Differentiated Businesses Are Turning Away from One-Size-Fits-All
by Greg Lemiska
(Updated from the December version, located here.)
In 2024, the global enterprise software market exceeded $700 billion (Grandview Research). Yet, less than 7% of that was spent on custom-built solutions. That imbalance is starting to shift.
For decades, businesses favored commercial-off-the-shelf (COTS) platforms like SAP, Oracle, and Salesforce, trading customization for cost savings, fast deployment, and predictable support. But the emergence of large language models, AI agents, and flexible data infrastructure fundamentally reshapes what custom software means - and its cost/benefit equation.
Why Off-the-Shelf Dominated
Packaged software became dominant because building enterprise-grade systems is notoriously difficult. Vendors amortized that complexity across thousands of customers.
Reduced Cost: Shared development costs made the software affordable.
Fast Deployment: Deployments could be completed in weeks, vs. development taking years.
Vendor Support: Someone else handled regular updates and security patches.
However, this model came with tradeoffs, specifically flexibility. Businesses were forced to adjust their workflows to match the software, limiting innovation and adaptability. Custom features became expensive and risky bolt-ons, not native differentiations.
What Held Custom Back
Even though custom software offered better alignment with unique business needs, it carried significant risks:
Maintenance Costs: Updates and bug fixes required dedicated resources.
Scalability Issues: Scaling custom systems often meant expensive redesigns.
Data Rigidity: Traditional databases couldn’t handle dynamic data structures.
These challenges made custom software impractical for all but the most innovative organizations, but these barriers are crumbling. Advances in generative AI and modern databases mean that what once required dozens of engineers and years of investment is possible with smaller teams and faster cycles.
AI Changes the Equation
AI has fundamentally shifted how we build and manage software. Tools like GitHub Copilot, Claude, and Devin act as intelligent copilots, speeding up development, debugging, and testing. But the bigger story is what happens at runtime:
Autonomous Maintenance: Systems that monitor themselves, flag anomalies, and propose or even deploy fixes.
Scalable Infrastructure: AI-powered resource planning optimizes usage and cost in real-time.
Agent-Oriented Interfaces: Instead of static forms or menus, businesses are deploying AI agents that interface with backend systems, orchestrate workflows, and deliver natural, more intuitive experiences.
This isn’t just faster, cheaper software - it’s adaptive software.
Modern Databases = Flexibility at the Core
The data layer has always been just as important as the code or the UX. Old RDBMS systems required rigid, predefined schemas. Today’s best systems use:
Graph databases for complex, evolving relationships
Vector databases for semantic search and generative AI integration
Multimodal stores that handle structured and unstructured data side-by-side
These new technologies unlock agile data modeling and real-time learning loops.
Custom Software Does Things That Packaged Software Can’t
Imagine a company trying to embed augmented reality (AR) product demos into its sales experience. The best-case scenario for a company using a big-name CRM is that a third-party developer builds something into the developer's ecosystem, putting companies back into the “risky bolt-on” situation.
A custom platform using GenAI and graph models could:
Generate contextualized product demos based on real-time customer data.
Adjust scripts and visual flows dynamically based on industry, persona or deal stage.
Learn over time - getting better with each interaction
With AI and modern data architecture, this innovation no longer requires moonshot budgets. It’s not just possible - it's practical.
The Bottom Line is Always Financial
Software investment decisions all come down to a business case. Previously, only the highest-value drivers and differentiators could justify custom software development and maintenance costs. As that cost comes down, the business cases for custom software get stronger. With the combined power of AI and modern database tech, custom software is no longer a high-maintenance, inflexible option. Instead, it’s becoming a scalable, efficient solution for businesses that succeed based on their ability to differentiate.
The Hybrid Future
Off-the-shelf software isn’t going away. Off-the-shelf still makes sense for non-differentiating processes (think payroll, compliance, procurement, etc.). But increasingly, businesses will adopt a hybrid approach:
Standardized back-office software for commodity processes.
Custom front-end systems where competitive advantage lives
That means that the market won’t stay 90% COTS for long. We’ll see a shift to 60/40 or even 40/60 as businesses realize that differentiation comes from how they use software, not just what they buy.
A Call to Innovators
The next generation of business leaders will not just adopt new technology - they will architect new capabilities. With the barriers to custom software falling away, there has never been a better time to rethink what your software can do.
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