What to Build in the Age of Artificial Intelligence

Every week, another headline claims AI will replace software developers. Every month, a new AI tool promises to eliminate the need for custom applications. If you are reading this, you might be wondering: Is it too late to build a SaaS? Has AI already taken all the good opportunities?

The short answer is no. The slightly longer answer is that AI has actually expanded the market for specialized software, not shrunk it. But the nature of what gets built, and who builds it, is changing fundamentally.

The Fear: AI Will Build Everything

The fear is understandable. Watch a demo of Claude Code or Cursor, and you will see applications being built in minutes. Tasks that once took weeks now take hours. If AI can build software this fast, why would anyone pay for SaaS products? Why would customers not just generate exactly what they need?

This line of thinking contains a critical error. It confuses the ability to generate code with the ability to solve business problems.

Why ChatGPT Cannot Book Your Hotel

Consider a simple task: booking a hotel room. You might think: "I will just ask AI to build me a hotel booking system."

Try it. Ask any AI to create a complete hotel booking platform. You will get something that looks functional but lacks:

Integration with hotel property management systems
Real-time inventory management
PCI-compliant payment processing
Multi-currency support for international travelers
Cancellation policies that vary by property and season
Loyalty program integration
24/7 customer support infrastructure

The UI is easy. The business logic is hard. The integrations are harder still. The regulatory compliance is hardest of all.

This pattern repeats across every industry. From trucking logistics to medical scheduling to legal document management, the interface is the easy part. The domain knowledge, integrations, compliance requirements, and operational complexity represent years of accumulated expertise.

The SaaS Demand Is Growing, Not Shrinking

Research from Gartner shows the SaaS market growing from approximately $197 billion in 2023 to an estimated $232 billion in 2024. This growth is happening alongside the AI revolution, not despite it.

Why? Several factors:

1. AI Creates New Categories of Software

AI does not just replace existing tools. It enables entirely new categories:

AI-powered analytics that were previously impossible
Real-time personalization at scale
Predictive maintenance for industrial equipment
Automated compliance monitoring for regulated industries

Each of these categories spawns multiple SaaS products. The playbook that created Salesforce, Slack, and Zoom is now creating the next generation of AI-native applications.

2. Vertical SaaS Opportunities Are Exploding

Horizontal tools like spreadsheets and email work for everyone but solve no one's specific problems perfectly. Vertical SaaS products target specific industries:

Construction project management
Veterinary practice software
Brewery inventory systems
Dance studio scheduling

These vertical markets were previously too small to support traditional software development. With AI-assisted development, a single developer can serve a niche market profitably. The addressable market for SaaS has expanded from "fortune 1000 companies" to "any business with a specific workflow."

3. The Integration Economy

Every business now runs on dozens of software tools. Each integration point represents friction. Each data silo represents lost efficiency. The companies solving integration problems, data synchronization challenges, and workflow automation are thriving.

AI makes it easier to build these integrations. It does not eliminate the need for them.

What to Build: Three Frameworks

If you are considering building a SaaS in the AI age, here are three frameworks for finding opportunities:

Framework 1: The "Interface Sucks" Test

Find a process where businesses still use:

Spreadsheets for tracking complex data
Email for coordination
Phone calls for status updates
Manual data entry between systems

If people are using general-purpose tools for a specific workflow, there is room for specialized software. The interface might be simple to build, but the workflow understanding is valuable.

Framework 2: The "Compliance Required" Filter

Regulation creates moats. Consider:

HIPAA compliance for healthcare
SOX compliance for financial reporting
GDPR compliance for European data
SOC 2 for enterprise SaaS

Businesses cannot simply generate their own compliance solutions. They need software that has been audited, documented, and proven. AI can help you build compliant software faster, but the compliance itself remains a barrier to entry.

Framework 3: The "Integration Depth" Opportunity

The deeper your software integrates with a customer's existing systems, the harder it is to replace. Look for:

Multiple API integrations required
Data migration complexity
Custom workflow configurations
Industry-specific data formats

These integrations are tedious to build, which makes them defensible. AI makes the tedium manageable. The defensibility remains.

The New Moat: Speed and Understanding

In the pre-AI era, technical execution was the primary moat. The company with better engineers built better software faster. That advantage is eroding.

The new moats are:

Domain Expertise

AI can write code. It cannot understand your customer's business as deeply as you can. The founder who spent five years in logistics has an advantage over the generalist using the same AI tools.

Speed to Market

AI compresses development timelines. The advantage goes to those who ship fastest. A six-month head start in a market that previously took two years to enter is now an overwhelming advantage.

Customer Relationships

Software is increasingly commoditized. Relationships are not. The founder who understands customer pain points, responds to feedback quickly, and builds trust will win against technically superior competitors.

What Not to Build

Just as important as knowing what to build is knowing what to avoid:

Pure AI Wrappers

If your entire product is a thin layer over GPT-4 with no additional value, you have no defensibility. The moment OpenAI adds your feature to their interface, your business disappears.

Undifferentiated Horizontal Tools

Another project management tool. Another note-taking app. Another to-do list. Unless you have a genuinely novel approach, these markets are saturated.

Solutions Looking for Problems

Building AI into your product because AI is trending, not because it solves a real customer problem. Customers pay for outcomes, not technology.

The Opportunity Window

The next five years represent an unprecedented opportunity for SaaS builders. AI has made development faster and cheaper. It has not made domain expertise less valuable. It has not eliminated the need for specialized software in specialized industries.

The companies that thrive will be those that:

Move fast while others debate whether to start
Focus on deep vertical problems, not surface-level AI features
Build genuine moats through integration, compliance, or domain expertise
Treat AI as an accelerator, not a replacement for understanding their customers

The question is not whether to build. The question is what to build, and how fast you can ship it.

In the next chapter, we will examine whether SaaS remains a profitable business model in this new landscape, and why the economics might actually be improving for independent builders.

Ready to learn why SaaS is still profitable? Continue to Is Building SaaS Still Profitable?