How AI Is Poised to Disrupt Consulting — but Change Won’t Happen Overnight

AI is on track to revolutionize people-heavy sectors like consulting, law, and accounting. Venture investor Navin Chaddha, managing director of Mayfield, shared his vision for how forthcoming "AI teammates" will transform $5 trillion worth of services by automating routine work and introducing software-like profit margins. Yet, he acknowledges this shift won’t be immediate—displacing trusted giants like McKinsey or Accenture takes more than innovative tech.

Decades of Disruption: The Next Wave Is AI

Chaddha’s long view is shaped by decades of technology shifts, from mainframes to mobile. Previous revolutions—e-business, global outsourcing—forced even brick-and-mortar businesses to evolve, often tapping emerging markets for new efficiencies. Today, large language models (LLMs) and AI are the next exponential leap. They aren’t replacing professionals overnight, but they are teaming up with humans to reimagine how services are delivered and monetized.

AI is best poised to take on repetitive, structured tasks first. For example, companies implementing complex platforms like Salesforce could delegate the bulk of the process to AI-powered solutions, with human experts stepping in only when necessary. This model both reduces labor costs and shifts pricing structures toward paying “per event” or outcome, rather than for hours of human labor.

Start With the "Neglected Masses," Not the Giants

Rather than challenging industry behemoths head to head, Chaddha advocates for targeting untapped smaller markets. There are 30 million small companies in the U.S. alone, many of which can’t justify—or afford—traditional consulting. Here, AI can offer services like reception, scheduling, or legal paperwork generation as software, filling gaps where expensive knowledge workers previously dominated. For early-stage founders, outcome-based pricing can create high-margin businesses, with the potential for 60–70% blended margins, dwarfing many tech startup economics.

Gruve: A Real-World Example of AI-First Service

Mayfield recently invested in Gruve, an AI-driven security consulting firm. Gruve acquired a small managed security company and grew revenue from $5M to $15M in six months by automating key services. Their outcome-based approach (clients pay only if a security event is handled) achieved eye-popping gross margins—proof that high-value knowledge work can be reimagined around AI and service automation. Even industry leaders like Cisco are taking notice.

Why Large Firms Face the Innovator’s Dilemma

Why can’t the incumbents simply “buy” these capabilities? Chaddha draws a parallel to the early days of SaaS: enterprise software giants were slow to abandon lucrative traditional contracts for monthly subscriptions. Similarly, consulting giants are incentivized to stick with hourly or annual models. Serving small companies at scale with AI-powered, outcome-based models disrupts their business—and smaller, more nimble players can move faster. But over time, the line between today’s startups and tomorrow’s disruptors will blur, and even the largest consulting firms will need to adapt or risk being left behind.

Deep Founder Analysis

Why it matters

This evolution signals a major shift in value creation for startup founders, not just in consulting but across all people-intensive industries. As AI lowers the cost and barrier to entry, startups have an unprecedented opportunity to carve out new markets and capture share from slow-moving incumbents. Service business models can finally benefit from the scalability and profit margins typical of SaaS.

Risks & opportunities

The main risk is market resistance—trust, relationships, and “the way it’s always been done” still matter in B2B services. Startups must balance automation with human touch and prove both reliability and results. However, the opportunity is massive: enabling millions of small businesses worldwide to access expertise once reserved for Fortune 500s. The firm that cracks scalable, outcome-driven AI service delivery (with strong UX and clear value for non-experts) will lead the next wave.

Startup idea or application

Consider a startup offering AI-powered compliance consulting for SMEs—a "Compliance Copilot" platform that automates regulatory paperwork, provides audit-readiness checklists, and (where necessary) connects users to human experts for negotiation or resolution. Charging per regulatory event or audit delivered, not per hour, this model brings fortune-500-level oversight to companies that previously could not afford top-tier advisors.

AI Teammates: Beyond Tools, Toward Collaboration

Mayfield’s “AI teammate” thesis distinguishes between tools and true digital collaborators. AI teammates are digital companions—like an HR assistant or a sales engineer—that partner with humans toward shared business outcomes, rather than just automating busywork. The goal is synergy, not replacement.

The Human Factor: Navigating Disruption With Empathy

Large-scale automation raises tough questions about job displacement. Chaddha suggests facing this reality directly: new technology always brings disruption, but also creates new markets and often expands the overall pie. Historical examples—PCs and secretaries, Excel and accountants, Uber and taxi drivers—show short-term pain but long-term market growth and transformation. The secret lies in adaptation and expanding services, not simply cutting costs.

Managing Uncertainty—and Catching the Next Wave

Valuations in the AI era can seem irrational, but Chaddha points out that success in venture depends on having a clear strategy, resisting FOMO, and focusing on value creation (not just chasing logos). Those with experience navigating tech cycles, discipline, and an appetite for risk will be best positioned to seize opportunities — and mitigate the inevitable downsides when markets overheat.

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