The future of ERP: Why flexibility trumps features in an AI-Driven world

I've been in the enterprise software business long enough to see many “revolutionary” trends come and go. But the conversations I'm having with customers today feel fundamentally different. Organizations aren't just asking about features anymore, they're asking existential questions about adaptability, longevity, and survival in a rapidly changing business landscape.

Recently, I sat down with our Product Marketing Director, Barry Spielman, for Priority's Coffee Break series to discuss what we're really hearing from customers. What emerged wasn't just a discussion about AI (though we certainly covered that), but a deeper conversation about how ERP systems must evolve to serve businesses that can't predict what they'll need next year – let alone in five years.

The real trend nobody's talking about enough

Everyone wants to talk about AI. And yes, AI matters – I'll get to that. But the most critical trend I'm seeing is something more fundamental: the desperate need for adaptability. Organizations are facing an ever-changing reality. They're looking for business applications that are adaptive, personalized, flexible, and open. Here's what they've told me repeatedly: “We cannot imagine what tomorrow will look like.” This isn't about lacking vision; it's about being honest. Business models shift, markets evolve, regulations change, and technologies emerge. The pandemic taught us that even the most solid five-year plans can become obsolete overnight. So, when organizations evaluate ERP systems today, they're not just asking, “Does this support our core needs today?” They're asking, “Will this grow with us? Will it scale with us? Will it adapt when everything changes?”

Cloud: The not so hot trend that still matters

It's almost embarrassing to list “cloud” as a major trend in 2026. Cloud has been around forever, right? Yet I keep encountering organizations still running on-premises systems, harboring fear or resistance about cloud migration. And I understand that hesitation. Change is hard, especially when current systems appear to be “working fine.”

But here's the reality: if we're talking about the future, and more specifically about AI, cloud and AI go together. You simply cannot unlock the full potential of modern business intelligence, real-time analytics, or AI integration while anchored to on-premises infrastructure.

Cloud isn't just about where your servers live. It's about access to innovation, automatic updates, scalability, and the computational power needed for the sophisticated capabilities organizations will demand tomorrow.

Empowering users: The low-code/no-code imperative

When we talk about flexibility and adaptability, we're really talking about empowerment. Who controls your ERP system: you or your vendor? More importantly, who controls it within your organization: your IT department or your business users?
Low-code and no-code capabilities represent a fundamental shift in this power dynamic. These tools allow organizations to grow and adapt on their own terms, without becoming ERP experts and without submitting endless IT tickets for simple customizations.

Your warehouse manager should be able to modify a workflow. Your finance director should be able to create a custom report. Your operations team should be able to adjust processes as business needs evolve. The goal here isn't to eliminate IT, it's to free them from routine customization requests so they can focus on strategic initiatives while empowering business users to solve their own problems in real-time.

AI is more than a feature

Now, let's address AI directly, because we really can't avoid it. Here's my perspective: AI is not just another feature. AI is a robust platform component.

This distinction matters enormously. A feature gets bolted onto existing functionality. A platform component is built into the system's core and woven throughout it. It becomes part of the flexibility, part of the experience, part of the openness, and of course, part of the functionality.

In this context, ERP remains the single source of truth, but its role expands. The system must evolve its data architecture to pull data from multiple sources and provide insights across them. ERP continues to manage core business processes – that hasn't changed – but now, it must also orchestrate interactions between various business applications and AI agents.

The evolution, not decline, of ERP

Some industry observers suggest that traditional ERP is on the decline, being replaced by point solutions and AI agents. I strongly disagree. ERP is evolving, not becoming extinct. Yes, its role is changing. We've already seen this with the shift toward composable ERP architectures and the emphasis on connectivity with external applications. ERP is no longer the monolith that handles every business need, and that's a good thing.

But when we move into an AI-driven world, ERP becomes even more critical. It serves as the core, the single source of truth, the system that synchronizes all business processes across business applications and AI agents. Organizations need that central nervous system. Without it, you have chaos: disconnected data, conflicting processes, and no reliable foundation for AI to work from.

Openness and connectivity: Breaking down the walls

This brings me to one of our core strategic priorities at Priority: openness and connectivity. ERP is no longer the “one and only” system. It's not the monolith managing all business processes and business needs. There are other players, and that's fine, it's even healthy.

What ERP needs are the right tools to connect with other business applications, creating seamless flows for users and enabling integrated insights, automations, and processes.

This happens through APIs (Application Programming Interfaces): the traditional and proven method for connecting business applications in a common language. But as we move into an AI-driven future, we're also focusing on MCP (Model Context Protocol). MCP is essentially like an API, but is designed specifically to connect with LLM (Large Language Model) algorithms. These are the tools that enable conversational AI experiences; the ability to chat with your ERP system the way you interact with ChatGPT or Claude.

