metrics such as gross margin, working capital and return on capital employed. Finance leaders therefore, need to understand not only how these methods work, but also how they influence financial performance, reporting transparency and capital efficiency. This guide explains the main inventory valuation methods, how they affect financial statements and how businesses can choose an approach that aligns with their operating model and financial objectives.

Accounts Receivable salary in the UK varies significantly depending on seniority, revenue scale, industry complexity and operational responsibility. In 2026, the gap between transactional AR roles and strategic AR leadership continues to widen. Entry-level roles typically earn between £24,000 and £32,000. Supervisor roles range from £38,000 to £50,000. Accounts Receivable Managers generally earn between £50,000 and £75,000 nationally, while Senior Managers and Heads of AR can exceed £100,000 in complex or enterprise environments. Location, billing structure, dispute volume and automation maturity all influence where a role sits within that range.

Trade spend sits at the heart of financial planning and performance for FMCG (Fast-Moving Consumer Goods) companies. It is one of the most complex and largest components of the cost base, frequently representing 10–25% of gross sales and directly affecting revenue, profitability, and working capital. In this article, you’ll learn exactly what trade spend is, how it’s accounted for under modern accounting standards, and how to optimise, allocate, and control trade deductions and disputes for stronger margins.

Credit control is central to cash flow, risk management and customer relationships, yet in many organisations execution remains manual and inconsistent. Spreadsheets, inboxes and individual vigilance often determine whether commitments are tracked, disputes are surfaced, and escalations happen on time. As volumes grow, this model becomes fragile. AI agents introduce structured, system-level discipline into credit control. Operating within defined guardrails, they monitor debtor activity continuously, categorise communications, track promise-to-pay commitments, prioritise risk and trigger consistent follow-up. This reduces reliance on manual coordination while preserving human oversight. Because credit control is data-rich, rule-based and measured by clear metrics such as DSO and ageing, it is particularly well suited to AI-driven execution. Implemented in a phased and controlled way, AI agents strengthen operational consistency, enabling credit teams to focus on judgment and negotiation while routine monitoring and follow-through happen reliably in the background.

Order-to-Cash (O2C) describes the complete flow from when a customer places an order to when cash is collected and recorded. Over time, technology has helped streamline parts of this cycle. ERP systems auto-generate invoices, reminders push out automatically, and dashboards track key metrics. But the biggest ongoing challenge remains the volume of operational work around that cycle, answering invoice queries, handling disputes, matching payments, clarifying PO numbers, and chasing commitments. In 2026, AI agents are automating that operational layer, reading messages, identifying intent, taking action in systems and escalating only when needed. As a result, Order-to-Cash teams spend less time on repetitive work and more time on strategic work.

For modern finance teams, the inbox is not just a communication channel. It is the operational centre of accounts receivable. Invoice queries, disputes, deductions, remittances and payment negotiations all take place in email. Yet traditional shared inboxes centralise communication without structuring it. As volume increases, ownership becomes unclear, prioritisation follows timestamp rather than financial impact, and repetitive billing queries consume valuable collector capacity. Moving to ticketing systems often introduces processes without solving the underlying problem. By embedding AI agents directly into the finance inbox, billing and collections conversations can be triaged, prioritised and progressed automatically. Routine queries are resolved instantly, promise-to-pay dates are tracked systematically, disputes are surfaced early, and follow-ups are triggered without manual intervention.

Credit control remains a critical function within finance teams, directly impacting cash flow, risk management and overall business stability. As economic pressures, late payment risks and regulatory scrutiny increase, demand for skilled credit professionals continues to grow. This guide provides a comprehensive overview of credit control salaries across the UK in 2026, including role breakdowns, regional differences, influencing factors and hiring trends.

Sales ledger control ensures that customer balances in the receivables ledger match the total in the general ledger. Strong control reduces errors, prevents write-offs, and gives finance teams confidence in their numbers. This article explains the basics of sales ledger control, common reconciliation issues, and practical steps to keep accounts accurate, from invoice creation to cash application and month-end close. We also show how AI agents can help automate checks, flag exceptions, and free finance teams to focus on resolving problems rather than hunting for them.

