If AI lowers the cost of building applications, where does scarcity move, and what new opportunities appear?
The abundance hypothesis
AI software-generation tools are lowering some of the barriers to producing prototypes and applications. That does not mean development is free, or that any automatically generated system is fit for production. Integrations, security, maintenance and adoption still take work.
But the shift in costs deserves a strategic question: if building an interface becomes easier, what becomes relatively harder?
Scarcity moves
When one activity gets cheaper, value can concentrate in other stages. In enterprise software, some candidates are defining relevant problems, authorized access to quality data, integration with real processes, verification, distribution, compliance and trust.
No law guarantees that shift in every market. Some companies will capture value with new horizontal tools; others will find their customers still prefer integrated providers. The competitive context matters.
Four spaces to investigate
- Verification: testing, auditing and observability of applications generated or maintained with AI assistance.
- Integration: connecting scattered solutions with existing systems, permissions and processes.
- Governance: knowing what software exists, who uses it, what data it touches and when it should be retired.
- Operation: ensuring continuity, support and business results beyond the initial prototype.
These are hypotheses about business spaces, not validated segments or market-size estimates.
How to test them
An economic experiment can start with interviews with IT and operations leaders, followed by a manual test of a single problematic workflow. You need to measure how often the incident occurs, what it costs to resolve, the budget available and who would have purchasing authority.
If the problem rarely occurs, the solution is easy to replicate or no one controls the budget, the opportunity weakens. An early negative result is also strategic knowledge.
More software, better organizations?
Abundant application generation could democratize capabilities and enable useful experiments. It could also multiply ownerless assets and operational complexity. Both outcomes are plausible.
Competitive advantage may lie less in producing the next program and more in understanding what work should exist, how its value is verified and who answers for how it runs.
Know more. See further.
Exploring uncertainty with rigor is part of intelligence work.