Profitable AI Business Models to Consider

AI is finally making services businesses scalable—and—exciting to VCs. The global services market is in the trillions of💰s, far larger than today’s software market. Yet, services businesses haven’t been the darlings of venture capital, as they were perceived to lack rapid scaling potential. 𝗔𝗜 𝗶𝘀 𝗰𝗵𝗮𝗻𝗴𝗶𝗻𝗴 𝘁𝗵𝗮𝘁. By blending AI seamlessly with human expertise, there is an opportunity to get into much larger markets with models that have the potential to scale in ways services - or even SaaS businesses - can't. For example, instead of offering a marketing SaaS, an AI-powered Service-as-Software business can deliver what the customer really wants: high-quality leads or compelling content. We’ve seen this potential firsthand through Emergent Ventures’ investments in multiple AI-powered companies that leverage humans-in-the-loop. These models resonate with B2B customers because they offer faster, clearer paths to value—reliable outcomes delivered with greater efficiency. For many customers, it’s a significant upgrade over traditional agency or service-provider relationships. While the potential is huge, only a fraction of AI-powered services startups will scale. 𝗦𝘂𝗰𝗰𝗲𝘀𝘀 𝗱𝗲𝗽𝗲𝗻𝗱𝘀 𝗼𝗻 𝘁𝗵𝗼𝘂𝗴𝗵𝘁𝗳𝘂𝗹 𝗲𝗮𝗿𝗹𝘆 𝗰𝗵𝗼𝗶𝗰𝗲𝘀 𝗮𝗻𝗱 𝗲𝘅𝗰𝗲𝗽𝘁𝗶𝗼𝗻𝗮𝗹 𝗲𝘅𝗲𝗰𝘂𝘁𝗶𝗼𝗻. Here’s what we have learned works well: 𝟭. 𝗔𝗜-𝗛𝘂𝗺𝗮𝗻 𝗦𝘆𝗻𝗲𝗿𝗴𝘆: AI and software should do the heavy lifting, with humans involved strategically— e.g. for validating AI output, edge cases, enabling adoption, or acting on AI insights. Over time, reduce human input as the AI learns, and models improve. Target 60%+ initial gross margins, with a path to SaaS-like 75%+ margins over time. 𝟮. 𝗦𝗰𝗮𝗹𝗮𝗯𝗹𝗲 𝗛𝘂𝗺𝗮𝗻 𝗜𝗻𝘃𝗼𝗹𝘃𝗲𝗺𝗲𝗻𝘁: The dependency on hiring & training humans should not constrain scale and economics. Have a path to tapping into freelancers or agency partners. Leverage human experts in a high-talent location such as India. 𝟯. 𝗥𝗲𝗰𝘂𝗿𝗿𝗶𝗻𝗴 𝗥𝗲𝘃𝗲𝗻𝘂𝗲: Focus on high-value, recurring use-cases to ensure subscription-based revenue with strong net revenue retention (NRR). 𝟰. 𝗣𝗿𝗶𝗰𝗶𝗻𝗴 𝗣𝗼𝘄𝗲𝗿: Iterate to a solution that can command higher pricing, and a model that aligns incentives with customers, e.g. based on outcomes. 𝟱. 𝗗𝗮𝘁𝗮 𝗠𝗼𝗮𝘁𝘀: Build solutions that improve with use, creating compounding competitive advantages over time. 𝟲. 𝗠𝗼𝗱𝘂𝗹𝗮𝗿 𝗧𝗲𝗰𝗵: Architect a stack that can evolve with AI advancements. 𝟳. 𝗙𝘂𝗹𝗹-𝗦𝘁𝗮𝗰𝗸 𝗧𝗲𝗮𝗺: A founding team that has the technical expertise to build and rapidly improve complex AI-powered solutions, and deep operational acumen. A rare combination. These are complex businesses to build, and the right playbooks are yet to be perfected. But where this works, 𝗦𝗲𝗿𝘃𝗶𝗰𝗲𝘀-𝗮𝘀-𝗦𝗼𝗳𝘁𝘄𝗮𝗿𝗲 𝗔𝗜 𝗯𝘂𝘀𝗶𝗻𝗲𝘀𝘀𝗲𝘀 𝘄𝗶𝗹𝗹 𝗿𝗲𝗱𝗲𝗳𝗶𝗻𝗲 𝗺𝗮𝗻𝘆 𝗕𝟮𝗕 𝗰𝗮𝘁𝗲𝗴𝗼𝗿𝗶𝗲𝘀 📈 #EnterpriseAI #startups #vc #SaaS

