OpenAI and Anthropic Just Entered the Consulting Business

On May 4, 2026, something happened that most business owners missed entirely.

OpenAI and Anthropic the two most closely watched AI companies in the world both launched enterprise consulting ventures on the same day. Not the same week. The same day.

OpenAI announced the OpenAI Deployment Company (DeployCo): a $10 billion entity, $4 billion in committed capital, backed by 19 firms including TPG, Goldman Sachs, SoftBank, McKinsey & Company itself, and Capgemini. Anthropic announced a parallel venture backed by Blackstone, Goldman Sachs, Hellman & Friedman, General Atlantic, Apollo Global Management, GIC, and Sequoia Capital with approximately $1.5 billion in committed capital.

Combined: $11.5 billion entering the consulting industry in a single morning.

The $375 billion management consulting industry built over decades by McKinsey, BCG, Bain, Accenture, and Deloitte had its most consequential competitive moment since the Big Eight accounting firms invented modern consulting. And most people in that industry were still writing their Tuesday morning emails.

This piece covers why the AI labs made this move, what it means for the consulting industry, and most importantly for independent consultants and boutique firms where the opportunity sits in the gap between what the labs can serve and what the market actually needs.

Why Now The Problem the Labs Were Trying to Solve

The move did not come from ambition alone. It came from a specific, measurable problem that every enterprise AI buyer had been describing to the labs for 18 months.

AI pilots can be launched quickly. Turning them into secure production systems usually requires months of integration and process work. The labs were watching enormous enterprise deals get signed, watching the pilots succeed, and then watching the production deployment stall because the client's IT team was overwhelmed, the systems integrator was slow, and the consulting firm was still writing the requirements document.

Enterprise already accounts for more than 40% of OpenAI's revenue, with the company reporting $25 billion in annualized revenue as of February, and enterprise on pace to reach parity with consumer revenue by end of 2026. The labs had the clients. They did not have the implementation capability to turn pilot success into production reality at the speed the market required.

For every dollar companies spend on software, they spend roughly six on services a ratio that has made consulting a multitrillion-dollar industry for decades. The labs had been capturing the software dollar. The six-dollar services opportunity was going to Accenture, Deloitte, and McKinsey firms that were reselling the labs' own models at consulting rates, with the labs seeing none of that revenue.

McKinsey says about 40% of its projects are now AI-related. BCG's AI revenue accelerated to roughly $3.6 billion about 25% of total revenue in 2025. The firms consulting on AI were growing their AI revenue faster than any other category. OpenAI and Anthropic looked at those numbers and made a simple decision: stop subsidising the consultants' growth and capture it directly.

The Palantir Playbook What Forward-Deployed Engineers Actually Do

WWII operations room editorial cartoon contrasting traditional consultant pointing at enterprise map from distance versus forward-deployed engineer sitting at the table fixing it in real time

Both ventures are built on the same model: forward-deployed engineers embedded directly inside client organisations.

The concept comes from Palantir, which pioneered the model over the past decade. Instead of shipping software and leaving implementation to someone else, Palantir's engineers lived inside client organisations understanding the legacy systems, the compliance constraints, the political dynamics, the undocumented processes that no requirements document ever captures. They built working systems in real environments rather than demos in controlled conditions.

DeployCo will use embedded engineers specialised in AI deployment into organisations to design, test, and deploy production-ready AI systems that deliver the greatest value. The engineers go on-site. They understand the specific complexity of a specific client's environment. They build inside it rather than around it.

Anthropic said its applied AI engineers will work with the new company's engineering team to identify use cases, build custom systems, and support customers over time.

The model has three structural advantages that traditional consulting firms cannot match:

Lower cost of model access. When DeployCo builds a Claude-powered system, it accesses the model at cost. When Accenture builds the same system, it pays API rates then charges the client a margin on top. The economics are structurally different before a single billable hour is logged.