Late payments are one of the most persistent challenges for businesses. Even when clear payment terms are set, invoices are often paid late, placing pressure on cash flow, forecasting accuracy, and working capital. Traditionally, finance teams have managed overdue accounts manually, relying on spreadsheets, diary reminders, and ad hoc emails. This approach is slow, inconsistent, and difficult to scale, often leading to delays, errors, and customer friction. Microsoft Dynamics 365 Business Central is a cloud-based system that centralises business operations, including finance, sales, and customer management. It offers a structured framework for automating payment reminders, known as dunning letters, transforming what was once a reactive administrative task into a systematic, intelligent process. Layering AI agents on top further enhances the process, allowing reminders to be prioritised and tailored based on customer behaviour.

Debt collection in B2B often requires a delicate balance. Handle it poorly, and invoices sit unpaid for weeks or months. Push too hard, and customer relationships suffer, potentially affecting future revenue. The reality is that manual processes in fragmented inboxes, spreadsheets, and inconsistent follow-ups make it difficult for finance teams to strike the right balance. AI agents are changing the game. By managing high-volume billing and payment conversations autonomously, they help businesses recover payments faster, resolve disputes efficiently, and maintain professional, consistent communication with customers.

The cash conversion cycle (CCC) is a key measure of working capital efficiency, capturing how long cash remains tied up in operations from paying suppliers to collecting from customers. Even profitable organisations can face liquidity stress if CCC is not actively managed. This article explains how to calculate CCC, explores the factors that influence it, and highlights common pitfalls to avoid. It also examines international complexities, including currency risk, local payment norms, and regulatory considerations. One of the most effective levers for shortening CCC is reducing Days Sales Outstanding (DSO). AR automation tool, such as Paraglide help finance teams accelerate collections, manage disputes proactively, and track outstanding payments, freeing working capital and enabling finance teams to focus on higher-value tasks. By combining operational improvements with intelligent automation, businesses can improve liquidity, reduce reliance on external financing, and achieve a more predictable and resilient cash conversion cycle.

Working capital is the cash a business has available to fund day-to-day operations and support growth. Challenges like delayed customer payments, excess or mismanaged inventory, and suboptimal payables tie up cash, reduce financial agility, and make it harder to fund strategic initiatives. AI Agents are transforming how finance teams manage working capital by automating repetitive tasks, providing predictive insights, and enabling proactive cash decisions. They help reduce Days Sales Outstanding (DSO), optimise inventory, improve payables timing, and accelerate cash conversion. Organisations using AI consistently report improved efficiency, better cash visibility, and faster decision-making. Solutions such as Paraglide integrate seamlessly into finance workflows, allowing teams to focus on high-value activities while ensuring cash is managed more effectively.

Trade receivables are amounts customers owe a business for goods or services sold on credit. They are recorded as current assets on the balance sheet and play a vital role in managing working capital and cash flow. Keeping track of the money customers owe helps finance teams understand whether the business is getting paid on time and spot any potential cash shortages before they become a problem. While traditional processes focus on invoicing and reminders, AI agents can take this further by handling customer communications, resolving disputes, and managing collections automatically. This reduces the burden on finance teams, speeds up payments, and improves financial predictability.

Dunning is the process of following up on overdue invoices to ensure payment is received. It is a structured workflow that includes reminders, resolving issues that block payment, and escalating when necessary, all while keeping customer relationships professional and consistent. In SaaS companies, dunning works a little differently. Recurring revenue doesn’t always mean cash arrives on time, because unpaid invoices are often stuck in subscription workflows, billing questions, or internal accounts payable processes. Early-stage dunning confirms invoices are received and sent to the right person, while later stages involve more structured follow-ups, escalations, and actions tailored to different customer types. Effective dunning is more than sending reminder emails. Automation handles both routine follow-ups and the more complex tasks that arise when payments are delayed, but AI agents take it further. They can manage incoming emails, resolve disputes, capture missing information, and update systems automatically, making the entire dunning process and collections faster for finance teams.

