Traditional payment rails like credit cards, checks, ACH transfers and wires continue to dominate corporate finance departments because they are familiar, already integrated into existing systems and operationally predictable.

Data in the report “Ready and Willing: B2B Payments Are Headed for Real-Time Rails. Here’s How They’re Getting There,” a collaboration between PYMNTS Intelligence and The Clearing House, finds that 94% of businesses pay suppliers on time, 86% say their accounts payable operations are efficient and 82% report strong visibility into cash flow.

But beneath that satisfaction lies a more revealing pattern. Companies using real-time payment rails consistently report materially better outcomes across nearly every operational metric that matters, from liquidity management and reconciliation to supplier relationships and strategic flexibility.

The issue is no longer whether the current system works. It is whether corporate payment systems that are merely good enough are increasingly slowing down firms that are looking for something that’s a little better.

Real-Time Payments Deliver More Than Speed

If invoices are being settled and suppliers are satisfied, many executives see little urgency to overhaul the plumbing behind the process. And that approach is not necessarily irrational. Businesses optimize for operational continuity as much as innovation. Payment systems are deeply embedded within enterprise resource planning (ERP) platforms, treasury workflows and reconciliation systems. Replacing or modifying those systems carries risk, expense and organizational friction.

Still, that sentiment increasingly resembles the logic that once protected paper invoicing, on-premise software and manual procurement systems. Functional does not necessarily mean optimal.

Across 20 separate business capabilities measured in the report, firms consistently rated real-time payment methods superior to non-instant alternatives. Eighty-five percent cited faster access to funds for suppliers, 82% pointed to faster transaction processing and 81% highlighted the ability to send payments on demand.

Real-time settlement allows finance teams to operate with near-live visibility into liquidity positions rather than relying on batch-based approximations tied to banking windows and settlement delays. That shift changes treasury management fundamentally. Instead of padding timelines for uncertainty, businesses can synchronize outgoing payments with actual liquidity needs and supplier obligations in near real time.

The most telling finding may be how dramatically perceptions shift after adoption. Businesses that had not used RTP® Network or FedNow® Service assigned both systems modest ROI scores of roughly 52 out of 100. But companies with direct experience using the rails rated them 19 to 21 points higher.

Read the report: Ready and Willing: B2B Payments Are Headed for Real-Time Rails. Here’s How They’re Getting There

Integration Is the Real Bottleneck

If the benefits are so clear, why does adoption remain relatively limited? It has little to do with distrust in the rails themselves, the report found.

Instead, the central challenge is integration. Across nearly every revenue segment surveyed, businesses identified ERP, treasury and accounting system integration as both the biggest obstacle to adoption and the most important improvement needed for future payment performance.

That is why ISO 20022 messaging standards matter so deeply to the evolution of real-time payments. The standard allows richer payment data and cleaner integration into ERP environments, enabling automated reconciliation and more sophisticated treasury workflows.

The adoption curve already reflects this reality. Larger firms with more complex treasury operations and greater integration resources are moving fastest. Among companies generating more than $25 million annually, RTP Network adoption reaches 17%, compared to just 3% among firms earning between $1 million and $5 million.

The momentum appears to be building. Fifty-three percent of businesses surveyed said they plan to adopt the RTP Network within two years, including nearly three in 10 planning adoption within six months.

As real-time payment infrastructure matures, companies that adopt early gain operational advantages that compound quietly over time: tighter liquidity management, improved supplier leverage, faster revenue recognition and reduced administrative friction. These are incremental efficiencies individually, but collectively they reshape working capital performance and organizational agility.

“Upgrading risk software has always meant disruption and for firms managing risk in real-time, that’s a trade-off they can’t afford,” FIS said in a news release Tuesday (May 19). “This deployment on AWS reduces this by delivering a cloud-native risk management platform that keeps financial institutions on the latest version of the software, continuously and without operational disruption.”

According to the release, the platform’s “microservice-based, cloud-native architecture” lets clients scale their risk architecture in the cloud and run “higher volumes of calculations with lossless performance.” With burst computing, clients can instantly gain additional processing power for large calculations or peak workloads, with no need for costly on-site hardware.

