📊 Full opportunity report: The Forward-Deploy Pivot: Why Anthropic and OpenAI Are Becoming Consulting Firms in the Same Week on ThorstenMeyerAI.com — validation score, market gap, and execution plan.
TL;DR
Anthropic and OpenAI are creating new enterprise-focused units backed by major investors, aiming to embed AI engineers into mid-sized companies. This shift challenges the traditional consulting industry and signals a move toward AI-as-a-service for outcomes.
Anthropic and OpenAI have each announced the formation of new enterprise services entities designed to embed AI engineers directly into mid-sized companies, marking a significant shift in their strategic approach and challenging the traditional consulting industry.
On May 4, 2026, Anthropic disclosed plans to form a $1.5 billion AI-native enterprise services company, backed by major investors including Blackstone, Hellman & Friedman, and Goldman Sachs. This entity will deploy Anthropic’s Applied AI engineers alongside client teams to redesign workflows for sectors such as healthcare, manufacturing, and financial services, following a Palantir-inspired forward-deploy model.
Two days later, on May 6, 2026, OpenAI announced a similar initiative called ‘DeployCo,’ backed by TPG, Bain Capital, and others, with a $4 billion commitment and a valuation of approximately $10 billion—roughly 6.7 times larger than Anthropic’s vehicle at launch. These parallel developments suggest a coordinated effort to position AI as a core enterprise service, akin to a consulting model but driven by AI engineering.
Both companies are aligning these moves with upcoming funding rounds and potential IPO plans, with Anthropic reportedly nearing a $50 billion valuation and considering a public listing as early as October 2026. The strategic intent appears to be capturing a larger share of the $6 in services spent for every dollar on software, particularly in the mid-market segment underserved by traditional consulting firms.
Same week.
Two consulting firms.
Anthropic and OpenAI synchronized $5.5B in commitments to rebuild the consulting industry from scratch — backed by ~$10 trillion in aggregate AUM.
May 4 · $1.5B Anthropic vehicle with Blackstone + Hellman & Friedman + Goldman Sachs as founding partners. OpenAI’s “DeployCo” announced hours earlier — $4B at $10B valuation, 6.7× larger. Both use Palantir’s forward-deployed engineering model. Captive customer pipeline through PE portfolio ownership = unprecedented enterprise software moat.
Two ventures. One opportunity.
The most concentrated assembly of private capital ever announced for AI services. Captive customer pipeline through PE portfolio ownership is the structural moat — when the PE firm owns both the services firm AND the customer, traditional buyer-seller dynamics break down.
- Anthropic$300M · founder
- Blackstone$300M · $1.3T AUM
- Hellman & Friedman$300M · $115B AUM
- Goldman Sachs AM$150M · $625B alts
- General Atlantic~$150M · $80B+
- Apollo + Leonard Green+ GIC + Sequoia
overlap
- OpenAI$500M · founder
- TPG$250B+ AUM
- Brookfield$1T+ AUM
- Bain Capital$185B+ AUM
- Advent International$90B+ AUM
- 15 unnamed investors$4B total commits
AI engineering consulting tools
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Four days. Four layers.
Each layer compounds the others. Compute enables deployment scale. Models provide capability. Templates productize workflows. Services firm provides delivery. PE pipeline provides customers. The blitz is coordinated IPO positioning ahead of Q4 2026.
enterprise AI deployment software
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Five tiers. Five trajectories.
The disruption is uneven by tier. Indian IT faces structural threat (cost-arbitrage labor model obsolescence). Big Four maintain Fortune 500 dominance. Strategy consultancies durable on judgment work. Palantir’s FDE model gets validation premium.
AI workflow redesign tools
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Three scenarios. One restructuring.
Whether the captive customer model scales as projected or faces execution constraints. Both vehicles likely achieve material scale rather than one collapsing — the structural setup is overwhelming.
- 1,500-2,500 deploymentsBy end-2027 across portfolio.
- 3-6 month deliveryVs 12-18 months traditional.
- Big 4 mid-market compressesIndian IT down 30-40%.
- JV revenue $1-2B by 2028Material IPO contribution.
- Outcome: October 2026 IPO at $900B+. JV is bull case.
- 800-1,500 deploymentsBy end-2027.
- Bifurcated marketFDE entities + traditional SI both grow.
- Big 4 deepen alt-AI partnershipsAccenture+OpenAI; Deloitte+Google.
- JV revenue $400-800M by 2028Supporting narrative.
- Outcome: IPO proceeds. JV is one of several threads.
- Engineering scaling hardFDE talent the binding constraint.
- PE governance frictionMultiple sponsors create overhead.
- Big 4 defends aggressivelyPricing competition compresses.
- JV revenue $100-300M by 2028Underperforms projections.
- Outcome: IPO valuation hit. Potential 2027 delay.
This is the most aggressive enterprise distribution play in tech history, executed in synchronized fashion within hours of each other, backed by approximately $10 trillion in aggregate AUM. The captive customer move is the new structural moat for AI commercialization. Everything else is supporting infrastructure.
Project Management with AI For Dummies
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Four assignments. By role.
Track 90-180 day customer traction.
