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IVP - The Value of Vertical AI - September 2024 logo

IVP - The Value of Vertical AI - September 2024

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Exploring the transformative potential of vertical AI

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Type
Open Source
Company
IVP
Visit Website GitHub (38 stars)

About IVP - The Value of Vertical AI - September 2024

This article from IVP, published in September 2024, analyzes the transformative potential of vertical AI compared to traditional vertical SaaS. It argues that LLMs enable replacement of labor in repetitive processes, leading to larger total addressable markets (TAM) and higher willingness to pay. The piece outlines two primary wedges: cost efficiency optimization (e.g., saving weeks in industrial design, accelerating insurance claims review, predicting equipment maintenance) and incremental revenue generation (e.g., AI order-taking in quick-service restaurants, analytics for home services conversion, ecommerce inventory optimization). It notes that vertical AI startups exhibit stronger retention rates than horizontal AI peers due to clear ROI and fast time-to-value, though overall AI products have faced higher churn rates initially.

Key Features

Cost efficiency optimization through automation of manual processes
Incremental revenue generation via AI-driven sales and analytics
Stronger retention rates than horizontal AI products
Higher willingness to pay compared to traditional seat-based software
Fast time-to-value with clear ROI for underserved industries

Pros & Cons

Pros
  • Vertical AI offers clearer ROI and faster time-to-value than horizontal AI
  • Enables cost structures that significantly reduce labor spend
  • Translates to larger TAM due to higher customer willingness to pay
  • Helps businesses differentiate in competitive industries and strengthen customer relationships
  • Average retention rates are stronger for vertical AI startups compared to horizontal peers
Cons
  • AI product churn rates have been higher than traditional SaaS over recent years
  • Not all types of work in all verticals can be automated
  • Initial adoption requires transitioning from experimentation to utility, which can be slow

Best For

Industrial design and simulation (e.g., wind turbines, automobiles) saving weeks and engineering hoursInsurance claims review acceleration for top insurersPredictive equipment maintenance for global manufacturing firmsAI order-taking in quick-service restaurant drive-thrus to increase throughput and average order valueHome services companies improving conversion rates and ticket sizes via AI analyticsEcommerce inventory prediction and dynamic pricing to prevent stockouts

FAQ

How is Vertical AI different from Vertical SaaS?
Vertical AI replaces labor (internal or outsourced) rather than just aiding it with software, enabling fundamental cost structure changes and larger TAM.
What are the main use cases for Vertical AI?
Two primary wedges: cost efficiency optimization (e.g., automating manual processes) and incremental revenue generation (e.g., improving sales and analytics).
Why do vertical AI startups have better retention than horizontal AI?
Because they focus on making expensive, time-consuming manual processes cheaper and more efficient, delivering measurable value and clear ROI.