Faster integration cycles. To staff the new entity from day one, OpenAI has acquired Tomoro a UK-based applied AI consulting firm with deployments at Tesco, Virgin Atlantic, and Supercell, where its engineers built an in-game support agent serving 110 million users in 12 weeks. Twelve weeks. Traditional enterprise deployments of comparable scope run 18–24 months.

Built-in distribution. OpenAI's investment partners collectively sponsor more than 2,000 businesses globally, giving the Deployment Company a built-in distribution channel that bypasses the traditional CIO sales cycle entirely. Anthropic's venture has drawn backing from General Atlantic, Apollo, Leonard Green, and GIC each with their own portfolio of client companies already paying consulting bills.

Victorian apothecary editorial cartoon showing AI lab pharmacist measuring the $1 software dollar versus the $6 services drum the ratio that drove OpenAI and Anthropic into consulting

What the Labs Are NOT Attacking And Why That Matters

This is the part most coverage gets wrong by omission.

OpenAI and Anthropic are not attacking the entire $375 billion consulting market. They are attacking the AI-services slice that is currently growing fastest inside it.

The specific target is large enterprise clients Fortune 500 and equivalent with complex AI deployment challenges, legacy system integration requirements, and the budget to pay for embedded engineering teams. The venture is designed to embed Anthropic's engineers and models directly into the core operations of mid-size businesses.

What they are not building:

They are not serving the long tail of small and medium businesses that cannot afford embedded engineering teams regardless of how the pricing is structured. The $1.5 billion and $10 billion vehicles are not being deployed at a $200/month SaaS equivalent price point.

They are not doing strategy. Forward-deployed engineers build systems. They do not sit in boardrooms advising on whether to enter a new market, how to restructure an organisation, or which acquisition makes strategic sense. The strategy layer stays with the traditional consultants.

They are not doing change management. Getting a new AI system adopted across 10,000 employees requires organisational psychology, communication strategy, and training programmes that no forward-deployed engineering team is staffed to deliver.

They are not local. OpenAI could meet obstacles in consulting because the business is vendor-specific. A client in Pune or Lagos or Warsaw needs implementation support that operates in their timezone, their regulatory environment, their language, and their business context. DeployCo and Anthropic's venture are, for now, primarily US-focused with gradual international expansion.

They are not domain specialists. A forward-deployed engineer can build an AI system for a healthcare compliance workflow. They cannot advise on the clinical implications of the outputs, the regulatory nuance of a specific jurisdiction, or the professional liability questions that a healthcare consultant with 20 years of domain experience handles as a matter of course.

What This Destroys And What It Doesn't

Accenture's fiscal 2025 results showed $69.67 billion in revenue, 7% growth, $2.7 billion in generative AI revenue tripled year over year and $5.9 billion in genAI bookings. Accenture is growing its AI consulting faster than any other segment. OpenAI and Anthropic are coming directly for that growth.

The consulting roles most at risk from the labs' moves:

Generalist AI strategy consultants who advise large enterprises on AI adoption without building anything. When DeployCo can show up and build a production system in 12 weeks, the 18-month strategy engagement that precedes nothing becomes very hard to defend.

Systems integrators reselling AI tools without proprietary methodology or implementation depth. The margin between what Accenture charges and what the labs' own ventures will charge will compress fast.

Mid-market transformation consultants selling AI transformation programmes to companies in the $50M–$500M revenue range exactly the target market for both ventures' portfolio company distribution channels.

The consulting roles least at risk:

Domain specialists with vertical expertise that model-agnostic engineering teams cannot replicate. A healthcare AI consultant who understands HIPAA, clinical workflows, and provider liability is not being replaced by a DeployCo forward-deployed engineer who knows how to build RAG systems.

Boutique implementation specialists serving clients too small for DeployCo's minimum engagement size, too specific for a generalist engineering team, or in markets where local presence and local relationships are the product.

Independent consultants with established client relationships and demonstrated delivery track records at a price point and responsiveness level that a $10 billion venture cannot match for smaller engagements.

The Real Opportunity For Everyone the Labs Cannot Serve

OpenAI's investment partners collectively sponsor more than 2,000 businesses globally. That is the distribution channel that makes the venture viable. It is also, viewed differently, a ceiling.