The release noted that the launch is happening as financial institutions face increasing pressure to track a growing range of risks.

However, upgrading to a new software version has historically required firms to “choose between staying current and staying operational.” Andrés Choussy, president of the capital markets at FIS, said moving to AWS means the end of this trade-off.

“Our clients can now run the latest, most powerful version of Enterprise Risk Suite at all times, while scaling their risk infrastructure dynamically to meet whatever the market demands,” he added. “This modern framework combined with comprehensive risk coverage enables smarter, faster and more capital-efficient risk management decisions that drive revenue growth.”

PYMNTS Intelligence collaborated with FIS recently on the report “Where Payment Decisions Happen: How Issuer Data Is Powering the Next Era of Commerce.”

That report charts an evolution in issuer processing, from what had been a “back-end utility” into a “decisioning layer” that shapes how payments are approved, optimized and secured in real time.

“Commerce itself is becoming more automated, personalized and AI-driven, especially as agentic commerce models emerge,” PYMNTS wrote.

The report’s core finding is that not all data are equal. Historical transaction records alone are not enough in modern payments environments where AI systems increasingly initiate or guide transactions. This is pushing issuers and processors to aggregate behavioral, contextual and real-time operational data that can enhance authorization decisions, reduce fraud and minimize friction at checkout.

Traditional issuer processing systems were designed primarily for execution reliability and speed, the report argues.

However, the report added, “those rules-based systems struggle in environments where transactions are increasingly shaped by contextual signals, consumer behavior and AI-enabled commerce flows.”

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But something more fundamental is shifting beneath the surface. Card rails and digital corporate payment settlement layers—long regarded as intermediaries moving funds between buyers and sellers—are becoming validators of commercial legitimacy itself. As artificial intelligence (AI)-generated impersonation scams, vendor fraud and synthetic business identities proliferate, CFOs are confronting an uncomfortable truth: they often don’t know who is on the other side of a transaction before funds move.

That uncertainty is elevating a previously underappreciated feature of commercial card ecosystems. Beyond settlement and liquidity, B2B card networks are emerging as a practical identity and authentication infrastructure for enterprise commerce, turning payments into a governed trust layer capable of verifying businesses, validating counterparties and authenticating transactions at commercial scale.

The stakes are concrete. Modern enterprise risk now includes onboarding fake suppliers, routing invoices to compromised accounts, authorizing payments triggered by AI-powered impersonation and managing sprawling third-party ecosystems where trust signals are often fragmented or weak. The card rails CFOs once took for granted may be the identity infrastructure they didn’t know they needed.

See also: The Riskiest Words in B2B: This Is How We’ve Always Done It 

CFOs Unlock the Hidden Identity Value Embedded in Card Networks

The acceleration of AI-driven fraud is forcing finance organizations to rethink authentication as a treasury issue rather than merely a cybersecurity concern. The vulnerability is not simply technological. It is structural. Many B2B payment systems still rely on fragmented verification processes disconnected from payment execution itself.

Unlike many open payment environments, commercial card transactions occur inside a highly structured framework involving banks, networks, issuers, acquirers and compliance controls. Businesses entering the ecosystem are typically subjected to Know Your Customer and Know Your Business requirements through regulated financial institutions.

That architecture helps create a foundational layer of authenticated commercial identity before any transaction occurs. And while this infrastructure was traditionally viewed as incidental to the payment itself, it is increasingly becoming central to procurement and finance strategy. The commercial card ecosystem effectively bundles payment acceptance with identity verification, governance standards, fraud monitoring, dispute mechanisms and auditability.

That realization is changing how enterprises think about payment value. The old procurement mindset focused heavily on interchange costs and rebate economics. The emerging perspective is broader. Finance leaders are evaluating the total economic value of payments ecosystems, including fraud reduction, operational efficiency, supplier governance and data intelligence.

“The real operational shift happens when card and virtual cards carry remittance data and when that flows directly into the ERPs (enterprise resource planning),” Marc Pettican, global head of corporate solutions at Mastercard, told PYMNTS in a recent interview. “Cards ultimately stop being perceived as a cost and start being perceived as an operational enabler.”

