What happens when your employees can build better software than the vendors you're paying millions to?
In July 2026, Replit revealed something remarkable.
The company had canceled a seven-figure SaaS solution. Not because it found a cheaper vendor, but because its employees had built an internal application they considered superior—and were already using it.
That's a nightmare scenario for traditional software vendors.
And it may be the beginning of a much bigger shift.
According to McKinsey's August 2026 Global AI Survey, 32% of respondents said their organizations had decided against purchasing at least one software product or feature because they could build the functionality internally using AI coding agents.
For decades, businesses bought software and adapted their workflows around it. Now, AI is making it possible to generate software designed around the workflows themselves.
But does this mean companies should start replacing their ERP, CRM, and HR platforms with AI-generated applications?
Absolutely not. And this is where executive judgment becomes critical.
Figure 1. The New Enterprise Software Playbook: Generate what differentiates your business, buy what demands reliability, and own the foundations that keep everything running. Source: World AI X | Data: McKinsey, August 2026.
What Are Real Companies Doing?
The interesting part is that companies aren't following one strategy. They're making very different decisions depending on what they're trying to achieve.
Company | Strategy | What actually happened |
|---|---|---|
Remote | Configure | Connected Zapier, Slack, Okta, and AI to automate IT support. Reports 27.5% of tickets resolved automatically, saving 616 hours monthly. |
Sears Home Services | Generate | Nontechnical employees created over 50 internal applications, including technician alerts and ticket-management tools. |
Klarna | Buy + own | Moved HR services from Workday to Deel while bringing important organizational knowledge and workflows in-house. |
JPMorgan Chase | Hybrid | Built its own secure enterprise AI platform, LLM Suite, onboarding 200,000 employees within eight months. |
Replit | Generate + replace | Canceled a seven-figure SaaS solution after employees migrated to an internally built alternative. |
These are reported company experiences, not controlled comparisons. But together, they reveal a powerful insight:
The future isn't about building everything. It's about becoming much smarter about what deserves to be bought.
Sources: Zapier / Remote · a16z / Sears · Klarna CEO · JPMorgan Chase · Replit
The Executive Decision Matrix: Generate, Configure, Buy, or Hybrid?
Before approving another software purchase, ask two questions:
How unique is the capability to our business? And how much damage could a failure cause?
Standard business requirement | Unique business requirement | |
|---|---|---|
Lower operational risk | CONFIGURE existing tools. Example: internal approval workflows or support-ticket routing. | GENERATE custom applications. Example: real estate feasibility calculators or specialized sales dashboards. |
Higher operational risk | BUY established platforms. Example: payroll, accounting, or regulated recordkeeping. | HYBRID — build your unique workflows on proven infrastructure. Example: AI-native insurance claims processing. |
This matrix is a starting point, not a substitute for technical and financial assessment.
The logic is simple:
Configure when the capability already exists.
Generate when customization creates value.
Buy when reliability, compliance, and ongoing support matter more than differentiation.
Hybrid when you need both unique capabilities and enterprise-grade infrastructure.
The Trap: Cheap to Build Doesn't Mean Cheap to Own
Imagine your company pays $150,000 annually for a specialized software platform.
Your technology team demonstrates a similar application generated with AI in three days.
Should you cancel the subscription?
Not before answering one question: What will this application cost us to operate for the next three years?
Decision factor | Buy a platform | Generate your own |
|---|---|---|
Initial cost | Licensing, setup, configuration | Development, integration, testing |
Ongoing cost | Renewals, subscriptions, support | Hosting, maintenance, security, AI usage |
Flexibility | Limited by vendor capabilities | Greater customization and control |
Operational responsibility | Shared with vendor | Primarily your organization |
Main risk | Vendor dependency and rising costs | Reliability, security, maintenance burden |
An AI-generated prototype might cost very little. But keeping it secure, reliable, updated, and integrated with critical systems is a different financial proposition.
The real comparison is total cost of ownership, operational risk, and strategic value—not simply how quickly AI can write the code.
The Bigger Opportunity: Build What Makes Your Business Different
Imagine two real estate developers. Both purchase the same CRM, accounting system, and project-management software. But one builds a proprietary AI operating layer that connects land feasibility, architectural constraints, financial modeling, procurement, construction progress, and investment decisions.
Which company is more likely to develop a meaningful operational advantage?
The second company isn't winning because it owns more software.
It's potentially winning because it has embedded its unique business knowledge and processes into a system its competitors cannot simply purchase.
That's where the opportunity gets interesting.
As AI reduces software development costs, companies can increasingly afford to build capabilities that were previously too expensive or too specialized to justify.
The executive playbook is changing:
Configure what already works. Generate what makes you different. Buy what demands proven reliability. Own your data, intelligence, and controls.
The next time your CIO presents a software renewal, don't just ask whether the price is competitive.
Ask whether you still need to buy it at all.
About the Authors
Sam Obeidat is an AI strategist, investor, and venture builder who works at the intersection of AI, business, and capital to turn complex opportunities into scalable ventures and measurable enterprise outcomes. As Founder, President, and Chief AI Officer of World AI X Ventures, he has led 60+ corporate and government AI strategies, helped develop more than a dozen enterprise AI solutions, coached 5,000+ executives worldwide, contributed to AI ventures valued at over $100M, and previously managed investment portfolios exceeding $300M—combining deep strategic insight with the ability to move from idea to execution, commercialization, and scale.
Sam host the Certified Chief AI Officer (CAIO) Program by World AI University, a 6-week executive accelerator that equips leaders to drive AI transformation, redesign business operations, and turn real-world challenges into executable AI initiatives. Program details below.
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