Right now it's Vertical AI Saas because we still need all the current platforms, data and recurring fees to pay the bills
Every industry needs Ai once they’re ready
Greetings from Tel Aviv!🇮🇱 I'm here for a few days, meeting with incredible investors and some of the most innovative startups and founders. As I’ve shared before,Israel is a powerhouse of technology and entrepreneurship, and I’m committed to investing my time, energy, and capital to help fuel its growth. Excited for what’s ahead! 🚀
The Problem with General AI in Enterprise
It’s a race to the bottom for OpenAi, Anthropic, Big Tech etc.
Artificial intelligence is reshaping industries, but not in the way most people expected. The early hype aroundgeneral AI for enterprises—broad automation tools meant to replace entire workflows—has collided with the reality of corporate bureaucracy, siloed data, and slow adoption cycles.
Enterprise AI adoption ispainfully slow. Large organizations operate with rigidbudget cycles, compliance constraints, and internal resistance to change. Even if AI could improve efficiency, most companies don’t have thedata infrastructure or internal expertiseto implement it effectively.
This is whyVertical AI is where the real money is.
I might coin this Vertical Saas 3.0 in the future 😀
Many AI startups have tried to sellhorizontal AI solutions—tools that automate broad functions across industries. But these approaches face significant challenges:
🚧Siloed Data– Most companies don’t have centralized, structured datasets AI can easily learn from.
🚧Long Sales Cycles– AI tools that require deep integration struggle to get buy-in without an internal champion.
🚧Budget Rigidity– Corporate budgets are planned18+ months in advance, limiting flexibility to adopt new AI solutions.
🚧Lack of AI Expertise– Even when companies buy AI tools, they often lack the talent to implement and optimize them.
Because of these barriers,enterprise AI adoption is taking far longer than anticipated.Companies aren’t just resisting AI for fear of job loss—they simplydon’t have the structure or incentivesto adopt it at scale.
Why Vertical AI is the Real Opportunity
Instead of buildingbroad AI solutions, startups that focus onVertical AI—AI designed for specific industries like healthcare, finance, and defense—are seeing faster adoption and stronger ROI.
✔Industry-Specific Workflows:Vertical AI is built forreal problemsthat companies already spend money on.
✔Better Data Access:Companies in specialized sectors are more likely to havestructured, usable dataAI can learn from.
✔Faster ROI:Executives can justify investing in AI when itdirectly impacts revenue, compliance, or cost savings.
Trace Cohen@Trace_Cohen
Vertical AI is where the real money is.
Enterprise AI adoption is slow—silos, messy data, no budget flexibility. But Vertical AI startups solve specific industry problems (healthcare, finance, defense) with better data & faster ROI.
The next AI unicorns won’t be general.…x.com/i/web/status/1…
16 RepliesWhere Vertical AI is Winning
Healthcare AI– Startups using AI forradiology, drug discovery, and administrative automationare growing rapidly because they solve high-friction, high-cost problems. Example: Tempus, which applies AI to personalized cancer treatment.
Financial AI– AI is thriving in areas likefraud detection, underwriting, and trading algorithmsbecause these use cases have clear ROI. Example: Upstart, which uses AI for credit underwriting.
Defense & Security AI– AI forautonomous systems, cybersecurity, and intelligenceis seeing huge investment, particularly from governments and private defense contractors. Example: Anduril, which builds AI-driven defense systems.
Manufacturing & Industrial AI– AI is transforming industrial automation, predictive maintenance, and supply chain optimization, reducing downtime and improving efficiency.
Example:Falkonry– Uses AI-driven anomaly detection to predict equipment failures before they happen.
Legal & Compliance AI– AI is revolutionizing contract analysis, regulatory compliance, and document automation, saving law firms and corporations significant time and resources.
Example:Evisort– Uses AI to extract key insights from contracts and streamline legal workflows.
Retail & E-commerce AI– AI-driven personalization, demand forecasting, and inventory optimization are helping retailers increase conversion rates and reduce waste.
Example:Stylitics– Uses AI to recommend personalized outfits and boost online fashion sales.
Agriculture & Food AI– AI is optimizing crop monitoring, precision farming, and food safety, helping farmers increase yield and sustainability.
Example:Verdant Robotics– Uses AI-powered robotics for precision spraying and automated weeding.
Energy & Climate AI– AI is improving energy grid management, carbon tracking, and renewable energy efficiency, making sustainability efforts more scalable.
Example:Aurora Solar– Uses AI to design and optimize solar panel installations.
Real Estate & PropTech AI– AI is streamlining property valuation, tenant screening, and predictive analytics for real estate investment.
Example:Cherre– Uses AI to unify and analyze real estate data for better decision-making.
VCs Are Moving Their AI Bets to Vertical AI
Venture capital investors have realized thatthe next wave of AI unicorns won’t be generic enterprise tools—they’ll be deeply specialized.
Enterprise AI funding is slowing downas companies struggle with adoption.
Vertical AI startups are raising more capitalbecause they showreal traction, not just potential.
Investors arebacking industry-specific AI companiesthat align with existing budgets and infrastructure.
TL;DR: The Problem with General AI in Enterprise
General AI for enterprises is struggling because ofslow adoption, rigid corporate structures, and siloed data. Despite the hype, broad AI automation tools face long sales cycles and budget constraints, making it difficult for companies to integrate them effectively.
🚀Vertical AI is the real opportunity.Instead of generic AI, startups focused onindustry-specific AI (healthcare, finance, defense, etc.)are seeingfaster adoption and higher ROIbecause they solvereal, high-friction problems.
💰Winning Sectors for Vertical AI:
Healthcare AI(radiology, drug discovery) – e.g.,Tempus
Financial AI(fraud detection, underwriting) – e.g.,Upstart
Defense & Security AI(autonomous systems, cybersecurity) – e.g.,Anduril
📉Enterprise AI funding is slowing down, whileVertical AI is attracting more VC moneybecause these startups align withexisting budgets and infrastructure, showing real traction rather than just potential.
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