TL;DR
- AI-first startups are targeting law, consulting, and accounting — a combined $5 trillion market — with outcome-based automation models.
- Veteran VC Navin Chaddha of Mayfield sees software-like gross margins (up to 90%) disrupting people-heavy firms like McKinsey and Accenture over the next decade.
- Early-stage companies like Gruve are already demonstrating revenue growth and client wins with AI-managed services.
- Incumbents face the innovator’s dilemma, resisting model shifts from hourly billing to event-based pricing.
- AI teammates, not just tools, will redefine how digital services scale in fragmented global markets.
The $5 Trillion Opportunity in Labor-Heavy Services
Navin Chaddha, Managing Director at Silicon Valley-based Mayfield, believes that the next decade will witness AI-first startups redefining consulting, law, and accounting — industries historically reliant on billable hours and deep client relationships. Speaking at TechCrunch’s StrictlyVC event in Menlo Park, Chaddha argued that large language models (LLMs) are enabling companies to deliver professional services with software-like margins, significantly reducing the need for human labor.
Chaddha pointed out that just as outsourcing and offshoring transformed software and manufacturing in past decades, AI will be the next great disruptor of white-collar industries. However, he advised founders not to compete directly with Accenture or Tata Consultancy Services (TCS), but instead to serve the underserved — millions of small businesses that can’t afford traditional consulting rates.
Outcome-Based Billing and AI-Driven Growth
In Chaddha’s view, outcome-based pricing — where clients pay only when AI delivers value — is the new model. He used the example of AI-driven Salesforce implementations: instead of charging per hour, companies should charge per completed outcome, using AI as the primary executor and humans only when needed.
This approach creates blended margins as high as 70%, with up to 90% of work handled by AI. Chaddha noted that traditional tech firms have long operated at losses funded by venture capital, whereas service firms generate real profits — a dynamic AI can amplify.
Gruve: A Case Study in AI-Led Services
Mayfield recently led a Series A round in Gruve, a security consulting firm founded by serial entrepreneurs who previously bootstrapped two $500 million companies. Gruve began by acquiring a $5 million revenue business in managed security, then layered on AI to scale it to $15 million in revenue within six months, boasting 80% gross margins.
Notably, Gruve charges nothing until a security breach occurs, moving away from traditional $10,000-per-month retainers. Clients like Cisco are embracing this risk-aligned model, which blends AI observability with trust-based payments.
The Data
| Metric | Value |
| Target Industry Size | $5 trillion (law, consulting, accounting) |
| AI-Led Gross Margins | Up to 90% |
| Gruve Revenue Growth (6 Months) | $5M → $15M |
| Gruve Pricing Model | Outcome-based (pay only on breach or event) |
| Number of U.S. Small Businesses | 30 million (underserved by traditional consulting) |
| Potential Global SMB Market | 100 million companies |
The Innovator’s Dilemma Hits Consulting Giants
Chaddha warned that incumbents like McKinsey, BCG, Infosys, and Accenture face a classic innovator’s dilemma. While they serve large enterprise clients with predictable, time-based billing, they risk losing market share by delaying a pivot to AI-powered utility models.
Just as perpetual-license software companies struggled to adopt SaaS in the 2000s, Chaddha believes major consulting firms will resist shifting from fixed monthly contracts to dynamic billing, where customers only pay when AI delivers measurable value.
AI Teammates vs. Tools: What’s the Difference?
Chaddha has carved out $100 million from Mayfield’s latest fund for investments in AI teammates, defined as digital collaborators working alongside humans toward shared goals. Unlike mere tools or copilots, AI teammates are sector-specific assistants — such as “HR teammates” or “sales engineering teammates” — that function as embedded knowledge agents in workflows.
This reframing not only improves adoption but also positions AI as an augmentative force, not a replacement, echoing historical transitions like Microsoft Word replacing typewriters or Excel enhancing accounting roles.
Addressing Job Displacement Honestly
Chaddha acknowledged the growing tension between AI optimism and worker anxiety. “Yes, there’s going to be job displacement,” he said, “but humans are the jockey — AI is the horse.” He cited past disruptions such as the arrival of PCs, rideshare platforms, and mobile networks in emerging markets, noting that markets tend to expand, not contract, following technological leaps.
He drew a comparison to how countries like India and Africa leapfrogged landlines to adopt cellular networks, predicting that underserved regions will similarly skip labor-intensive service models by deploying AI from day one.
Navigating Today’s AI Valuation Hype
Asked about a recent acquisition — an Israeli startup with $200K in monthly revenue bought for $80 million by Wix — Chaddha quipped: “I thought it would be $800 million. In today’s world, no math makes sense.” He emphasized that AI investing today is more art than science, where experience, discipline, and a strong internal compass matter more than herd behavior.
For Mayfield, investing is still about managing money, not collecting brand logos. “FOMO is for sheep,” he cautioned.