Composable ERP: The best of both worlds

The concept of composable ERP has been promoted by Gartner and other analysts for several years now, and I believe it represents the future of business applications, not just ERP. The fundamental insight is this: no single business application, whether it be CRM or ERP, will remain a monolith. Multiple business applications need to communicate and work together seamlessly.

Composable ERP is especially relevant when discussing AI agents and integrated business applications. But, and this is crucial, composability doesn't replace subject matter expertise.

Organizations in specific verticals or industries—whether high-tech, manufacturing, retail, and more, still expect their ERP system to be best-of-breed for their particular needs. They want to start with industry best practices built into the system.

The magic happens when you combine that deep vertical expertise with platform flexibility tools. You begin with proven best practices, then adapt the system to your organization's unique requirements. That's the sweet spot.

Avoiding vendor lock-in

One concern that a lot of ERP shoppers have is vendor lock-in. Organizations have been burned before, and they're rightfully cautious about becoming too dependent on any single vendor.

Our philosophy at Priority is straightforward: we believe in connectivity and openness. Because ERP is no longer a monolith and isn't necessarily the one-and-only solution an organization uses, there's no need for vendor lock-in.
We've built an open system with robust APIs and over 150 tech partners and integrations. Our customers can decide whether to use specific functionality from Priority ERP or to integrate with another dedicated system, whether that's CRM, BI, payroll, or other applications.

Yes, we offer all those capabilities within our system. But if an organization prefers a different solution for any of those functions, they have the freedom to connect it. This applies to AI capabilities as well: organizations can use our built-in AI features or connect to other AI services.

This is what composable ERP really means in practice: choice, flexibility, and control.

The experience challenge

One of our major focus areas in recent years has been user experience, and for good reason. ERP systems are inherently complex. They're rich with functionality because they need to support sophisticated business processes. But here's the challenge: how do you take a complex, feature-rich system and make it intuitive?

Balancing these needs requires thoughtful design. It means personalizing interfaces based on roles and usage patterns. It means progressive disclosure showing users what they need when they need it, without overwhelming them. It means intelligent defaults and guided workflows.

Experience isn't cosmetic. It's fundamental to adoption, productivity, and ROI.

The human side of digital transformation

Beyond technology, there's a human dimension to digital transformation that we must address honestly. Customers tell me they want AI. They like saying “AI.” But often, there's no specific goal attached to that buzzword. And beneath the enthusiasm, there's fear, lack of trust, and significant resistance from teams and employees.

Some of this resistance is rooted in a legitimate concern: will AI replace me in my job?
I'll share my personal belief: AI will not replace most workers. However, it will change their roles. People will need to work together with AI and leverage it to strengthen their capabilities and impact.

Building trust in AI systems

So how do we address these fears and build trust? First, we must be transparent that AI isn't fully autonomous. We keep the human in the loop. These are business decisions, and we want people in the organization to participate in processes. Practical implementation means AI stops and asks for confirmation: “Is this what you wanted to do? Do you approve this transaction?” This “human in the loop” approach helps us maintain control while leveraging AI's speed and analytical capabilities.

Second, we invest in education and training, providing employees with relevant skills. The goal isn't to replace people, it's to augment their capabilities and free them from repetitive tasks so they can focus on higher-value work.

The data quality challenge

There's another challenge that emerges during digital transformation: messy data.
Organizations often have inconsistent, incomplete, or inaccurate data scattered across systems. When you implement AI and expect accurate insights to support decision-making, that messy data becomes a critical liability.

Addressing data quality isn't glamorous, but it's essential. AI amplifies what you feed it: garbage in, garbage out. Organizations must invest in data cleansing, governance, and quality controls as part of their digital transformation journey.

My two cents

If I could give just one piece of advice to organizations looking to implement or upgrade their ERP system, it would be this: Prioritize flexibility above all else.

Yes, features matter. Industry-specific functionality matters. Price matters. But flexibility is what enables your business to scale and grow into an uncertain future.
You cannot know what will change tomorrow. You can't predict new business models, new territories, new regulations, or new competitive threats. What you can do is choose tools that will support any change that happens.

Don't just ask, “Does this ERP system meet our needs today?” Ask, “Will this ERP system enable us to adapt to needs we can't yet imagine?”

Choose a platform that empowers your users. Choose openness over lock-in. Choose cloud over on-premises. Choose systems designed for evolution, not just execution.

Share:

In this article we've covered

ERP

AI

The Author

Keren Sherer Taiber

Chief Product Officer

Since joining Priority in 1998, Keren has progressed through several leadership positions and now leads as the Director of Product Strategy. She has an industrial engineering degree and an MBA from Tel Aviv University. Her journey reflects a consistent dedication to advancement and excellence.