Read more: It’s Level 3 or Bust as Visa’s Interchange Shift Rewires B2B Data 

The Data Dividend of Commercial Card Adoption

Visibility is emerging as another key benefit of B2B card use. Traditional B2B payment methods, particularly ACH transfers, checks and manual invoice workflows, often produce fragmented or limited transaction data. Card ecosystems, by contrast, generate highly structured and standardized information flows that can feed procurement analytics, cash forecasting, compliance monitoring and supplier management systems.

That level of granularity helps enable finance teams to identify duplicate spending, uncover maverick procurement activity, monitor vendor concentration risk and optimize supplier relationships more effectively.

Zach Lynn, head of customer data and insights at Boost Payment Solutions, wrote in the PYMNTS eBook “Headlines That Will Shape the Close of 2025” that data exchange has become non-negotiable in the payments industry.

“In today’s environment, seamless, secure data flows between buyers, suppliers and financial institutions are essential,” Lynn wrote. “Whether it is enabling real-time reconciliation or supporting advanced analytics, the ability to move and leverage data is now table stakes for any organization.”

Finance organizations are using commercial payment data not merely for reporting historical activity, but for predictive decision-making. Spending trends can inform liquidity planning, vendor transaction patterns can surface operational anomalies and procurement activity can become a real-time signal for business performance.

The result is a broader reframing of commercial payments. Rather than evaluating payment methods purely on settlement cost, CFOs are increasingly evaluating them based on trust efficiency: how effectively a payment system reduces uncertainty, operational friction and counterparty risk.

And in an era shaped by AI-powered deception, synthetic identities and escalating vendor risk, that capability may prove more valuable than the payment itself.

The German software giant’s “Autonomous Enterprise” initiative, announced Tuesday (May 12), focuses on a new unified platform and specialized tools intended to automate end-to-end tasks across various corporate functions.

“For the mission-critical processes of our customers, ‘almost right’ just isn’t good enough,” Christian Klein, SAP’s chief executive, said in a news release. “By uniting SAP Business AI Platform with SAP Autonomous Suite, we anchor AI agents in the business processes, data and governance so they can deliver accurate, compliant and secure outcomes, unlocking new sources of revenue and meaningful cost savings.”

SAP Business AI Platform, the release added, unifies the company’s SAP Business Technology Platform, SAP Business Data Cloud and SAP Business AI into a “single, governed environment.” At its center is the SAP Knowledge Graph solution, which gives AI agents a “structured map of business entities, processes and relationships.”

In addition to the new product rollouts, SAP is also announcing a series of AI partnerships tied to its various tools, with companies that include Anthropic, Amazon Web Services and Nvidia.

SAP began this year by rolling out a series of agentic artificial intelligence enhancements for its retailer customers.

“Retailers face a landscape where AI is no longer optional,” Balaji Balasubramanian, SAP’s chief product officer for customer experience and consumer industries, said at the time. “SAP provides one closed-loop, AI-enhanced retail operating system that ties planning, execution and engagement together. We put data and AI at the heart of retail, delivering speed, personalization and growth across every channel and segment.”

The company is launching these tools at a moment when “agentic artificial intelligence is moving from frontier technology to operational table stakes,” as PYMNTS wrote recently.

Agentic AI, that report said, marks a shift from tools that help shape decisions to systems that carry them out.

“For CFOs, this changes the calculus,” PYMNTS added. “The question is no longer whether artificial intelligence can improve finance operations, but whether it can do so within a framework of control and accountability.”

That’s where the “agentic AI harness” comes in. This term may sound technical, but its implications are chiefly operational. The harness isn’t the model itself, but the system that controls how models perform in the real world. It sets the parameters for what an AI agent can access, what it is permitted to do, how it is monitored and when it needs to defer to a human.

“For chief financial officers, understanding this layer is becoming as important as understanding internal controls or capital allocation,” the report added.

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This expansion follows the offering’s launch in the United States in the second quarter of 2025 and its later expansion to the United Kingdom and Canada with limited availability, Remitly Global said in a Tuesday (May 12) press release.