Finance shared services, particularly order-to-cash (O2C) teams, face constant pressure to scale, reduce cost-to-serve, and maintain high-quality operational control. Even with standardised O2C processes, teams spend a disproportionate amount of time managing invoice disputes, payment follow-ups, claims, deductions, and credit workflows. In 2026, AI agents for O2C and finance operations are emerging as a practical extension of shared services teams. They automate high-volume operational work, handling account queries, following up on commitments, escalating exceptions, and maintaining workflow continuity, allowing finance professionals to focus on decision-making, exceptions, and strategic initiatives.

Working capital management is a critical lever for finance leaders seeking to improve cash flow, operational flexibility, and business resilience. While many organisations focus on a single balance sheet figure, leading finance teams track multiple metrics to identify precisely where cash is tied up, including receivables, payables, inventory, and capital efficiency. In 2026, AI agents are increasingly helping finance teams optimise working capital by reducing delays in collections, resolving disputes, and providing actionable insights without adding headcount. This guide explores the seven key working capital metrics, how to calculate them, practical examples, and how AI agents can improve outcomes—especially by reducing Days Sales Outstanding (DSO).

SAP FI-AR (Financial Accounting – Accounts Receivable) is a core ERP module used by finance teams to manage customer invoices, balances, and receivables at scale, providing the visibility, accuracy, and controls required to run disciplined AR operations. Within SAP FI-AR, dunning letters are formal, structured reminders sent to customers to prompt payment, confirm commitments, or surface disputes as invoices age. Automating dunning in SAP FI-AR enables teams to generate reminders, apply escalation rules, track outcomes, and reduce manual administrative work. When implemented effectively, SAP FI-AR dunning automation delivers consistent customer communication, faster cash collection, improved cash-flow forecasting, and reduced risk of late or missed payments. Paraglide is an agentic accounts receivable automation tool designed to work alongside ERP solutions such as SAP. Paraglide manages two-way dunning communication directly from the finance inbox with AI agents that automate two-way billing and collection conversations to help businesses get paid faster.

Sage is the ERP system of record for many AR teams, managing invoices, customer balances, and ageing. To turn ageing into cash, teams rely on dunning: structured, policy-aligned overdue messages that escalate over time to prompt payment or surface disputes early. Dunning automation inside Sage helps ensure the right message goes out at the right stage, improving consistency and reducing manual effort. But “automation” in practice needs more than scheduled reminders because collections often require two-way conversations, not one-way email sequences. This is where AI agents come in. They extend traditional dunning automation by handling replies, sending segmented and personalised reminders, tracking promises to pay, and automating follow-ups. Paraglide is an agentic accounts receivable automation tool designed to work alongside ERP solutions like Sage. Paraglide automates dunning conversations directly in the finance inbox with AI agents to help businesses get paid on time and reduce DSO.

NetSuite AR module provides tools to manage invoices, customer balances, and overdue accounts across organisations. Dunning letters and reminders in NetSuite formalise communication with overdue accounts, helping to trigger payments or identify disputes. Automating dunning reduces manual effort, ensures consistent communication, applies escalation rules, and enforces late payment charges where applicable. AI agents and automation tools can complement NetSuite, managing replies to the dunning letters, personalising messages at scale, resolving routine billing queries, tracking payment commitments, and removing bottlenecks. Paraglide is an agentic accounts receivable automation tool that works alongside Netsuite, managing two-way dunning communication, managing replies to dunning letters in the finance inbox, escalation logic, and feedback into AR and credit without changing accounting logic or ERP controls.

Dunning software is a type of accounts receivable software that automates the process of collecting overdue payments from customers, typically by sending payment reminders. Legacy dunning tools focus on one-way, time-based reminder emails, which break down as soon as customers reply or dispute payments. Today’s B2B dunning software is conversational and context-aware, designed to resolve payment blockers, not just send reminders. Agentic dunning software personalises collection outreach, automates replies to billing queries, manage replies, tracks promises to pay, and follow up automatically. Paraglide automates two-way billing and collection conversations in the finance inbox, automating and personalising payment reminders, managing replies and follow-ups to reduce manual work, lower DSO, and help businesses get paid on time.

