Back in the mid-1990s, I was part of a small team at Intel that worked on the project called WIINGS that managed indirect inventory and was critical to their factory stores. We were told that the ERP rollout will replace our software within a year.
Decades later, its core logic still runs, largely untouched, while UI/UX layers around it evolved. That experience has stayed with me, and today, it feels less like an anomaly and more like a preview. We are at a genuine inflection point, one that will reshape how enterprises think about software, value creation, and competitive advantage.
Custom software will explode
For the last two decades, enterprises outsourced differentiation to SaaS in the name of speed and cost. That trade-off is breaking down. AI has fundamentally altered the economics of software creation. What once required large engineering teams, long cycles, and significant capital can now be done faster, cheaper, and with far more precision. Tools powered by generative AI can scaffold applications, generate APIs, write test cases, and even suggest architectural improvements in real time.
Consider what companies like Netflix did. Instead of relying on off-the-shelf solutions, they built highly customized systems, from their recommendation engine to their content delivery infrastructure. That investment became their moat. Today, what Netflix achieved with elite engineering teams is becoming accessible to every enterprise.
Or look at Shopify. While it is a SaaS platform, its real strength comes from enabling deep customization for merchants, effectively allowing each business to feel like it owns its own stack. That model will extend far beyond e-commerce. We are entering an era where every enterprise can, and should, build software that reflects its unique brand, ‘personality’, and operating model. Custom is no longer expensive. Generic is.
SaaS must reinvent itself, or risk irrelevance
This does not mean SaaS disappears. But its current form is under pressure. The traditional SaaS model is optimized for scale with standardization, multi-tenancy, and feature bundling. The pet peeve amongst CIOs has been that they pay for 100% of a product while using 30% of its capabilities. Worse, they inherit constraints – (SaaS) product roadmaps, design and feature priority they don’t control, innovation they cannot accelerate, and differentiation they cannot express, or it becomes available to all their competitors who also subscribe to the same platform.
We are already seeing the cracks as Salesforce fires the first salvo. They seem to have realized that their customers build extensive custom layers on top of the core platform. SAP, Workday and other SaaS deployments often involve significant customization to fit enterprise workflows.
The next generation of SaaS will look very different as they become composable platforms instead of monolithic suites. They will integrate AI-native extensibility where customization is expected and enabled, not treated as an exception. The pricing model will change to outcome-based pricing rather than seat-based licensing. Embedded intelligence will adapt to enterprise context. In short, SaaS will shift from being the system of record to becoming the system of enablement. The real question is – which ones?
Tech debt will no longer be inevitable
For years, tech debt has been treated as a necessary evil, a byproduct of speed and scale. That assumption is about to be challenged. AI-driven development environments can now continuously refactor code, identify inefficiencies, and enforce best practices. Testing can be exhaustive rather than selective.
Imagine a world where the legacy codebases are modernized incrementally without massive rewrites, security vulnerabilities are detected and patched proactively, and the architecture evolves dynamically based on usage patterns. Over time, the concept of ‘accumulated debt’ will give way to ‘continuous renewal.’
Software quality will improve 10x
Quality has historically been constrained by human limitations – time, attention, and the ability to anticipate edge cases. AI changes that equation. With AI generating test scenarios, identifying vulnerabilities, simulating user behavior, and monitoring systems in real time, the gap between expected and actual performance will shrink dramatically. Systems will become more resilient, adaptive, and self-healing with fewer outages, stronger firewalls, faster recovery, and significantly better user experiences.
The shift CxOs must recognize
This is not just a technology evolution. It is a strategic reset. For years, the dominant question was “build vs. buy.” That binary framing is obsolete. The real question now is, where do we differentiate, and where do we commoditize? The core vs. context decision framework becomes even more relevant now. Forward-looking enterprises are already moving in this direction. They are investing in internal platforms, leveraging AI to amplify engineering productivity, and reclaiming ownership of their digital capabilities.
Several forward-looking trends are emerging that CxOs should pay close attention to:
- AI as the new development layer: Not just a tool, but a collaborator embedded across the lifecycle. I talked about cognitive architecture in one of my earlier blogs, which will gain importance even in product development lifecycle
- Hyper-personalized enterprise systems: Software that adapts to individual roles, workflows, and decisions. Imaging one business analyst, one developer and a coding agent churning out an app that achieves 100% of business objectives, with no tech debt and can evolve in near real-time
- Innovation harvesting at scale: Similar to hyper-personalized software, a two-person + AI team can create a prototype and validate it without having to go through budget and bureaucratic approvals. Ideas will move from concept to production in days or weeks, not quarters
- Digital sovereignty: Enterprises regaining control over their data, logic, and differentiation
The implication is no less than seismic. Software is no longer just an enabler of business strategy, it is the business strategy and, once again, will become a differentiator amongst peers.
We are coming full circle. The industry moved from custom-built systems to standardized SaaS in pursuit of efficiency. Now, enabled by AI, we will return to custom, but at a completely different scale and speed. The organizations that recognize this shift and adopt early will not just modernize their IT; they will redefine their competitive advantage. And those that don’t may find themselves constrained by the very systems that once promised to accelerate them.