“Canadians have trusted Remitly to move money across borders for more than a decade,” Jung Lee, general manager of Canada at Remitly, said in the release. “Bringing that same speed and reliability to Canadian business owners was overdue — and the demand we’re already seeing makes that clear.”

Remitly Business is powered by the same compliance, risk and disbursement infrastructure that serves 9.6 million quarterly active Remitly customers. It extends that infrastructure’s capabilities to SMBs that have cross-border financial needs, together with a design that is focused on the needs of owner-operators, according to the release.

Since its launch in the U.S. in the second quarter of 2025, Remitly Business has been used by more than 20,000 businesses, per the release.

Remitly Global also announced in the Tuesday press release that it has added two more features to Remitly Business for customers in the U.S.

The Bulk Payments feature, which is rolling out to select U.S. customers and will later be made generally available, enables users to pay multiple international recipients in one workflow.

The Send by Link feature, which is generally available to U.S. customers, enables senders to initiate payments using only the recipient’s email and phone number. The recipient can then provide the rest of the information through a secure link, whenever they want and without sharing the information with the sender.

“A small business owner shouldn’t lose half a day to a single overseas pay run — or deal with transfer delays because of a typo in a recipient’s name,” Remitly Chief Business Officer Pankaj Sharma said in the release. “We’re moving fast to solve the pain points our customers care about most.”

Small businesses are joining Remitly because of of the messiness of international payments, which typically bounce through layers of correspondent banks, foreign exchange providers and settlement systems, Remitly CEO Sebastian Gunningham told PYMNTS CEO Karen Webster in an interview posted Thursday (May 7).

Gunningham said the small business opportunity could be enormous. “If you get 1% of the small business market, that’s like two or three Remitlys right there,” he said.

For all PYMNTS B2B coverage, subscribe to the daily B2B Newsletter.

In a world where companies are being pressured to do more with less, payments data is emerging as an underleveraged asset.

At least, that’s the case for those companies whose accounts payable (AP) and accounts receivable (AR) functions can capture it.

“The real operational shift happens when card and virtual cards carry remittance data and when that flows directly into the ERPs,”  Marc Pettican, global head of corporate solutions at Mastercard, told PYMNTS.

Particularly in B2B environments, where complexity can obscure opportunities, the real transformation begins when organizations stop treating payments as manual endpoints and start treating them as foundational building blocks of smarter, more connected operations.

“The biggest unlock is moving from what I would classify as reactive reconciliation to proactive decisioning,” Pettican said. “At that point, reconciliation stops being the month-end cleanup exercise and becomes more continuous.”

The implication is one that’s becoming increasingly clear and attractive: payments should not introduce friction. They should help to dissolve it.

Unlocking Smarter B2B Payments Through Data and Automation

The enterprise push toward automated and data-driven decision-making is central to what Mastercard calls “adaptive commercial acceptance,” which represents a model where payment acceptance scales only when it is fully integrated into existing workflows.

“Cards ultimately stop being perceived as a cost and start being perceived as an operational enabler,” Pettican said, noting that, rather than focusing solely on fiscal cost, organizations should consider time saved, reductions in manual reconciliation, faster cash application and lower dispute volumes.

After all, in many cases, the gains of operationalizing card use for B2B payments can be significant. Finance teams can process higher volumes without adding headcount, while suppliers benefit from improved cash flow predictability and reduced administrative burden.

Still, when card conversations do come around to the economics, they increasingly look better than they perhaps ever have. Mastercard’s own research, cited by Pettican, indicated that 57% of suppliers that accept cards use services to automate transaction processing, while over one-third say card acceptance helps them with greater payment visibility.

For leadership teams seeking to operationalize these insights, a measured, incremental approach can prove beneficial compared to rip-and-replace initiatives. Rather than overhauling existing systems, organizations can build on their current data and technology foundations.

“Start with the existing data and technology that you have within the organization, because everything else depends on it,” Pettican said.

As organizations increasingly rely on data to modernize payments, security and trust become foundational to long-term success. Protecting sensitive information, maintaining strong controls and using data responsibly are critical to realizing the full value of automation. In an increasingly digital ecosystem, businesses that pair innovation with resilience will be best positioned to scale confidently.

