Everybody Wants to Rule the World

At Oktane a couple of weeks ago, Okta and a group of enterprise heavyweights, including AWS, CrowdStrike, Databricks, Google Cloud, Salesforce, ServiceNow, Wiz and Zscaler, launched the Blueprint Alliance . Their goal is a shared plan for securing and governing AI agents across the enterprise. The biggest names in tech are forming bigger alliances, signing bigger deals and making bigger promises. Everybody wants to rule the world. Bigger doesn’t always mean better for the people writing the checks. More than half of CEOs told PwC this year that AI had delivered neither higher revenue nor lower costs over the prior 12 months. Only one in eight saw both. You will work with alliances like this one. The real question is whether you’ll still hold the keys when you do. What the Blueprint gets right Credit where it’s due. The Blueprint Alliance is a multi-vendor coalition that co-authored an open reference architecture for governing AI agents at enterprise scale. It’s built around four practical questions: Where are my agents? What can they do? What are they doing? How do I respond? Those are the right questions, and the timing is right. Okta cites a Gartner prediction that the average global Fortune 500 company will run more than 150,000 agents by 2028, up from fewer than 15 in 2025. No single product will govern that. Ganesh Kirti, founder and CTO of TrustLogix, wrote in a LinkedIn post that the blueprint “treats agent security as an enterprise architecture problem, not a single-product problem.” He also landed on a principle every CIO should tape to the wall: “agents need identities, but identity alone does not make an action trustworthy.” At their best, industry alliances do good. They create shared language, speed up interoperability and give buyers a baseline to hold vendors to. Coalitions gave us SAML, OAuth and FIDO. Those made my job easier for two decades. Notice what’s missing, though. None of the four questions asks what an agent is worth. That one stays with you. So, I’m a fan. I have also been in the Buyer’s seat. Buyers read the fine print. The one-way door Jeff Bezos famously split decisions into two types. Two-way doors you can walk back through. One-way doors you can’t. Alliances often look like the first and behave like the second. Here’s why. When the companies that already run your cloud, identity, endpoints and data agree on how AI should be governed, the easiest path is to govern AI with the tools you already own. That’s convenient. It’s also how a governance decision quietly becomes a procurement decision. Incumbents don’t need to win a new category. They need the status quo to hold. Their established product lines fund the roadmap, and new AI capabilities get folded into renewals you were going to sign anyway. An alliance makes that path feel safe, because everyone you already trust is standing on it. That’s how successful businesses behave. Your job is to notice when their interests and yours start to drift. Watch for these signs that the door is closing behind you: AI governance arrives as a “free” add-on to a renewal, with pricing that changes in year two. The architecture assumes one vendor’s control plane for identity, policy and logging. Your agent activity data lives in a format only one platform can read. Exit costs, data portability and migration support are missing from the contract. ROI slides count seats and adoption instead of business outcomes. I’ve walked through this door before I spent 2007 to 2015 at VMware as an Oracle consultant, and then as the head of IAM. We deployed Oracle’s identity and middleware stack to get the company through its IPO. It was the right call, and it did exactly what was needed at the time. Then the costs and complexity grew. New environments took weeks to build. Every change needed engineering and admin time. That eventually led to an informal effort that we called Get Off Oracle, or GOO. The surprise was where GOO led. To regain control, we virtualized the entire Oracle stack, including Fusion Middleware and Oracle RAC, using VMware software and automation we built ourselves. Build and delivery times dropped from weeks to hours. That speed helped fuel VMware’s explosive growth and accelerated time to market. Even Okta came by to study how we did it. The lesson stuck with me. Our leverage came from owning the architecture. Once we controlled how the stack was built, deployed and moved, we negotiated from strength. The vendor stayed. The dependence didn’t. Price is not risk Every time an AI system acts on data you can’t fully trace, bound or prove, you take on Verification Debt. It compounds quietly and comes due at the worst moment: a release, an audit, a regulator’s letter. That’s why the sticker price misleads. A $100,000 AI project with a clear economic mechanism can carry less risk than a $20,000 project nobody can explain. The price tells you what you’ll spend. It tells you nothing about what the system can reach, what it can decide or what it would cost to unwind. Two companies show the difference. Klarna rolled out an AI assistant for customer service and cut its cost per transaction from $0.32 to $0.19 over two years. But cost became the main scorecard. Its CEO later admitted that the focus on cost produced lower quality , and Klarna started hiring human agents again. He now describes human support as something close to a VIP service . The savings were real. The scorecard was lopsided. Morgan Stanley took a slower path. The firm built an evaluation framework to test every AI use case before deployment . Today more than 98% of its advisor teams use its AI assistant. Both companies worked with the same AI partner. Different discipline produced different results. PwC found the same pattern at scale: CEOs with strong AI foundations were three times more likely to report meaningful financial returns. A strategy for sovereignty Here’s the economics most renewal decks leave out. Year one is the honeymoon. Pricing is generous, services are bundled and the executive sponsor is thrilled. By year two or three, costs rise, complexity grows and switching gets harder. Value stays flat while leverage moves to the vendor. Sovereignty is how you keep that leverage. It means you can join any alliance and still walk away from any vendor. Five moves get you there: Own your data layer. Keep governance metadata, lineage and agent activity logs in formats you control. Build your own AI harness. Put models, agents and identity providers behind a layer you control. Price year three before you sign year one. Cap increases, define exit rights and require data portability in writing. Measure value in business terms. Tie every AI commitment to revenue, cost, risk or customer outcomes, with a named owner. Keep the program in house. Vendors advise. Your leaders decide. The harness is where sovereignty gets real. An AI harness is the layer you own between your people, your data and whatever models or agents you run. It carries the context, policies, evaluations and logs, so any model can plug in, and any model can be swapped out. Pair it with an intelligence layer: a governed view of what your enterprise knows, drawn from every system instead of trapped inside one. Together, they change the economics. Data silos stop dictating what AI can see. Per-seat SaaS pricing loses its grip, because the value lives in a layer you own. And every vendor becomes a position in a portfolio you can rebalance. That’s leverage at the negotiating table and at renewal time. It’s the GOO lesson all over again. Own how the stack is built, and every vendor has to keep earning its place. The Blueprint Alliance will produce real success stories. It will produce regrets too. Just don’t let them be yours. The organizations that come out ahead will have active leadership, clear governance and the discipline to keep every vendor honest and accountable, including their favorites. Everybody wants to rule the world. Build your own harness, and