New research from digital asset investment firm Sarson Funds reveals which industries are making the most significant investments in private artificial intelligence and which blockchain companies are building the infrastructure for decentralized AI deployment. The study, conducted in early 2026, comes as the global private AI market is projected to grow from $11.1 billion in 2025 to $113.7 billion by 2034, with 58% of deployments expected to remain on-premises.
The research identifies healthcare, financial services, and manufacturing as the industries under the most pressure to adopt private AI solutions. These sectors face stringent regulatory requirements, data privacy concerns, and proprietary information protection needs that make public cloud AI models unsuitable for many applications. The findings suggest that industries handling sensitive data are leading the transition toward private AI implementations that keep data within organizational control while still leveraging advanced AI capabilities.
According to the report, decentralized compute networks are emerging as a critical solution for enterprises seeking to balance security requirements with operational flexibility. Companies like Aethir, 0G, Venice AI, and Manifest Network are building infrastructure that enables enterprises to run private AI with on-premises security while providing cloud-like flexibility and significantly lower infrastructure costs. These blockchain-based platforms allow organizations to access distributed computing resources without compromising data sovereignty.
The potential cost savings represent a significant driver for adoption, with decentralized networks reportedly reducing infrastructure expenses by 60-80% compared to traditional cloud providers. This economic advantage could accelerate private AI adoption across industries, particularly for mid-sized enterprises that previously found AI implementation cost-prohibitive. The research indicates that blockchain technology is solving key challenges in AI deployment by creating verifiable, transparent computing markets that ensure data privacy while optimizing resource utilization.
For business leaders, the implications extend beyond technology selection to strategic competitive positioning. Industries that successfully implement private AI solutions may gain significant advantages in data security, regulatory compliance, and proprietary algorithm development. The research suggests that early adopters in regulated industries could establish substantial barriers to entry through their AI implementations while maintaining control over sensitive data assets.
The growth projections for the private AI market indicate a fundamental shift in how enterprises approach artificial intelligence deployment. As organizations increasingly recognize the limitations of public AI models for sensitive applications, the demand for private, secure alternatives is creating new opportunities for infrastructure providers. The convergence of blockchain and AI technologies appears poised to address longstanding challenges in data privacy, computational efficiency, and cost management that have previously hindered widespread enterprise AI adoption.
Sarson Funds, which focuses on early-stage crypto projects and decentralized AI, notes that its research highlights the intersection of two transformative technologies. The firm's analysis suggests that blockchain-based decentralized computing represents more than just an infrastructure alternative—it potentially redefines how enterprises approach AI strategy, data governance, and technological innovation in increasingly regulated and competitive environments.