Anthropic IPO valuation case strengthens materially. The captive distribution channel adds structural multi-year revenue visibility worth plausibly $500M-$2B incremental ARR by Q4 2027. Q4 2026 IPO probability rises from ~50% pre-announcement to ~65-70% post-announcement. Verify execution before drawing valuation conclusions.
Form competing vehicles or cede captive economics.
KKR, Carlyle, Vista, Thoma Bravo, Silver Lake, Warburg Pincus face strategic choice. Form parallel vehicles with smaller AI labs (Mistral, Cohere, xAI) or with Microsoft/Google/Meta as model partners. Or accept structural disadvantage. The captive customer model is the new value-creation default.
Equity-aligned partnerships and vertical specialization.
Big 4 — deepen alt-AI partnerships (Accenture-OpenAI, Deloitte-Google likely). Indian IT — pivot to AI-native delivery aggressively or face 25-40% market cap compression. Mid-market integrators (EPAM, Genpact) face direct competition; vertical specialization in regulated industries (defense, government, large healthcare) is the defensible position.
PE-owned companies face accelerated AI deployment.
If your company is owned by Blackstone, H&F, Apollo, GA, Leonard Green, GIC, Sequoia — direct JV engagement arriving 12-24 months. If OpenAI DeployCo’s PE backers — same. Reskill toward judgment-intensive roles. The Atlassian template applies — workforce composition reshape, not just headcount cut. 15-25% restructuring across PE-portfolio companies over 2026-2030.
Implications for the Consulting Industry and AI Market
This shift signifies a fundamental change in how AI companies are approaching enterprise engagement, moving from software providers to direct, outcome-focused service providers. By embedding engineers into client organizations, Anthropic and OpenAI are challenging the traditional consulting model, which relies heavily on human consultants and systems integrators. This could lead to a redistribution of revenue from established firms like McKinsey, BCG, and the Big Four consulting giants toward AI-native firms, especially in the mid-market segment.
The developments also indicate a broader trend of AI companies positioning themselves as essential partners for digital transformation, potentially disrupting the entire $1.4 trillion global IT services market. The strategic focus on embedded engineering and vertical productization could accelerate the adoption of AI solutions across industries, impacting employment, consulting practices, and the competitive landscape.
Background on AI-Driven Consulting and Market Trends
Over the past year, AI companies like Anthropic and OpenAI have increasingly emphasized enterprise adoption, securing large contracts and expanding their technical infrastructure. Anthropic’s ARR (annual recurring revenue) is projected to grow from $9 billion in late 2025 to over $30 billion by early 2026, reflecting rapid enterprise demand.
Historically, the consulting industry has operated on a model where firms like McKinsey and Accenture provide strategic and systems integration services, generating significant revenue from client engagements. The rise of AI-native enterprise units introduces a new paradigm—offering outcomes directly through embedded engineering teams, reducing reliance on traditional consulting firms. This aligns with comments from industry observers like Julien Bek, who predicted that future companies will focus on delivering outcomes rather than just software.
Prior to these announcements, Anthropic maintained relationships with major consulting networks, but the new joint ventures are equity-backed and designed to directly compete for mid-market deployments, signaling a strategic pivot.
“The world’s next great company won’t sell software at all, but outcomes—legal services, financial analysis, insurance processing delivered by AI.”
— Julien Bek, Sequoia Partner
Unconfirmed Details and Potential Challenges
While the formation of these entities and their funding structures are confirmed, the long-term impact on the consulting industry remains uncertain. It is not yet clear how clients will respond to embedded AI engineering models or how traditional consulting firms will adapt over time. The actual revenue share, client adoption rates, and potential regulatory or ethical considerations are still developing areas.
Additionally, the competitive dynamics between Anthropic, OpenAI, and established consulting giants are still unfolding, and the success of these models depends on execution and market acceptance.
Upcoming Developments and Strategic Moves
Both Anthropic and OpenAI are expected to continue expanding their enterprise offerings, potentially scaling their embedded engineering models and forming additional partnerships. The companies may also pursue IPOs or further funding rounds to support growth, with Anthropic reportedly nearing a $50 billion valuation.
Industry observers anticipate that traditional consulting firms will respond by developing their own AI-driven services or forming alliances. The next 12-24 months will reveal how effectively these AI-native enterprise units can capture mid-market demand and reshape the consulting landscape.
Key Questions
What is the main goal of Anthropic and OpenAI with these new entities?
The primary goal is to embed AI engineers into client organizations to deliver outcomes directly, challenging traditional consulting models and capturing a larger share of enterprise AI spending.
How do these moves affect the existing consulting industry?
They threaten to displace parts of the traditional consulting market, especially in the mid-market segment, by offering more integrated, outcome-focused AI services that reduce reliance on human consultants.
Will these AI-driven consulting models replace all traditional consulting?
It is unlikely they will replace all traditional consulting, but they could significantly reshape parts of the industry, especially in sectors where AI can deliver measurable outcomes efficiently.
What are the risks involved for Anthropic and OpenAI?
Risks include client resistance, regulatory challenges, technological execution hurdles, and competition from established consulting firms adapting to AI models.
When might we see these models fully adopted in the industry?
Full adoption could take several years, with early signs of success emerging within the next 12-24 months as these entities expand their client base and refine their offerings.
Source: ThorstenMeyerAI.com
