For decades, enterprise software strategy has been largely shaped by a clear dichotomy: build or buy. Organizations in need of scalable digital capabilities often faced a tough decision: invest time and resources into developing in-house solutions tailored to their unique workflows, or buy ready-made commercial off-the-shelf (COTS) software, designed for broader appeal but often lacking deep customization.
But this binary choice is evolving. Today, artificial intelligence (AI)-powered tools are significantly lowering the barriers to custom software development. As a result, enterprises are increasingly leaning toward a new paradigm, Custom Off-the-Shelf: pre-built, modular, AI-assisted, easily customizable applications that strike a balance between bespoke development and COTS software.
This transformation is not just a technological shift either; it signals a fundamental rethink of enterprise software strategy.
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Reframing the Build vs. Buy decision with AI
Historically, the decision to build custom software meant long development timelines, large engineering teams, and high maintenance costs. Therefore, large enterprises usually prefer commercial Software as a Service (SaaS) offering mission-critical systems despite their limited flexibility. This leads to a proliferation of such tools, with software licenses now accounting for 35%–45% of total enterprise Information Technology (IT) spends.
However, generative AI (gen AI), low-code/no-code platforms, and AI agents have drastically tipped the scales. Enterprises can now use AI to create composable applications with off-the-shelf frameworks yet tailored to match the nuance of internal processes.
Rise of the “Custom Off-the-Shelf” model
The term Custom Off-the-Shelf captures this new middle ground. It refers to a modular, AI-enabled approach to software development where enterprises begin with a base set of Application Programming Interface (API)-friendly components, then rapidly tailor them to their environment.
For example, instead of subscribing to a COTS Customer Relationship Management (CRM) platform loaded with features they may never use, companies can now design lean, purpose-built CRM solutions tailored to their sales team’s workflows.
One of the key enablers in this space has been the rise of custom app marketplaces. Technology vendors now offer catalogs of pre-built apps that are easily customizable using APIs and AI tools. Enterprises can use these to co-create value with providers, adapting apps to their environments without building from scratch.
Disruption of SaaS
SaaS has played a key role in driving cloud adoption, but it’s showing its limits:
- Feature bloat and overlapping subscriptions drive cost inefficiencies
- Customization options are often slow or restricted
- Licensing models scale poorly with usage
Enterprises are responding by reducing SaaS footprints. Instead of stacking more SaaS, they orchestrate capabilities through custom off-the-shelf models.
Strategic implications: Beyond software procurement
For enterprise buyers:
- Prioritize platforms that support composability and co-creation models
- Build internal capabilities in platform engineering and prompt design
For software vendors:
- Shift from rigid products to modular solutions
- Embrace marketplaces that allow buyers to extend and adapt offerings autonomously
For service providers:
- Collaborate with clients not just as implementers but as co-builders of tailored digital solutions
- Offer advisory support for enterprises navigating the transition
From Buyers to Builders
The friction traditionally associated with building custom software is falling away. Enterprises no longer need to settle for generic solutions or wait months for vendors to deliver incremental features. Instead, they can harness AI to assemble, personalize, and continuously evolve their software landscape.
Custom Off-the-Shelf is not just a technical evolution anymore; it’s a strategic mindset. It empowers enterprises to shift from reactive procurement to proactive innovation, and in doing so, it may well reshape the future of enterprise software altogether.
To discuss this and other insights from our research on modern application development, please reach out to Manukrishnan SR ([email protected]) and Yugal Joshi ([email protected]).
