Identifying High-Growth AI Applications: Patterns and Opportunities
5 Ways AI Actually Makes Money Right Now
The AI industry is young. Big tech has spent hundreds of billions on AI infrastructure, and skeptics keep asking: where's the money? While cloud providers are the obvious winners so far, we're starting to see the first wave of successful AI startups. It may take a decade to see unicorns emerge, but the early signs are promising.
As an angel investor, I hunt for fast-growing AI companies. I learn from two main sources: my own portfolio's investor updates and Y Combinator's trends. YC especially interests me because they see hundreds of AI startups each batch. Their recent YouTube episode highlighted several AI companies growing exceptionally fast.
I've noticed patterns in successful AI startups. Here's what's working now, where I see opportunities, and what founders should look for when building in these spaces.
Key Patterns in Rapidly Growing AI Applications
Pattern #1: AI Replacing Specialists
AI is best at taking over specialized work that's repetitive and data-heavy. Parahelp shows this perfectly - they built an AI support agent that handles customer tickets from start to finish. It's growing fast because it solves a clear pain point.
I've invested in two similar companies. Tusk helps engineering teams automate UI testing & generate unit tests, and Praxos automates routine tasks for insurance agents. Both succeeded by targeting specific roles where humans spent too much time on repetitive work.
Pattern #2: AI as a Speed Multiplier
The best AI tools don't just replace humans - they make existing processes dramatically faster. Momentic helps engineering teams test software in minutes instead of days. In my portfolio, Keye cuts due diligence time for PE firms from weeks to hours. Clear Way shrinks EV charging station documentation production from months to days.
Pattern #3: AI That Learns You
The most exciting AI apps don't just work - they adapt to each user. Fluently, one of my investments, personalizes English teaching based on how you actually speak and what interests you. YourStory creates custom learning paths for K-12 students, adapting to their strengths and weaknesses.
I'm drawn to these companies because I experienced the power of personalized learning firsthand. When I moved from Belarus to the U.S., the freedom to learn at my own pace changed everything. That's what good AI does - it meets you where you are.
Pattern #4: AI as Your Data Brain
AI shines when it has to process mountains of data that would overwhelm humans. Outset turns hours of user interviews into actionable insights in minutes. Entangl, one of my investments, spots engineering problems and fixes them before they cascade - something that used to take whole teams weeks to do. Another company in my portfolio, Metreecs, uses AI to provide deman forecasting, reducing stockouts and unsold inventory for retailers.
Pattern #5: AI Talking to Humans
The best AI isn't just a chatbot - it handles complex human interactions. Apriora conducts entire job interviews, asking follow-ups and probing candidates just like a human recruiter. Toma, one of my investments, makes sales calls and handles customer service for car dealerships, closing deals and solving problems in real-time.
These companies work because they do one thing really well: have natural conversations at scale. No more choosing between personal touch and reaching everyone.
Potential Areas for Growth
Building on these patterns, several promising areas emerge where AI can create significant value:
Legal Services Automation
Legal processes are extremely costly, data-intensive, and repetitive, making them ideal for AI automation. Similar to how Keye automates due diligence, AI can take over routine legal tasks, increasing efficiency and reducing costs. AI Paralegals or Legal Assistants can automate document review, case law research, and contract analysis. From the insanely funded examples of Harvey to YellowPad in my portfolio, this space is highly competitive with winners yet to emerge.
Healthcare Support and Diagnostics
The healthcare sector presents vast opportunities for AI-driven transformation. AI can enhance both the efficiency of healthcare delivery and the quality of patient care through data-driven insights and personalized interactions. From intelligent intake systems to preliminary diagnostic support, AI can streamline numerous aspects of healthcare delivery. Similar to how modern AI handles customer support, these systems can engage with patients to collect symptoms and provide initial guidance. An important note on healthcare is that due to extensive regulations, innovation will take longer here compared to other sectors. Looking at YC companies funded in 2023 and 2024 alone, you'll find 111 companies in this space. A notable example from my portfolio is Syntra.
Financial Advisory and Planning
The financial services sector is ripe for AI transformation. By combining data analysis with personalized guidance, AI can revolutionize how financial advice is delivered. These systems can automate routine financial tasks while providing tailored recommendations based on individual circumstances and goals.
Real Estate Services
The real estate industry stands to benefit significantly from AI-powered solutions. Modern platforms can transform property searches, conduct virtual tours, and handle buyer/seller queries with unprecedented efficiency. Early companies in this space that I talked to this year include Modern Realty and Bramble.
Supply Chain and Logistics Optimization
In logistics, AI can process vast amounts of real-time data to optimize operations, similar to how Momentic enhances software testing processes. AI logistics coordinators can streamline operations, predict demand, and optimize routes, bringing new levels of efficiency to supply chain management.
Human Resources and Employee Training
The workplace presents numerous opportunities for AI implementation, from streamlining recruitment processes to personalizing employee development. Building on successful approaches in customer interaction, AI can transform internal processes like orientation, training, and feedback collection while enhancing workplace satisfaction.
Education and Skill Development
Educational AI systems can provide truly personalized learning experiences, adapting to individual learning styles and needs. Whether in academic settings or corporate training, AI can facilitate more effective skill development through customized approaches and engagement strategies.
Marketing and Sales Automation
Following the early success of companies like Toma and Pipeline in my portfolio, there's significant potential for AI to transform customer engagement across marketing and sales. AI can optimize campaigns through sophisticated data analysis while handling customer inquiries and lead nurturing at scale.
Want to use AI to fix an industry? Start by finding what's broken. Look for:
Tasks that eat up talented people's time
Processes that are slow because humans can't handle the data
Services that would be better if they adapted to each user
Conversations that need a human touch but should happen at scale
If you're building something like this, I want to hear about it.
I think its just my personal bias to focus on app layer. Plenty of room in infra layer, as Scale AI is doing mostly expensive contracts these days, and startups are under-served.
Sounds like you're focused mostly on the application layer. Any insights or moves further down the stack? For example, PublicAI.io is paying experts to improve AI with niche data; an infrastructure play especially aligned with "Pattern #1: AI Replacing Specialists."