Redcar - Vertical AI vs. Horizontal AI

The world is rapidly adopting different types of AI—from chatbots for multiple departments (horizontal) to specialized tools (vertical) to hyper-focused solutions for specific industries (industry-specific vertical).

This guide explains each approach, why adding AI to older SaaS platforms usually isn’t enough, and why most organizations benefit from combining horizontal and vertical AI strategies.

TL;DR

1. Use Horizontal AI to create a common AI layer that all teams can tap into.
2. Add Vertical AI for functional areas where you need deeper, more specialized features.
3. One Horizontal AI + multiple Vertical AIs for functional teams is best for companies.

Types of AI

Horizontal AI
‍A general AI platform that any team in your company (Sales, HR, Finance, Operations) can use. This is typically a ChatGPT-like chatbot.

• Key Benefit: Upload data once, and everyone can access it.
• Challenge: The experience will feel hard to use for every team except for in simplest cases. Functional teams will want their dedicated environment (engineers want Cursor for coding, for example). Finally, different teams’ data might accidentally mix.

Vertical AI
‍‍A specialized solution built for a particular function, like Sales outreach or Customer Support.

• Key Benefit: Highly accurate and user-friendly for that specific team.
• Challenge: You’ll need to connect it to your data (e.g., Salesforce), and managing multiple vertical tools can be complex.

Industry-Specific Vertical AI
‍‍An even more specialized version of vertical AI tailored to a specific industry (e.g., property management, primary care doctors).

• Key Benefit: Integrates with industry-standard platforms (e.g., Epic Electronic Healthcare Records) and often includes proprietary data or research.
• Challenge: Narrow focus makes it not useful for broad company types, so they have less R&D budget to develop features.

Why Horizontal AI + Last-Generation SaaS Falls Short

Old-school SaaS tools typically weren’t built with AI in mind. Simply layering a Horizontal AI solution on top can create issues:

• Rigid Data Structures: Legacy systems often store data in ways that AI can’t easily analyze.
• Poor Integration: Outdated APIs and limited automation options can slow or block AI-driven workflows.
• Disjointed Experience: Users end up juggling multiple logins, incomplete data syncs, and patchwork features.

An example is an end-to-end sales workflow that lets sales reps paste in a set of targeted accounts, fetch external data on those accounts (LinkedIn profiles, job posts, etc), reasoning based on that data, crafting a personalized template, and then crafting a personalized message.

Besides integration problems, dedicated UX saves users a lot of time and minimizes errors.

Pros and Cons Summary

Pros

Cons

Horizontal AI

-One central AI for all teams
-Easier data sharing

- Risk of mixing sensitive data
- Does not offer deep specialization

Vertical AI

- Tailored for one function
- More accurate and functional within that domain

- Requires multiple solutions for different functional areas
- Will need to integrate data sources more than once (until there is a universal data pipeline)

Industry-Specific Vertical AI

- Built for a single industry
- Can include proprietary datasets

- Narrow scope
- May have less support for software due to niche nature

Combining Vertical with Horizontal AI is the way to go

Combining Horizontal AI with Vertical AI often gives the best results. Have one Horizontal AI as a chatbot, ideally integrated into your communications tool (eg Slack), then add vertical solutions for different functional teams to get deep specialization. As your business evolves, you swap different AI solutions as needed.

Conclusion

Get both broad coverage of a horizontal platform and deep specialization of vertical solutions. As your business evolves, you can keep your core AI system in place while adding or swapping vertical tools as needed.

It's a high-stakes environment to make the transition to a post-AI world. Companies will win or lose based on how successful they are at maximizing the impact of AI.

When planning your AI strategy, consider how each solution type — horizontal, vertical, or industry-specific — fits your organization’s goals. Avoid relying solely on older SaaS platforms.Combine modern AI solutions (vertical and horizontal) to boost efficiency, drive innovation, and stay competitive.

For additional content, watch this Y Combinator video on why Vertical AI Agents Could Be 10X Bigger Than SaaS