The $1 Trillion Consulting Market Is Now Fair Game for Tech

01 /The Concept

Gruve was founded in 2024 because its founders spotted a gap in the market: AI was being adopted everywhere, yet companies weren't seeing meaningful results from the investment.

So Gruve set out to help companies deploy AI in ways that actually move the needle on business performance.

The goal isn't AI adoption for its own sake – it's measurable impact on operational efficiency and growth metrics.

To deliver that, Gruve walks clients through five implementation phases:

- Strategy definition. Working with key client stakeholders to identify which business processes stand to benefit most from AI.

- Data preparation. Helping the company get all relevant data into the right shape and delivery mode so AI can ingest and process it automatically.

- Infrastructure architecture. Designing and connecting AI tools to data sources and processes in a way that's reliable and scalable.

- AI adaptation. Customizing and fine-tuning models to maximize performance in each specific deployment context.

- Security and governance. Verifying that deployed AI is protected against compromise, and that it operates within the company's internal policies and industry regulations.

The results clients report: 45% faster AI implementation than doing it independently, 80% higher employee adoption of deployed tools versus other implementation approaches, and cost savings of up to 70% compared to brute-force deployment.

Clients already span automotive, healthcare, manufacturing, financial services, research, and IT.

Despite having roots in India, Gruve has global ambitions. Offices are already open in the US, Dubai, Singapore, and South Korea, with Canada, the UK, and Germany on the expansion roadmap.

The company just raised $20M in new funding and simultaneously disclosed the $17.5M round it raised the previous year.

02 /Why It Matters

Gruve operates at the intersection of IT consulting and management consulting.

The interesting part is that venture investors historically avoided consulting startups because consulting was a fundamentally unscalable business:

- Revenue was directly tied to headcount – to grow, you had to hire proportionally. - Revenue was earned at the moment of service delivery, with no compounding effect that could drive exponential growth.

Gruve's business model changes both of those constraints:

- AI agents do a significant portion of the consulting work alongside humans. This has pushed Gruve's margins to 70–80%, well above the levels typical of traditional IT consulting. - Gruve doesn't charge by the hour. It charges for the use of the AI tools it deploys – revenue that continues flowing long after the implementation engagement ends.

And crucially, that usage-based pricing is tied to business outcomes rather than raw resource consumption. Which should be win-win: clients pay when things work, and Gruve earns a fraction of a very large number when its clients are large companies.

Naturally, Gruve isn't alone in figuring this out.

Quantum Rise ([related review](/review/na-jetom-uzhe-ne-stydno-zarabatyvat)) raised $15M in its very first round last summer and explicitly calls itself a consulting company – but one operating under a new paradigm: "Consulting 2.0" Its two founding principles: deliver profit growth for clients, not presentations; and make the deliverable a product that executes the recommendations, not a report that describes them.

Workhelix ([related review](/review/jeto-ne-gemorroj-a-vozmozhnost-eshhjo-bolshe-zarabotat)) – also founded just last year – has already closed two rounds totaling $30.3M. Its approach is "implementation as a service," powered by a proprietary knowledge base mapping employee job functions to available AI tools. It effectively runs that database against a client's organization to quickly identify where specific tools should be deployed for maximum impact.

This spring's Y Combinator graduate Operand ([related review](/review/tupoj-ii-skoro-budet-ne-nuzhen)) is carving off its own piece of the traditional management consulting market. Currently focused on pricing strategy for retail and e-commerce clients, it's explicit that pricing is just the starting point.

Management consulting as a market already clears $1 trillion annually. If the industry continues shifting from a report-generation business to a product-development-and-deployment business – with outcomes-based pricing – that market's size could start growing in step-changes rather than percentage points.

03 /Opportunities

The emergence of AI has created an unexpected transformation: traditional consulting is turning into a product business. The deliverable is no longer a strategy deck – it's an AI product that implements the strategy, embedded in the client's workflow. Consulting firms need to become software product companies. For anyone with an engineering background, this is a natural fit.

In the near term, the priority is AI implementation itself. Boston Consulting Group projected last year that AI-related services would account for 20% of consulting revenue across the industry.

The incumbents are already positioning. PwC became OpenAI's largest enterprise customer and its first official reseller – deploying OpenAI-based solutions for its own clients.

But disruption always reshuffles the field. New entrants who build for the new rules from day one – as Gruve, Quantum Rise, Workhelix, and Operand are doing – have a structural advantage over legacy firms trying to retrofit.

And a trillion-dollar market can accommodate many new entrants. The play doesn't require becoming a universal platform. Niche firms – focused on specific verticals or specific types of business processes – can build substantial businesses without competing head-to-head with the giants. The essential criterion: the niche needs to have real purchasing power.

So: in what domain could you become the new kind of consulting firm – the one that sells clients working AI products instead of slide decks, and earns a share of the efficiency gains rather than billing for hours?