Executive Summary
For decades, executives have debated whether to build or buy software. AI has changed the dynamics, but the fundamental principle has become clearer than ever:
-
Buy more often than you build. Mature, complex, regulated systems are safer to source from vendors.
-
Build only when it increases your competitive gap or creates a unique value proposition. That is where differentiation, margins, and long-term survival live.
-
Augment with AI agents to bridge gaps, integrate platforms, and accelerate productivity.
The cost of building commodity systems is escalating. The upside of building differentiators has never been higher.
1. Why Buying is the Default
Most enterprise systems today are not where you win. They are necessary infrastructure, governed by rules, regulations, and edge cases that have been ironed out over decades.
-
ERP, payroll, compliance, and procurement systems are heavy with regulatory complexity.
-
Rebuilding them is not innovation. It is reinventing the wheel under stricter deadlines and greater scrutiny.
Case Examples of Buying
Hershey’s ERP Failure: Hershey’s $150M Halloween miss in 1999 stemmed from trying to build and implement custom systems in-house instead of leaning on proven vendors. The lesson: building where compliance and scale are at stake can be catastrophic.
Target Canada: Target entered Canada with a homegrown supply chain platform. Data quality issues caused chronic stockouts and overstocks, eventually leading to a $2B retreat from the market.
Executive Takeaway: Buying reduces risk and shortens time-to-value. If you are not seeking to differentiate, default to buy.
2. When Building is Worth It
The only justifiable reason to build is when it creates a gap competitors cannot easily close.
-
Netflix’s Recommendation AI: Built in-house, it drives 80% of viewing hours and is central to customer stickiness.
-
Tesla’s Autopilot Stack: Built internally because no vendor solution could deliver their vision of autonomy.
-
Amazon Logistics: Its robotics and routing systems are not off-the-shelf. They are the moat behind Prime delivery promises.
Executive Takeaway: If the system is tied directly to how you win in the market, you build. Otherwise, you are just adding risk and cost.
3. The Third Path: Augment with AI Agents
Between build and buy sits a fast-growing option: augmenting vendor systems with AI agents and orchestration.
-
JPMorgan uses AI copilots to generate compliance reports and reconcile trades across legacy systems, reducing time from weeks to minutes.
-
Walmart layered AI-driven scheduling on top of its HR systems to optimize labor deployment.
The Role of MCP (Model Context Protocol)
The emerging Model Context Protocol provides a standard way for AI agents to interact with enterprise systems. Think of it as a common language that lets AI pull data, trigger workflows, and coordinate across platforms. This turns bought systems into AI-ready infrastructure rather than black boxes.
Executive Takeaway: Even when you buy, demand openness and MCP-readiness. Augmentation is how you keep up with the pace of AI.
4. The Build-Buy-Augment Matrix
System Type | Best Approach | Why |
Mission-critical, compliance-heavy (ERP, payroll, risk systems) | Buy | Risk is high, complexity is mature, no differentiation payoff. |
Differentiators (recommendations, pricing intelligence, autonomy) | Build | Creates defensible competitive gap, defines customer value. |
Workflows, integration, orchestration | Augment | AI agents and MCP deliver speed without heavy rebuilds. |
5. The Executive Checklist
-
Audit systems: For each, ask, “Does this create a competitive gap?”
-
Default to buy: Unless the answer is yes, buy.
-
Invest where it matters: Build only where survival or differentiation depends on it.
-
Future-proof purchases: Require MCP-ready, API-rich platforms.
-
Double down on discovery: Technology can build anything; executives must decide what is worth building.
6. Embracing the Future of Software Decisions
In the age of AI, buy is the rule, build is the exception. But the exception matters: when chosen wisely, a build strategy creates lasting moats. When chosen poorly, it drains resources on commodity problems.
The winning formula for executives: Buy what you must, build what defines you, and augment everything else with AI agents.
Conclusion
Navigating the software landscape requires a strategic approach. The decision to build or buy is no longer a binary choice. With the advent of AI, we can now augment existing systems to enhance functionality and efficiency. This hybrid approach allows us to leverage the best of both worlds. So, as we move forward, let’s embrace this evolution and make informed decisions that drive our organizations toward success.
Article tools