There are approximately 350 million small and medium businesses worldwide. There are tens of millions of mid-market companies between the SMB floor and the Fortune 500 ceiling. DeployCo and Anthropic's venture are not serving them not at launch, not at their current price point, and not without the local presence that enterprise relationships require.

The opportunity for independent AI consultants and boutique firms in 2026 is precisely in that gap and it is large enough to build a serious practice on.

Goldman Sachs' Marc Nachmann said the venture would help "democratise access to forward-deployed engineers" for companies that currently cannot afford the talent or the consulting fees to build AI systems on their own. That democratisation does not happen at the top of the market. It happens at the mid-market and SMB level where independent specialists operate.

Sequoia partner Julien Bek argued that the world's next great company will not sell software but outcomes: legal services, financial analysis, insurance processing delivered by AI and billed like consulting. The Anthropic joint venture is essentially that thesis, capitalized and staffed.

For independent consultants, the same thesis applies at a smaller scale. The question is not whether to compete with DeployCo. The question is which specific outcome for which specific client type can you deliver more reliably, more quickly, and more cheaply than a forward-deployed engineer from a $10 billion venture who has never worked in your client's industry.

The Four Positions That Win in the Post-DeployCo Market

Position 1: The Vertical Specialist

Pick one industry. Finance, legal, healthcare, real estate, e-commerce. Go deep enough in that industry's workflows, regulations, and terminology that a generalist engineering team cannot replicate what you do without six months of domain learning. The labs are horizontal. The opportunity is vertical.

Position 2: The Mid-Market Implementation Partner

DeployCo's minimum viable client is a large enterprise with a complex, multi-system deployment challenge. Your minimum viable client is a 50-person business that needs three workflows automated and a content pipeline running. Different client, different price point, different relationship model. Not competing serving the gap.

Position 3: The Outcome-Based Practitioner

Sequoia partner Julien Bek argued that the world's next great company won't sell software at all, but outcomes. Charge for the outcome the reduction in processing time, the increase in leads qualified, the hours saved per month not the hours spent building. The labs' ventures are staffed by engineers who charge engineering rates. You can charge for business outcomes that an engineering rate structure cannot easily capture.

Position 4: The Local Expert

International expansion takes time. Local regulatory knowledge, local business culture, local language, local relationships these are competitive advantages that a US-headquartered $10 billion venture builds slowly. In India, Southeast Asia, the Middle East, Africa, and most of Europe, the local AI consultant who speaks the client's language, understands their regulatory environment, and shows up in their timezone is not competing with DeployCo. They are serving a market DeployCo has not yet reached.

Victorian apothecary editorial cartoon showing AI lab pharmacist measuring the $1 software dollar versus the $6 services drum the ratio that drove OpenAI and Anthropic into consulting

What the Timeline Looks Like

This is where most analyses stop at the announcement. The implementation timeline is where the opportunity calculus becomes real.

DeployCo launched with more than $4 billion in initial investment that OpenAI said it will use to scale operations and acquire firms. Scaling from launch to serving 2,000 portfolio companies takes time not weeks, but quarters. Hiring, onboarding, building client relationships, developing engagement methodologies, navigating enterprise procurement cycles all of it takes longer than the press release implies.

OpenAI said 150 engineers from Tomoro will join DeployCo. They will work on-site at enterprises to design, test, and deploy production-ready AI systems. 150 engineers serving 2,000 portfolio companies is a ratio of approximately one engineer per 13 companies. That ratio clarifies the scope of what DeployCo can actually deliver in year one and the size of the gap it leaves.

The window for independent consultants and boutique firms to establish themselves to build the client relationships, the domain reputation, and the delivery track record that compounds into referrals is not five years. It is the next 12–18 months, before the labs' ventures have finished onboarding their initial pipeline and before the second wave of competition arrives.

The businesses that move in that window will be significantly better positioned than the ones that wait to see how the market settles.

