OpenAI, Anthropic, and Google committed over $6 billion to rebuild the enterprise AI channel, in partnership with the world’s leading private equity firms. Why is the money flowing to consultants instead of to software companies? Because Enterprise AI is a workforce transformation, and the channel built over 50 years to sell and deploy software licenses cannot deliver one.
AI is a coworker, and seven of the eight factors that decide whether an AI agent actually delivers value sit on the Human Resources (HR) department, working with your business leaders, yet in most companies HR is the missing chair at every AI strategy table. And that is an expensive mistake.
🎧 Go Deeper: In this week’s companion episode we walk the seven-of-eight framework live, and share success stories. Listen on Apple Podcasts | Spotify
In our last issue, we showed the value of AI hiding at the task level. In the issue before that, we argued that AI is working at the individual level, but enterprise strategies are not. Today, we focus on who must be in the room when those strategies are written.
💸 What the Frontier Labs Just Told Every CEO
In the past month, the companies that build the AI we all use committed more than $6 billion to a new channel. The existing one was built to sell licenses and deploy software. The new one is being built for something else entirely: workforce transformation.
| Announcement | Amount | Backers | What it signals |
|---|---|---|---|
| OpenAI Deployment Company (DeployCo) | $4B at a $10B pre-money valuation | Bain & Company, plus 19 global partners; OpenAI retains majority control | Frontier lab building its own enterprise deployment channel |
| Anthropic enterprise services joint venture | $1.5B+ | Blackstone, Hellman & Friedman, Goldman Sachs (lead); plus General Atlantic, Leonard Green, Apollo Global Management, GIC, Sequoia Capital | AI-native services firm to bring Claude into core business operations |
| Google Cloud partner ecosystem fund | $750M | Global consulting firms, system integrators, software partners, channel partners | Funding agentic AI development across the partner ecosystem; new ways to deploy partner agents in Gemini Enterprise |
| McKinsey Google Transformation Group | Co-invested practice | McKinsey + Google Cloud | First dedicated end-to-end frontier-lab transformation practice inside a top-tier consulting firm |
🧩 Seven of Eight
In our AI4SP advisory work, we have helped guide over 8,000 AI agents for nine enterprise clients over the past 18 months. The same eight elements determine whether an agent actually works inside a company.
| 7/8 |
Factors that decide whether an AI agent delivers value in your company
Seven sit with Human Resources and the Business Divisions. One sits on IT. Most companies hand all eight to IT.
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HR & SMES
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Context and culture
Subject Matter Experts (SMEs) at Business Divisions provide the context, knowledge, and daily guidance an agent needs, HR provides the culture and values context, defining the way work gets done.
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HR & SMEs
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Job descriptions
HR, working with Business Divisions, has to redraw each of them.
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HR & SMEs
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Placement in the org chart
Agents need a manager, a team, and a reporting line. Three people and twelve agents break every assumption in the current model.
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HR & SMEs
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Performance measurement
Every review template was designed for humans managing humans; evaluation frameworks are defined by HR, goals by SMEs.
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HR
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Continuous training
Identity work, not button training.
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HR
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Escalation paths
When the agent breaks, who decides what happens next?
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HR
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Guardrails
The behavior charter for AI coworkers.
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IT
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The tool itself
The platform, the integration, procurement, security, and data governance.
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Seven out of eight elements are HR work, in partnership with the functional experts or frontline team members getting the work done. We keep handing the whole project to IT Departments, who own one of these 8 critical elements.
According to Deloitte’s 2026 Global Human Capital Trends, only 14% of leaders are adept at designing how humans and AI actually work together. 86% of leaders are not ready for the work the next two years are about to demand of them. And there is no chair on the strategy committee labeled ready for this.
🏢 What HR-Led Transformation Actually Looks Like
🪑 The View From Two Chairs
Aurelie Saada, AI-Change Leader at Microsoft, told us:
“The hardest barriers to AI adoption aren’t technical. They’re perceived. People think they can’t. They think they shouldn’t. They think they aren’t ready. We gave them the confidence that they could actually do it. That’s Human Resources and Cultural Transformation work, not IT work.“
She also flagged the unsolved performance question.
“HR needs to rethink how performance is evaluated, particularly for humans managing agents.”
