Mark Cuban advises graduates to approach small to medium-sized, non-tech companies. He suggests they identify manual, tedious processes and offer to build AI agents to automate them, creating immediate value where internal AI resources are lacking.
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Most companies are not Vanguard tech firms. Rather than pursuing speculative, high-failure-rate AI projects, small and medium-sized businesses will see a faster and more reliable ROI by using existing AI tools to automate tedious, routine internal processes.
The new wave of entrepreneurship isn't about scaling large companies. It's about solopreneurs acting as "gig entrepreneurs" who master and customize a suite of AI tools to deliver bespoke, high-value outcomes for clients, effectively replacing the work of entire small agencies.
Founders are stuck in a SaaS mindset, selling tools to existing service providers. The bigger opportunity is to build new, AI-first service companies (e.g., accounting, legal) that use AI to deliver a superior end-to-end solution directly to customers.
Instead of incurring debt for a traditional education, aspiring tech entrepreneurs can launch an AI automation agency. This model allows them to learn cutting-edge skills by solving real-world client problems, effectively getting paid for their own professional development.
SaaS companies serving SMBs in non-tech industries can create a new revenue stream by offering a managed service—using humans-in-the-loop but framed as an "AI boost"—to run marketing campaigns for them. This provides immense value and captures more of the customer's budget.
Don't start with a broad market. Instead, find a niche group with a strong identity (e.g., collectors, churchgoers) that has a recurring, high-stakes problem needing an urgent solution. AI is particularly effective at solving these 'nerve' problems.
To bridge the AI skill gap, avoid building a perfect, complex system. Instead, pick a single, core business workflow (e.g., pre-call guest research) and build a simple automation. Iterating on this small, practical application is the most effective way to learn, even if the initial output is underwhelming.
Flexport is upskilling its non-technical staff through a 90-day "AI boot camp." By giving domain experts one day a week to learn low-code AI tools, the company empowers them to automate their own repetitive tasks, turning them into "lightweight engineers" who are closest to the problems.
Traditionally, service businesses lack scalability for VC. But AI startups are adopting a 'manual first, automate later' approach. They deliver high-touch services to gain traction, while simultaneously building AI to automate 90%+ of the work, eventually achieving software-like margins and growth.
To build an effective AI product, founders should first perform the service manually. This direct interaction reveals nuanced user needs, providing an essential blueprint for designing AI that successfully replaces the human process and avoids building a tool that misses the mark.