Ignoring Smarter Payments Leaves Stronger Operations on the Table

Despite the promise of digitization, many organizations still struggle with fragmented data environments due to a persistent disconnect between payment data, remittance information and invoice records across B2B.

“The biggest break point occurs when payment data, the remittance data and invoice data are just not working together,” Pettican said.

The result is a paradox familiar to many finance leaders: more data, but less clarity.

The solution, Pettican suggested, often lies in standardization and direct system integration. Platforms like Mastercard’s Mastercard Receivables Manager aim to “unify the payment and the remittance data … and deliver that in a standardized format directly into the ERP platforms,” he said, reducing manual intervention and improving data consistency.

“Richer data replaces friction and replaces it with facts. When you’ve got invoice-level data shared alongside the payment, you can resolve faster,” Pettican said. “Commercial payments … deliver value when the business knows where that payment is, how it’s been settled, and how it will be reconciled.”

At the same time, API-led innovation is playing an increasingly important role in helping modernize commercial payments. As businesses look to connect fragmented finance, procurement and payment systems, standardized integrations can help reduce manual processes, improve interoperability and accelerate adoption of more efficient payment methods. Solutions such as Mastercard’s Commercial Connect API reflect the growing industry shift toward embedded, workflow-driven payments that meet businesses where they already operate.

After all, even digital payments can fail to deliver full value if they are not unified across systems. And as organizations continue to invest in automation, the quality and accessibility of a firm’s own payments data could prove to be critical in determining the effectiveness of downstream decisions.

Here’s something most people in finance don’t talk about. The billing systems that run the back office were built for a world that doesn’t really exist anymore.

These typical toolkits, the ERPs, revenue recognition platforms and billing engines were designed with a simple assumption baked in: that companies charge their customers in more or less the same way every time. Same pricing tiers. Same contract structures. Predictable, repeatable, neat. And for a long time, that assumption mostly held up.

But it doesn’t anymore.

In a recent conversation with PYMNTS CEO Karen Webster, Apurv Bansal, CEO and Co-Founder of Zenskar, laid out the problem plainly. Today’s B2B deals are messy. Every customer wants something different. Sales teams negotiate custom terms, layer in usage-based pricing, tack on geographic adjustments. And finance teams are left trying to squeeze all of that into systems that were never designed to handle it.

“Collecting money is important. If you don’t get paid, you don’t run the business,” Bansal said, adding that the financial back office is overdue for a ground-up rebuild.

His company just raised $15 million to do exactly that, building what he calls “AI-native financial architecture” designed to reinvent billing and revenue management.

Every Deal Is Different. And That’s the Problem

Think about what B2B pricing actually looks like today. A company might offer one customer a flat monthly rate, another a usage-based model, and a third some hybrid of the two with volume discounts and a custom payment schedule. Multiply that across hundreds or thousands of accounts, add in different geographies and currencies, and you’ve got a combinatorial nightmare.

On its own, that’s just the reality of selling. The real issue is that finance teams are trying to manage all of this variability with tools that expect every deal to look the same.

As Webster pointed out, billing complexity tends to get written off as a series of “edge cases,” even though entire companies have been built to address it. That framing understates how fundamental the problem has become.

“Sales is driving revenue, and rightly so… Trying to convince sales teams to change the way they structure their contracts is a lost cause,” Bansal said. Every new product, geography, or enterprise customer introduces variation—and it’s the finance teams that are left to reconcile the mess downstream.

What ‘AI-Native’ Actually Means Here

Bansal’s pitch isn’t about bolting a chatbot onto an existing billing system. It’s about starting over.

Traditional finance tools are rule-based. Finance teams define their pricing templates, invoice formats, revenue recognition rules, and then everything has to fit inside those guardrails. When it doesn’t, and increasingly, it doesn’t, someone on the finance team ends up doing it manually.

An AI-native system works differently. Instead of forcing contracts into rigid templates, it reads and interprets them. Parsing out the terms, understanding the pricing logic, and handling the downstream billing, invoicing, and revenue recognition automatically.

“All a human has to do is come in and hit okay,” Bansal said, describing a workflow where AI handles everything from contract execution through invoice generation, collections, revenue recognition, and journal entries.

