- +1 (615) 717-7616
- kip@dodsonmc.com
- 9050 Carothers Parkway, Franklin, TN 37067
On July 1, 2026, Palantir CEO Alex Karp went on CNBC’s Squawk Box to talk about a new Nvidia partnership. What he delivered instead was one of the most direct warnings I’ve seen a major tech executive make in public: enterprises that pay AI vendors by the token are quietly surrendering their own competitive edge to those vendors. “The jig is up,” he said.
Richard Spitz, Managing Director of Strong Force Innovation Portfolios, used that clip as a proof point in our conversation — not a talking point. His view: if the CEO of one of the most sophisticated data companies in the world is saying this on live television, it’s already happening at every enterprise that hasn’t asked who actually controls its AI architecture.
Richard took the argument further than Karp did.
“Model access and token consumption alone will not produce durable returns. Economic value is created by embedding AI into enterprise data, workflows, decisions, products, and operations. That makes control the central issue. Enterprises must control what data AI can access, how proprietary context is applied, which models and tools are used, what agents are authorized to do, how decisions are executed, and who retains the intelligence generated from the results. Without that control, AI can improve efficiency while quietly weakening the enterprise’s own differentiation.”
This is the part that most AI conversations skip. Everyone is focused on which model is best, which platform to build on, which vendor to trust. Those are real questions — but they’re the wrong first question. The first question is: when AI processes your customer data, your operational history, your proprietary workflows — who owns the intelligence that comes out the other side?
For most enterprises right now, the honest answer is: not us.
Richard’s position is that owning the architecture — the patents on how AI is orchestrated inside the enterprise — is the only structural answer to that problem. It creates a property right that doesn’t depend on secrecy, doesn’t erode as AI improves, and doesn’t require staying ahead of your competitors. It requires ownership.
I spent a lot of time in my career at the infrastructure layer of large industrial systems. The companies that owned the architecture — the control systems, the communication protocols, the integration standards — had leverage that pure software companies never did. Rockwell Automation was one of them. What Richard is describing is that same dynamic, playing out at the AI layer, right now, faster than most people realize.
SO, HERE’S WHAT I’M TELLING YOU
It’s not who has the best model — it’s who controls how AI touches the business.
The businesses asking this question today are a step ahead. The ones that aren’t are building on infrastructure they don’t own — and may not even know it.
Facebook
Twitter
LinkedIn
Discover expert insights on digital marketing! Click below to explore our blog for valuable strategies, trends, and perspectives to grow your business
Explore Our Marketing Insights
The founder and managing partner of DodsonMC who brings: 32 years of experience enhancing operations for Fortune 500 companies. A Vanderbilt Executive MBA and an Industrial Engineering undergraduate degree. Over 20 years of success in owning and growing his own businesses. A vast network of partners that have driven accelerated results.
Kip DodsonFounder
https://dodsonmc.com/wp-content/uploads/2025/01/digital-agency-global-video_2.mp4
Foundation Tool: Our journey begins with the Sourceu2019 Digital Diagnostic Tool, essential for evaluating your current position before investing in new technology, capital improvements, or marketing strategies.
Why It Matters: Why It Matters: In todayu2019s rapidly evolving digital landscape, the Source Formula helps determine your readiness to adapt and succeed.
Proven ROI: By following the Source Formula roadmap, you can clearly see and measure your return on investment as you progress.