What This Means If You Are an AI Automation Consultant

The announcement of DeployCo and Anthropic's venture is the best and worst news for independent AI consultants in the same moment.

The worst news: the largest, best-funded, most technically capable organisations in AI are now directly competing for the enterprise implementation work that has been the high end of the independent consultant's market.

The best news: the announcement validates the market at a scale that removes any remaining doubt about whether AI consulting is a real business. When OpenAI raises $4 billion to enter your market, your market is real.

The practical implication is not to pivot. It is to position more specifically the vertical, the client size, the geography, the outcome and to build the proof of delivery that enterprise relationships require.

A boutique AI automation practice serving mid-market businesses in a specific industry, in a specific geography, with demonstrated delivery track records and outcome-based pricing, is not competing with DeployCo. It is serving the client DeployCo has not yet reached, at the price point DeployCo cannot match, with the local context DeployCo does not have.

That is not a consolation prize. It is a viable, growing, defensible market position in an industry that just received $11.5 billion in external validation.

FAQ

What is OpenAI's Deployment Company (DeployCo)? DeployCo is a majority-owned OpenAI subsidiary launched on May 4, 2026, with a $10 billion valuation and $4 billion in committed capital from 19 investors including TPG, Goldman Sachs, SoftBank, McKinsey, and Capgemini. It embeds specialised AI engineers directly inside enterprise clients to design, build, and deploy production-ready AI systems modelled on Palantir's forward-deployed engineer approach. OpenAI acquired UK-based consulting firm Tomoro to staff it from launch.

What is Anthropic's consulting venture? Anthropic's enterprise AI services company was announced on May 4, 2026, backed by approximately $1.5 billion in committed capital from Blackstone, Goldman Sachs, Hellman & Friedman, General Atlantic, Apollo Global Management, GIC, and Sequoia Capital. It embeds Anthropic engineers directly inside mid-size businesses to build AI systems around Claude, targeting portfolio companies of the PE backers as its initial client pipeline.

Why did OpenAI and Anthropic both launch on the same day? Both announcements were made on May 4, 2026, reflecting the competitive pressure each lab faces from the other and from traditional consulting firms capturing AI revenue. The timing was not coincidental each lab was aware the other was moving and chose not to cede the announcement cycle.

Does this mean AI consultants will be replaced by the labs? Not entirely. The labs' ventures target large enterprise clients with complex deployments, served through private equity distribution networks. Independent consultants serving SMBs, mid-market businesses, specific verticals, or non-US markets are not in the same competitive space. The labs are attacking the top of the market. The mid-market and SMB implementation opportunity remains open.

What is a forward-deployed engineer and how does this model work? A forward-deployed engineer (FDE) is an AI specialist who embeds inside a client organisation rather than working remotely. FDEs live inside the client's systems, understand their specific legacy infrastructure and compliance constraints, and build production-ready AI deployments in weeks rather than months. The model was pioneered by Palantir and is now being adopted by both OpenAI and Anthropic.

How large is the consulting market the labs are entering? The global management consulting market was approximately $375 billion in 2026, according to Mordor Intelligence. The AI-services slice growing fastest inside it is where the labs are focused. Accenture alone generated $5.9 billion in generative AI bookings in fiscal 2025. BCG's AI revenue reached $3.6 billion 25% of total revenue in 2025.

What opportunity does this create for independent AI consultants? The labs' ventures serve large enterprises through PE portfolio company pipelines. Approximately 350 million SMBs and tens of millions of mid-market companies worldwide are not served by this model at launch or at the current price point. The window to establish client relationships, domain expertise, and delivery track records in the underserved mid-market is the 12–18 months before the labs' ventures finish onboarding their initial pipeline.

What should an AI consultant do differently now that the labs have entered consulting? Position more specifically by vertical, client size, geography, and outcome. Generalist AI advice without implementation capability is the most at-risk consulting position. Domain specialists, mid-market implementation partners, outcome-based practitioners, and local experts in non-US markets are in positions the labs cannot easily replicate in the near term.