The Classic ERP Model Is Dying. What Comes Next?

ERP, AI, digital transformation

Highlights

Traditional, single-vendor ERP systems are increasingly seen as rigid, costly and misaligned with modern demands.

Finance leaders are split between composable, API-driven stacks of best-of-breed tools and the evolution of ERP into an AI-embedded, “agentic” core.

Regardless of the model, future finance systems must be open, real-time, AI-native and resilient.

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    That’s the reality increasingly setting in for the enterprise resource planning (ERP) system. But what’s dying is not enterprise finance software itself, but the assumption that one vendor, one platform and one rigid architecture can serve every organization indefinitely.

    Monolithic ERP platforms are increasingly viewed by finance teams as expensive, rigid systems that can struggle to keep pace with the speed, complexity and unpredictability of modern business. Forced upgrades, vendor-directed roadmaps and deeply embedded lock-in have collided with a 21st century CFO who now expects continuous innovation, real-time insight and artificial intelligence (AI)-assisted decision-making.

    What CFOs see as replacing the old ERP paradigm, however, is far from settled. Some finance leaders are of the view that progress means dismantling the core altogether, assembling composable stacks of best-of-breed applications stitched together by application programming interfaces (APIs). Others may believe ERP can survive, but only by mutating into something far more autonomous, intelligent and adaptive: an “agentic” core that embeds AI directly into the system of record.

    One thing, however, is clear. The ERP conversation has moved from one of optimization to one of reinvention.

    Read more: How AI Is Supercharging the Tools CFOs Already Trust

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    Why the Traditional ERP Contract Is Breaking Down

    Today’s CFOs operate at the intersection of strategy, operations and technology in ways their predecessors never did. The result is a widening gap between what finance organizations need and what their core systems are optimized to deliver.

    “We see challenges around legacy ERP systems with limited AR API capabilities,” Michael Younkie, vice president of product management at Billtrust, told PYMNTS in an interview this week. “We like to tie clear measurable KPIs to upfront things like DSO reduction, straight-through processing, digital invoice adoption.”

    One answer gaining traction is the composable, API-driven finance stack made up of best-of-breed FP&A, BI or data platforms, fed by ERP data. Instead of relying on a single monolithic system, organizations assemble specialized applications for core functions such as general ledger, billing, planning, treasury, revenue recognition and more, connected through standardized interfaces and shared data layers.

    For CFOs that can feel frustrated by forced upgrades and inflexible workflows, composability may feel like a reclaiming of agency.

    Running parallel to the composable movement is a different vision: not the death of ERP, but its evolution into an intelligent, autonomous platform, thanks to AI. SAP is pushing agentic AI deeper into its ERP suite. Oracle is rolling out AI agents, while Salesforce is packaging industry-specific copilots and autonomous workflows into its ecosystem.

    The PYMNTS Intelligence report “Smart Spending: How AI Is Transforming Financial Decision Making” found that more than 8 in 10 CFOs at large companies are either already using AI or considering adopting it.

    Agentic ERP innovations promise to preserve the benefits of a unified system of record while addressing its historical shortcomings. Instead of rigid workflows, processes become dynamic. Instead of static reports, finance leaders get scenario-based insight. Instead of vendor-driven change, AI-driven optimization becomes continuous.

    One of the biggest takeaways from PYMNTS Intelligence’s December “Invoice-to-Pay Automation Tracker Series” is the way in which enterprises are using AI to modernize AP. AI addresses lingering manual gaps by standardizing data fields, improving accuracy and creating a single view of obligations and supplier activity.

    See also: Vibe Coding Comes to Finance as CFOs Embrace Conversational AI

    What the Future Finance Core Actually Needs

    Whether CFOs choose composable stacks, agentic cores or some hybrid of the two, there is growing consensus on the operational requirements tomorrow’s finance systems must meet.

    First, finance leaders are prioritizing openness. Finance cannot be the last closed system in an otherwise digital enterprise, and APIs, data portability and interoperability are becoming tables takes.

    Second, core infrastructure is becoming increasingly immediate. Batch processing and end-of-month surprises are incompatible with businesses that operate continuously across global markets.

    Third, they must be intelligent by design. AI cannot remain a bolt-on analytics layer; it works best when it can be embedded where financial decisions are made, with clear governance and explainability.

    Fourth, resiliency is climbing up the priority list. Cybersecurity, regulatory compliance and operational continuity are board-level concerns and finance systems sit at the center of that risk profile.

    “There’s a continuous evolution and … dynamic disruption in finance that requires CFOs to harness data and AI to make finance more efficient, more effective and substantially more strategic,” Raj Seshadri, chief commercial payments officer at Mastercard, told PYMNTS in an earlier interview.

    For CFOs, the challenge is not to predict which ERP model will “win,” but to ensure their technology choices preserve optionality and resilience for the business and their bottom line.