Bad debt, doubtful allowances, and impairments are more than accounting concepts; they are practical levers that allow finance leaders to anticipate risk, protect cash flow, and make informed, confident decisions. These concepts work together as an ongoing credit risk management framework. By understanding how these concepts relate, spotting early warning signals in collection behaviour, and implementing a structured decision-making framework, finance teams can move from reactive write-offs to proactive management. Bad debt is the amount confirmed as uncollectible after reasonable recovery efforts fail, resulting in a write-off and a hit to profitability. Doubtful allowances are a proactive estimate of receivables unlikely to be collected, calculated using ageing, historical defaults, and customer-specific factors, reducing net AR without reversing revenue. Impairments are recognised when a receivable’s recoverable value declines due to credit deterioration, disputes, or customer financial difficulty, often before formal default, aligned with IFRS 9 expected credit loss thinking. Allowances predict portfolio-level loss, impairments flag specific exposures, and bad debt confirms loss once recovery is no longer realistic. Bad debt builds quietly through unresolved billing queries, missing documentation, slow dispute resolution, and broken payment promises. Early warning signs hide in email threads, CRM notes, and support tickets, not financial systems.

AI is not just automation, it spans three distinct approaches: rules-based automation, AI copilots, and AI agents; each suited to different types of work. AI agents represent a shift from assistance to execution, taking actions across systems, completing end-to-end workflows under human supervision and actually doing the work. Finance has adopted AI more cautiously than functions such as engineering, support, and sales. Finance is now well-positioned for agentic adoption, particularly in high-volume, repetitive, and measurable work. The highest-ROI uses of AI agents today are in operational finance, where these conditions are most common. The first and clearest high-ROI use cases are accounts receivable (billing support and collections automation) and accounts payable (invoice capture, coding, matching, and duplicate detection) Real value comes from agentic-native platforms that can safely act within systems, not legacy tools with chatbots rebranded as “AI-powered.”

At 1,000-10,000 invoices per month, AR teams receive 50-150 customer emails weekly - roughly one email for every 20-40 invoices - requesting missing documents, dispute resolutions, and payment confirmations. 60-80% of payment delays are caused by emails, not invoices; ERPs and standard workflow tools cannot manage the conversation layer of accounts receivable. AI-native AR automation converts inbox chaos into structured data: AI agents AR platforms read customer emails, extract promise-to-pay commitments, identify dispute patterns, and sync updates to the ERP, eliminating the manual triage that consumes entire workdays. The impact is measurable: AI-driven AR automation is correlated with 75% of finance teams reporting Days Sales Outstanding (DSO) improvement of 6+ days when AI is part of their receivables stack. Paraglide is a purpose-built Accounts Receivable (AR) software that automates the inbox layer with AI, handling 2-way emails in 100+ languages, retrieving documents, capturing promise-to-pay commitments, and escalating only when human judgment is required.

AR teams managing hundreds or thousands of invoices per month hit a ceiling that process changes alone cannot fix. The constraint is not invoicing or reminder cadence; it is the volume of customer communication required before payment can proceed. Requests for invoice copies, PO validation, dispute resolution, and payment confirmation drive most delays. When these messages sit unanswered in finance inboxes, invoices age even when customers intend to pay. Workflow automation cannot manage inbound AR communication: ERPs and traditional AR tools track balances and send reminders, but they cannot read customer replies, resolve questions, or capture promise-to-pay commitments hidden in email threads. Platforms like Paraglide operate directly inside the finance inbox, using AI agents to manage customer replies, retrieve documents, capture promise-to-pay dates, and escalate only when human judgment is required, removing the communication bottleneck that drives DSO.

