The debate rages on about AI’s effectiveness in business, with PwC highlighting how 56% of CEOs say they have yet to see significant financial benefit from it. Is this because they’ve been looking in the wrong place
One of the most critical, yet overlooked, core business processes, in both B2C and B2B, is order-to-cash (O2C). Every business depends on it, as much as they depend on sales and marketing or procurement: after all, it spans the entire cycle from receiving an order to collecting payment.
But O2C has historically worked ‘well enough’, it has often been neglected. But what if instead of a reliable back-office function, O2C could be flipped into a strategic growth engine, directly impacting liquidity, risk management and an improved customer experience?
Rethinking O2C may feel risky, but the data tells a different story. According to McKinsey, only 1% of CFOs have automated over three-quarters of their financial processes, and only 5% of mid-size firms have fully automated their accounts receivable processes.
This is problematic because too much use of manual tools—spreadsheets or even pen and paper—or siloed point solutions creates inefficiencies across the O2C process.
That harms your brand in multiple key ways: it weakens control and visibility of your working capital, and weakens the accuracy for investors and regulators of any financial forecasts, while also signaling that you are an outdated business, unable to deliver the seamless onboarding and interactions now expected as table stakes.
An evolving idea
Momentum is building around upgrading O2C, transforming an antiquated back-office function into something more integrated, customer-centric and better aligned with today’s supply chain and addressable market.
Much of this was underway before AI. Some B2B leaders have been focused on digital optimisation of individual O2C steps, from order receipt to invoicing to recording of the transaction, while others have demanded more ambitious, end-to-end automation. Many brands operate across both e-commerce and bricks and mortar settings, yet buyers expect a consistent experience across all channels.
In the last 18 months, AI has really moved O2C modernisation to the centre stage, largely in the form of predictive machine learning and analytics to significantly increase efficiency.
AI now increasingly provides practical insights around O2C by being able to sift through and analyse patterns in large volumes of data. Payment data can identify anomalies in buyer behaviour; useful for combating fraud, but also in exposing trends you could use to gain commercial advantage.
In the past 18 months, AI has pushed O2C modernisation to the forefront, using predictive analytics and machine learning to boost efficiency. By analysing vast payment data, AI can spot anomalies to combat fraud and uncover trends for commercial advantage.
Today’s most advanced payment platforms process large volumes of incoming data to make firms more efficient, while using AI to predict risks such as potential defaults. One system being trialled can predict potential customer withdrawal or payment issues by analysing account, purchasing and payment data, allowing sales teams to proactively re-engage buyers and give long-term relationships a chance to reset.
This generates enormous goodwill by talking to customers in a way that shows them their business is valued and understood. AI can also be used to personalise communications for small and large buyers—where GenAI-style chatbots come back in—significantly reducing the time key account teams need to spend on routine interactions, yet also improving communication throughout the entire order-to-cash journey.
Automated, personalised, fast and accurate AI-enabled communications can also be a huge help on KYC (know your customer) checks. Automation also accelerates the pace and accuracy of payment posting, freeing up credit teams for more value-add tasks and letting customers purchase without delay.
2026 AI O2C action plan
It’s time to turn this into practical reality. Our experience shows any automation or AI-led optimisation initiative only succeeds when it’s fully integrated into day-to-day, real-world operations.
To win hearts and minds, kick off any AI O2C work by focusing on high-friction areas, such as customer onboarding, days-to-pay, dispute resolution or payment allocation, in order to build momentum and gain buy-in.
Solving these problems one by one creates buy-in and momentum. Track days sales outstanding (DSO), working capital, percentage of past-due receivables, average order value (AOV), customer retention, purchase frequency and overall customer satisfaction before and after AI.
At its core, AI-driven O2C is a standard business IT project, so clear metrics, defined ownership and accountability, strong change-management practices and visibility into business impact is the best basis for success.
It’s time to see order-to-cash transformation as a growth engine, not only a back-office necessity. AI could be the rocket fuel needed to get lift-off.
Inez Berkhof-Hollander
Inez Berkhof-Hollander is EMEA Vice President for TreviPay, the global B2B payments network.