“You can scale your business without having to linearly add people to your team,” he added. That’s what he means by “zero-touch finance.” A back office that largely runs itself.

The Trust Problem

Of course, “just let the AI handle your billing” is a hard sell. Finance is one of those areas where accuracy isn’t a nice-to-have. It’s existential. Get an invoice wrong, and you don’t just lose money. You lose a customer’s trust.

“Trust once broken is extremely hard to earn back,” Bansal said. “You only get one chance.”

That’s partly why Zenskar isn’t asking companies to rip and replace everything. Bansal is deliberately avoiding the classic startup move of demanding that customers overhaul their workflows.

“You cannot expect businesses to change their workflow,” he said. Instead, the platform plugs into the tools companies already use, their CRMs, ERPs, payment stacks, to minimize friction and speed up adoption.

Billing and revenue management have never been glamorous, but they’ve always been essential. What’s shifting is the recognition that the tools most companies rely on simply weren’t built for the way business works now.

For Bansal and Zenskar, the challenge now is execution. Proving that AI-driven automation can meet finance’s uncompromising standard for accuracy while scaling across industries that rarely do things the same way twice.

It’s a finished product wrapped around the bet that the finance stack is ready to be rebuilt. And that AI is finally capable enough to do it.

This is driving a rethink of virtual cards as purely payables tools and innovation. While VCNs represent a smarter, more controlled way for companies to disburse funds and reduce fraud on the issuing side, that framing increasingly overlooks the potentially more transformative opportunity that buyer-issued virtual cards, when accepted by suppliers, can help modernize accounts receivable (AR).

The typical AR function remains, in many respects, a holdover from an earlier era, even as payment volumes grow and buyer expectations around speed, convenience and certainty continue to rise. Mastercard research showed that nearly two-thirds of B2B suppliers said they regularly fail to meet buyer expectations around the payment experience, often with direct consequences for cash flow.

Invoices are issued with clear terms, but the mechanics of payment are often left undefined. Money can arrive through a patchwork of channels, each with different timing, costs and levels of remittance visibility, making it harder for finance teams to predict, reconcile and plan. On average, large B2B suppliers accept five to six different payment types, the Mastercard research found, and nearly one-third reported that about a third of their payments arrive late, underscoring how fragmented receivables have become.

The result is that today’s enterprise AR process is less a system than a fragmented accumulation of practices. And those practices are increasingly showing their age.

Against this AR backdrop, virtual cards offer a compelling solution for re-engineering how companies get paid by introducing structure, predictability and embedded payments into receivables.

This is central to Mastercard’s adaptive commercial acceptance approach. Acceptance only scales when it is embedded inside the receivables and invoicing workflows suppliers already use, not layered on as a separate process. When acceptance is native to those workflows, virtual cards stop being perceived as a cost and start being experienced as an operational enabler that brings structure, predictability and confidence to how businesses get paid.

For finance leaders, greater control of AR is becoming something particularly valuable at a time when businesses are under growing pressure to improve liquidity, reduce operational friction and modernize their finance workflows.

Capturing New Benefits

Despite the broader shift toward digital-first operations, the process of getting paid remains stubbornly analog at its core across many companies. This results in a central weakness of existing receivables functions, such as limited control over how and when payments are executed.

It’s a challenge senior leaders recognize, as the Mastercard research revealed that 92% of suppliers said optimizing payment choices for customers is a priority, and 94% said more efficient payments directly boost profitability.

A company may know what it is owed and when, but it has limited control over how that payment will be executed. Checks still circulate. Traditional bank transfers arrive without sufficient remittance detail. Wires require manual confirmation. Even when payments are electronic, the workflow around them is commonly not.

Virtual cards offer a way out of this loop.

Rather than issuing an invoice and leaving settlement open-ended, a buyer can generate a transaction-specific virtual card tied to that obligation and share it with the supplier. The supplier then applies the virtual card to the corresponding invoice, with predefined parameters around amount, validity and use, reducing uncertainty and narrowing the range of possible outcomes.