Credit management breaks at scale when inbound communication overtakes outbound control: Once AR teams manage hundreds or thousands of invoices per month, delays are driven less by invoicing or reminders and more by unanswered customer emails related to disputes, documentation, and payment confirmation. Most credit management solutions automate reminders, scoring, and reporting, but rely on manual inbox work to resolve inbound queries. In 2026, the most valuable credit management software reduces manual work by automating follow-ups, capturing responses, and updating the ERP without adding AR workload. Paraglide is one of the best credit management platforms for high‑volume AR. It automates two-way customer communication inside the finance inbox, handles over 100 languages, captures promises-to-pay in real-time, and moves commitments into the ERP, targeting the bottleneck that delays payments.

Decreasing DSO is about more than chasing customers faster — it's about building smarter, data-driven, and automated AR workflows. With AI agents managing reminders, resolving issues, and escalating intelligently, finance teams can collect faster, improve cash flow, and maintain strong customer relationships.

Automating B2B collections isn't just about sending reminders faster — it's about creating intelligent, context-aware workflows that mirror what great collectors already do. AI agents now make that possible: they handle routine outreach, track commitments, resolve issues early, and keep humans focused on exceptions. The result is improved cash flow, happier customers, and a finance team that finally scales with the business.

The accounts receivable turnover ratio is a simple but powerful measure of how efficiently a company turns sales into cash. It is directly connected to DSO and free cash flow, making it a key KPI for finance teams. By improving collections processes, monitoring turnover closely, and reducing DSO, companies can unlock cash, strengthen working capital, and reduce financial risk.

Kundreskontra är en central process för alla företag, men den har länge varit tung och arbetsintensiv. Med AI och automatisering kan företag nu frigöra tid, minska DSO, förbättra AR turnover och få bättre kontroll över sina åldersanalyser. Resultatet blir snabbare inbetalningar, starkare kassaflöde och en ekonomiavdelning som kan fokusera på det som verkligen driver värde.

Free cash flow conversion is a vital measure of financial strength because it shows how much of your reported earnings actually makes it into the bank. The biggest drag on FCF conversion is usually working capital, and within that, slow-paying customers. By managing accounts receivable tightly and reducing DSO, companies can unlock significant amounts of cash and transform weak FCF conversion into strong performance.

Net Working Capital is a simple formula, but it reveals a lot about a company’s liquidity and financial flexibility. Positive NWC gives room to invest and grow, while negative NWC signals stress. The biggest challenge for most companies is managing accounts receivable. When customers pay late, DSO rises, AR balloons, and free cash flow suffers. By reducing DSO and modernizing collections with automation, companies can strengthen their working capital position and unlock millions in cash.

The bottleneck in accounts receivable isn't billing, it's conversations. When payment reminders go out, some customers reply with disputes and questions, others go quiet. AR teams have to manually respond to each inbound query and followup on overdue invoices from a shared inbox. AI agents help AR teams automate these conversations at scale to reduce DSO and save time. Paraglide builds AI agents for accounts receivable that work inside the finance inbox. The AI agents respond to billing queries, send reminders, track payment commitments, and follow up consistently.

The formula for DSO is simple, but the insights it provides are powerful. By tracking DSO consistently, comparing it with benchmarks, and applying best practices, finance teams can improve collections and unlock cash. If your DSO is climbing, it may be time to modernize your accounts receivable process. AI powered AR automation can help you collect faster, reduce disputes, and free your team from manual chasing.

The role of the credit controller is evolving. Today, much of the job involves repetitive email and phone conversations with customers. Tomorrow, AI agents will handle these at scale, allowing humans to focus on the judgment calls, the disputes, and the exceptions that truly require their expertise. Credit controllers will not be replaced. They will be elevated, moving up the value chain to manage AI-driven teams of agents and focus on more strategic, value-adding work.

AI agents are redefining the order-to-cash process. They can interpret contracts, create invoices, manage finance inbox queries, automate dunning and collections workflows, resolve disputes, and streamline cash application and reconciliation. Where shared services reduce cost by moving manual work offshore, AI eliminates the manual work altogether. The result is faster collections, fewer disputes, stronger cash flow, and finance teams that can focus on strategy instead of repetition.