Stop selling AI capabilities. Start selling AI outcomes. The most profitable companies in generative AI aren't selling better models — they're selling better results. After years of helping clients transform experimental AI outputs into revenue-driving workflows, I see something powerful in what Tarun Jain is doing with WaxWing. He's exploiting a real leverage point in this market. Most founders are fighting for position in overcrowded AI tool marketplaces or building agencies. Meanwhile, the structural opportunity sits precisely between these approaches. The pattern is clear: package expert workflows so customers can experience them through low-cost AI demos ($49) before upgrading to premium, human-assured outcomes ($1,000+). This isn't just a pricing strategy—it's an entirely different business architecture. When you codify your expertise into workflows that AI can demonstrate at scale, you're essentially creating a self-qualifying sales funnel. The entry-level AI preview attracts volume while filtering for serious buyers. Your human experts then focus exclusively on the high-value last mile—the part where accountability and judgment still command premium prices. The economics are transformative: You acquire customers at SaaS-level CAC but monetize them at services-level ARPU. I've seen companies struggle for months trying to sell "better AI." Then watch the same tech get rapid traction when repackaged as "better outcomes powered by AI." Same technology, fundamentally different value proposition. This is why productized AI workflows win: → Tools force customers to figure out use cases → Talent forces you to scale linearly with headcount → Workflows let you scale acquisition with technology while monetizing with expertise The winning formula isn't better AI—it's better packaging of AI into workflows that deliver predictable outcomes at unpredictable scale. Sustainable AI profit is fundamentally about finding the perfect balance between machine-driven scale and human-assured quality. #founders #startup #growth #ai

I've had over 500 AI agency sales calls and here's what businesses actually want. (Spoiler: It's not simple chatbots or voice agents although they do sell) While everyone's building weekend ChatGPT wrappers, businesses are quietly paying $15,000+ for completely different AI solutions. After generating six figures in AI service revenue, I've discovered exactly what companies are willing to pay premium prices for. The reality check: A $2M ARR SaaS company told me they'd rather pay $20,000 for a solution that increases revenue by $50,000 monthly than pay $2,000 for a chatbot that saves 5 hours per week. (who would've thought.. 😂) That conversation changed everything about how I approach AI services. What businesses actually pay premium prices for: Sales Automation Systems - Intelligent prospect identification across multiple data sources - Automated research and enrichment for each lead - Multi-channel outreach orchestration (email, LinkedIn, phone) - Dynamic nurturing sequences that adapt to prospect behavior - Lead scoring that prioritizes highest-value opportunities Content Creation Engines - Automated market research and competitor analysis - Multi-format content generation across all platforms - Advanced SEO optimization and ranking strategies - Brand voice consistency across all channels - Performance tracking and optimization Operational Workflow Solutions - Complete client onboarding automation - Document processing and compliance monitoring - Intelligent customer support with escalation protocols - Quality control and audit trail systems - Project management and resource optimization Data Processing & Analytics - Multi-system data integration and business intelligence - Predictive modeling for forecasting and optimization - Real-time performance optimization - Competitive intelligence gathering - Custom executive dashboards The industries reaching out most: - Professional services (agencies, consulting, law, accounting) - E-commerce and retail ($500K-$10M annual revenue) - Manufacturing and distribution - Healthcare and compliance-heavy businesses Why these command premium pricing: They solve expensive problems that directly impact revenue, provide strategic advantages competitors can't replicate, and generate measurable ROI that far exceeds investment. Stop building tools and start solving business problems. When you can demonstrate $200K in additional revenue or $150K in cost savings, charging $25K becomes an easy decision. 👉 Want the complete breakdown of high-value AI solutions? 1. Connect with me 2. Comment "SOLUTIONS" I'll send you the detailed analysis. (Must be connected - prioritizing reposts first!)