A principal advantage of this arrangement lies in its effect on timing. Traditional receivables are subject to delay at multiple points, including internal approvals, payment initiation, processing and confirmation. Two companies with similar days sales outstanding (DSO) can experience markedly different cash flow patterns, complicating forecasting and liquidity management.

The most powerful shift offered by virtual cards is also the simplest: embedding payment directly into the invoice. In the past, approval only confirmed what was owed; how payment would happen was still an open question. With embedded payments, approval aligns closely with execution. The payment method is predefined, reducing additional steps required to initiate settlement.

For finance functions, the distinction can be material. Cash flow forecasting improves when the dispersion of payment timing narrows and when remittance data is consistently tied to the transaction itself. Even modest reductions in timing variance can translate into improvements in liquidity management for companies with large receivables balances.

The Mastercard research showed that 32% of card-accepting suppliers reported improved payment visibility, and 30% cited faster processing, compared with those relying on more manual receivables methods.

A Reorientation of Financial Priorities

The case for virtual cards in receivables comes with considerations, as with any payment method. Organizations evaluate card-based payments in the context of their broader operating model, priorities and objectives. Increasingly, many are finding that the benefits of greater certainty, automation and predictability reshape how that decision is made.

Still, the virtual card receivables model is most compelling where the value of faster, more predictable cash flow outweighs transaction costs, and where operational complexity inherently amplifies the benefits of standardization.

But, already, virtual cards applied on the receivables side suggest that the process of getting paid can be structured with the same rigor as the process of paying. The implications may be incremental in isolation, but they are proving significant in aggregate and offer AR teams reduced variability, lower administrative burden and improved working capital dynamics.

What distinguishes virtual cards in receivables is less the technology than the shift in emphasis it implies. Payments have traditionally been managed as an outbound concern, focused on control and compliance. Receivables have traditionally been treated as an operational necessity.

But today, how a company gets paid increasingly shapes liquidity, resilience and competitiveness. It has grown beyond a back-office function to become a lever of financial performance.

Taken together, the implications of virtual card use in AR point to a reorientation of financial management, one in which cash collection is no longer passive but something actively designed.

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On Monday (May 4), businesses from mid-market to Main Street and the Fortune 50, potentially witnessed such a change.

The change, visible in announcements from Amazon, Anthropic and OpenAI, signaled the growing emergence of a top-down software and corporate services deployment model. It’s one where technology is no longer sold to one enterprise at a time but rather distributed across entire networks of companies in a single stroke. It represents a playbook that could reshape how software is bought, implemented and competed over.

Amazon announced Monday the launch of its Amazon Supply Chain Services (ASCS), a new business-focused offering modeled on the strategic DNA of its Amazon Web Services (AWS) cloud business that opens the company’s formidable freight, distribution, fulfillment and parcel shipping tools to businesses of all types and sizes.

OpenAI announced Monday that it raised $4 billion for a venture known as The Deployment Company, designed to get businesses to adopt its artificial intelligence tools. The initiative is backed by several investment firms, with the deal valuing the company at $10 billion. Partners for OpenAI’s new joint venture will reportedly get access to more than 2,000 portfolio companies and clients.

Not to be outdone, OpenAI rival Anthropic also announced Monday the launch of its own new venture focused on selling AI tools to enterprise companies, in partnership with Goldman Sachs, investment firm Blackstone and private equity group Hellman & Friedman. The Anthropic initiative will help companies embed Anthropic’s Claude AI model into their businesses.

Individually, these announcements might read as incremental expansions of already dominant platforms. Taken together, they could signal something more structural.

See also: ERP Data Can Fuel Enterprise AI. So Why Won’t Vendors Let It?

The Rise of Portfolio-Level Technology Adoption

For much of their history, enterprise technology sales have been defined by bottom-up friction. Vendors pursued individual contracts, navigated bespoke integrations and tailored deployments to each client’s needs. Even the most successful software-as-a-service companies typically scaled through accumulation.

What OpenAI and Anthropic are now pursuing breaks that paradigm. By structuring joint ventures with private equity firms and large corporate groups, they are effectively turning portfolios into distribution channels. A single agreement can unlock deployment across dozens—or even hundreds—of companies simultaneously.

