B2B spending on AI models and platforms will reach roughly $60 billion in 2026. At historical service attach rates, where every dollar of enterprise ERP, SaaS or cloud license generated $3–5 of services, that implies a $200–300 billion AI services market today.
Yet the actual AI services market is roughly $35 billion. The attach ratio hasn't reached even 1:1.
By 2030, if spending on AI models and platforms merely quadruples from here (it grew 63% this year alone), historical attach rates imply an AI services market on the order of $1 trillion, rivaling today's entire global IT services industry.
Figure 1. 2030 assumes AI models-and-platforms spend quadruples from 2026. Sources: Gartner; industry attach-ratio studies.
Many winners across massive diversified eco-system
Not dissimilar from prior technology shifts (SaaS & Cloud) which were dependent on services firms to enable adoption, B2B AI adoption will be no different, except much larger, across more vectors, producing more winners, large and small. As you can see below (based on what we know today), there are many categories of services where critical value will be provided, and this will only evolve with time as the technology matures, and flushes itself out.
Figure 2. The AI services market by category. Teal = project revenue; dark green = recurring.
Acquisition spree has begun and will only continue
The supply-demand imbalance is already stark: forward-deployed engineering talent is the scarcest resource in enterprise AI. The proof is the past eighteen months of acquisitions, by global integrators, by private equity, and most tellingly, by the frontier model providers themselves. When the most valuable technology companies on earth start buying services firms, they are telling you where the bottleneck is.
Figure 3. M&A and channel formation on one timeline. Frontier labs, lab-backed platforms and global integrators are buying AI services firms; the same labs are simultaneously funding the partner channel that produces them.
Frontier Labs acquiring service firms and heavy investment in the channel demonstrates the mission critical nature of AI services and the bottleneck
The frontier labs aren't just buying services firms, they're building a formal channel of them. In the span of four months, OpenAI, Anthropic, and Google each launched partner programs with published directories, tiered certification, and committed capital: over $1 billion between them.
Figure 4. Published directories, tiered certification and committed capital. The frontier labs are institutionalizing the AI services ecosystem.
The earliest innings
Enterprise AI adoption is still in its earliest innings: most organizations have experimented, yet few have scaled AI into production. The bottleneck is AI services: the firms whose forward-deployed engineers and related AI subject-matter experts wire AI capabilities into real workflows, automation and ultimate value. Those firms will carry businesses across the chasm into broad adoption, just as services firms have in every major platform shift.
Figure 5. The adoption curve that matters is scaled deployment, not experimentation. Gartner calls 2026 the inflection year for enterprise AI spending; the services attach ratio, still below 1:1 against a 3–5x historical norm, says the same thing. Sources: McKinsey State of AI 2026; Stanford HAI 2026 AI Index; PwC 2026 CEO Survey; Gartner.
Harbor Ridge Capital is seeking to back leading AI services firms that have reached meaningful scale and want capital and hands-on support to press their advantage and capture the market opportunity ahead that drives a lucrative exit. If you're building one of these firms, and would like a preliminary conversation, please reach out: cmaghami@harborridgecap.com.
Cyrus Maghami is the Founder & Managing Director of Harbor Ridge Capital, a SaaS- and tech-services-focused M&A advisory and investment firm that has completed 69 transactions representing $2.3B in value.