Catherine Moy, Chief People Officer at BDO US, named the classic first mistake leaders make: leading with technology as the tip of the spear. Her counter:
“This is very organic. It’s digital-native friendly. It’s meant to percolate up. We need some loving architecture.“
Loving architecture. The whole HR craft in two words. And Catherine left every Chief Human Resources Officer with the question that has to be answered next:
“How do we build the critical thinking skills for the AI era in people who haven’t had the experience of building it from the bottom? That is a key intervention for Human Resources in every single company.“
🧭 Start With Diagnosis
If you are a Chief Human Resources Officer reading this, the first move is a diagnosis. What is your workforce already doing with AI? Where is the value hiding? Who are your internal experts who can help you train others and lead by example? What interventions does your culture actually need?
Across the AI4SP diagnoses we have run in the past 18 months, the same five patterns surface in nearly every company:
| What the diagnosis surfaces | Typical finding | What it tells HR |
|---|---|---|
| Shadow AI adoption | 88% of employees already use AI tools that the company has not authorized | The transformation is already happening. The question is whether you fund it or fight it |
| The Two Percent | 2% to 5% of the workforce is already operating at an expert level, creating agents, automations, and apps | These are your champions. Most companies have never identified them |
| The trust chasm | A 50-point gap between executive optimism and employee confidence in the company’s AI direction | Identity work, not button training, is the unlock |
| Task-level wins, dashboard blindness | 4 to 8 hours saved per week per proficient user, none of it visible on the IT dashboard | The measurement system is counting the wrong things |
| Management capability gap | Fewer than 1 in 5 managers feel ready to lead a hybrid team of people and agents | The org chart needs to be redrawn before more tools are bought |
🛠️ The Playbook This Week
| Action | If you are a CEO | If you are the HR Leader |
|---|---|---|
| The invite list | Move your Chief Human Resources Officer to the top of the AI strategy meeting invite list. Not the third name. The first. | Do not wait for the invitation. Send yourself the invite. |
| The questions | Put these four on the agenda: why are we using AI, what work changes, who does it differently, and how do we measure whether our people are better off. | Walk in with those four questions answered for your function. |
| The diagnosis | Fund a workforce AI diagnosis before the next platform purchase. | Run the diagnosis on your own teams first to model the practice. |
Doing anything else is an expensive pilot.
“We are spending $37 billion a year on the technology and pennies on the change management. We are hiring the most powerful coworker in history and skipping orientation. Every successful AI transformation we have guided comes back to the same thing: somebody in the room owned the human side of the work.”
“When HR is in the chair from day one, the technology actually shows up in the results. When the chair is empty, the technology shows up in a footnote.“
🔗 Resources
- Companion episodes: Distributed AI: The Minutes No One Is Counting | AI Is Working. Your Strategy Is Not. | The Two Percent
Luis J. Salazar | Founder | & Elizabeth | Virtual COO | AI4SP
Sources: AI4SP Research (8,000+ AI agents guided across nine enterprise clients; eight-element agent deployment framework; 80% IT-led failure rate corroborated with IBM, McKinsey, Deloitte; stats drawn from 70-country research base; accounting firm and construction firm case studies are real AI4SP client engagements, individuals identified by first name only with permission). Frontier lab channel reinvention: OpenAI announcement on DeployCo · Bain press release · Axios on DeployCo · Anthropic announcement · Blackstone press release · WSJ on Anthropic JV · FT on Anthropic JV · Google Cloud partner fund blog · Google Cloud press release · CRN on Google partner fund · McKinsey Google Transformation Group announcement · PR Newswire. External research: Fortune / WalkMe (80% bypass, 52-point trust chasm) · intuitionlabs.ai (95% pilot failure) · Menlo VC State of Generative AI in the Enterprise ($37B enterprise spend) · MIT Sloan Review (76% see agentic AI as coworker) · BCG (50-55% jobs reshape) · Fortune / Anthropic (jobs as bundles of tasks) · Deloitte 2026 Global Human Capital Trends (14% of leaders adept at human-AI interaction design) · HBR / KPMG / UT Austin (5% sophisticated users; Ambitious, Curious, Iterative, Reflective behaviors) · HBR (six psychological debts of AI adoption) · Deloitte AI-Enabled Workforce Shift · Brookings (limits of worker retraining).