It’s pointed at a real problem. Organizational readiness is the most cited barrier to AI adoption at large companies. More than 71% of executives at companies with at least $1 billion in yearly revenue named it as the chief limit on AI performance, according to research by PYMNTS Intelligence. Just 11% said the technology itself is the main obstacle.

Neither of the AI firms stayed still after their enterprise announcements. FIS and Anthropic announced Monday that they developed a Financial Crimes AI Agent and plan to build additional AI agents for bank-grade operations. Meanwhile, on Tuesday (May 5), OpenAI launched a finance-focused agentic AI partnership with professional services network PwC.

In the same vein, PYMNTS wrote in April about the way enterprises are rethinking their AI spending as companies shift their pricing practices.

“AI tools that embedded themselves inside engineering workflows as productivity aids are now line items with variable, consumption-driven costs,” the report said. “Enterprises that adopted them at scale without modeling actual usage are finding invoices that don’t match budgets.”

Read also: CFOs Turn to AI Harnesses as Agentic Capabilities Scale

Tech Giants Are Rewriting the Traditional Economics of Scale

If the traditional SaaS era was characterized by a proliferation of specialized tools, the new model points toward consolidation. When deployment decisions are made at the portfolio level, the incentive is to minimize fragmentation. Fewer vendors, deeper integrations and broader platforms become the default. This can create a winner-take-most dynamic.

What is emerging is a tech landscape that is similar to the enterprise cloud landscape, where solutions are infrastructure-driven and not point-based.

Amazon, at least, is trying that same playbook all over again with its new logistics offering. The company’s move to open its logistics and supply chain services to non-platform businesses suggests an ambition to become the operating system not just for computing, but for physical commerce.

In practical terms, this means enterprises may increasingly outsource entire functional layers such as customer service, procurement optimization, forecasting, compliance monitoring and more, to Big Tech platforms. The differentiation would then shift from owning technology to orchestrating it effectively.

In related news, PYMNTS wrote in April that many small- to medium-sized businesses (SMBs) have stopped trying to compete with Amazon on delivery speed.

“The fact facing Main Street business owners is that, beyond a certain point, incremental gains in speed can require disproportionate increases in cost and operational complexity,” the report said.

For all PYMNTS B2B coverage, subscribe to the daily B2B Newsletter.

These tools are designed to accelerate collections, improve buyer payment experiences and provide AR teams with earlier cash flow visibility, the company said in a Tuesday (May 5) press release.

Billtrust’s new Buyer Payment Portal allows buyers to view invoices, manage balances, enroll in Autopay, make payments with multiple methods, and receive guidance on capturing early-pay discounts, avoiding surcharges and optimizing payment timing.

For suppliers, the portal enables AR teams to manage payment methods, branding and access without submitting support tickets.

Lee An Schommer, chief product officer at Billtrust, said in the release that the company built the portal “to actively guide buyers toward the actions that benefit both sides of the transaction, while giving AR teams their time back.”

Another new tool from Billtrust, the Cash Forecast analytics capability, generates a 13-week AR cash forecast based on Billtrust payment activity, invoicing data and a daily open AR balance file, per the release.

An agentic layer monitors buyers’ behavioral signals, notifies finance teams when material changes occur, and provides the projected cash impact broken down by week.

“By analyzing live buyer payment behavior across all receivables activity on the Billtrust platform, not limited to a single ERP or payment channel, Cash Forecast helps finance leaders see changes sooner, understand exactly what’s driving them and plan with greater confidence,” Schommer said in the release.

PYMNTS reported in April that while AR has long been run as a back-office chore, it is now expected to chase delinquency on buyers more frequently.

Augmenting ERP systems with purpose-built AR platforms can improve cash flow, reduce days sales outstanding and shift finance from reactive tracking to proactive decision-making, Schommer told PYMNTS in an interview posted in March.

“The ERPs are always going to be the system of record. Their core strength is financial transactions. AR solutions, they’re the intelligence layer,” Schommer said.

“Shifting from process automation to more predictive intelligence” is the next step, she said.

Companies need systems that can “start predicting cash flow, predicting disputes, understanding where there’s risk, and then helping you proactively manage it,” Schommer said.