Debt collection is no longer confined to manual chasing, expensive outsourcing, or rigid dunning software. AI agents are redefining the process by handling contextual outreach, managing two-way conversations, tracking promises to pay, escalating intelligently, and even using voice channels to reach customers. For CFOs, the benefits are clear: faster collections, lower DSO, reduced bad debt, and less reliance on costly collection agencies. For AR teams, AI takes on the heavy lifting, allowing humans to focus on disputes, escalations, and strategy.

AI agents bring a new paradigm to dunning workflows. Instead of static, one-size-fits-all reminder sequences that customers ignore, companies can now run personalized, conversational, and context-aware collection processes at scale. By capturing promise-to-pay dates, maintaining continuity of escalation, and applying proven tactics from AI-driven sales outreach, AI agents can act like a full AR team, chasing payments, resolving queries, and escalating only when needed. For CFOs, the benefits are clear: lower DSO, fewer bad debts, reduced headcount pressure, and less reliance on costly collection agencies.

AI agents are reshaping credit control by automating the conversational, repetitive work that has long dominated the role. They can respond to inbound queries, run outbound dunning and collection workflows, and hold two-way conversations that drive faster payments. For CFOs, the benefits are clear: lower dso, stronger cash flow, fewer overdue invoices, and finance teams freed from repetitive tasks. for credit controllers, the job evolves from manual chasing to managing intelligent agents and focusing on the disputes and decisions where humans add the most value.

Debt collection agencies cost anywhere from 10% to 50% of recovered amounts, with most B2B companies paying around 15–20%. But the bigger cost comes from letting invoices age, then outsourcing the work to humans who do the same manual chasing at a premium. AI agents provide a smarter alternative. They automate dunning workflows, handle two-way conversations, track promises to pay, resolve issues early, and even leverage voice channels. The result is lower DSO, stronger cash flow, and far less reliance on expensive agencies.

Accounts Receivable Days is a powerful liquidity metric that shows how efficiently your company turns credit sales into cash. It is closely connected to DSO, AR turnover, and net working capital. If your A/R Days are trending higher, it is a signal that cash is trapped in receivables and collections need attention. By modernizing your AR processes, leveraging automation, and reducing DSO, you can strengthen working capital and unlock millions in free cash flow.

The best finance teams are moving from static, rule-based reminders to dynamic, conversational workflows powered by AI. AI agents now handle thousands of customers simultaneously, personalise outreach, find the right contacts, track promises to pay, involve account owners when needed, and escalate intelligently at the customer level. The result: faster collections, lower DSO, fewer disputes, and better customer experiences — without adding headcount or outsourcing collections.

Accounts receivable aging is a foundational tool in working capital management. By structuring invoices into clear time buckets, AR teams gain visibility into payment risk, collections priorities, and cash flow impacts. When combined with metrics like DSO and AR turnover, AR aging helps finance teams act decisively: reducing late payments, improving liquidity, and protecting against bad debt. Want to see how AI-powered AR automation can streamline aging reports and collections? Book a demo with our team.

In large AR teams, overdue payments are usually due to inbox overload, not customer refusal to pay. High volumes of routine queries, missing POs, disputes, remittances, and invoice requests create delays that increase DSO, weaken forecasting, and stretch teams beyond capacity. AI agents for accounts receivable remove this bottleneck by automating high-volume finance communication. Agentic AR solutions can read and respond to emails, capture promise-to-pay dates, resolve disputes, match payments, and sync updates to ERP systems, turning unstructured inbox traffic into structured cash-flow data.

Getting customers to pay on time isn't about sending more reminders — it's about creating a system that makes payment easy, clear, and consistent. With AI agents handling the repetitive, conversational, and time-sensitive parts of collections, finance teams can focus on strategy and relationships. The result: fewer overdue invoices, healthier cash flow, and customers who pay on time — every time.