Presented by Contemporary Analysis & Omaha Data Science Academy​

This is week 1 of 5 where we breakdown the conversations we're having with clients that we wish all data and AI leaders understood in October 2026. First up:

Vendor lock

Vendor lock isn't new, but we are starting to see it happen in AI more and more.

Vendor lock is when a company selects a software, tool, or AI vendor and builds systems accordingly. Then 2 or 3 years down the line realizes the chosen tool isn't sufficient for their needs (or isn't getting used by employees), but the company is locked into a multi-year contract or spent the whole budget on the first tool and doesn't have money to rebuild the whole system with a new tool.

Or in the case of AI, token costs surge and models stop performing.

It can be tempting to say 'yes' when your enterprise AI provider offers:
​"We can build your AI system for you for free, or cheap."

Before you say yes, there are two things I want you to consider:

1. There are hundreds (maybe thousands) of AI providers, it's not just the big 5 or 6 we hear about in Forbes.

Where one fails at a task, another one succeed. Most enterprise AI implementation includes multiple models from multiple providers, including open-source and open-weight models, along with proprietary or frontier models.

Going with only one provider limits you from the speed, accuracy, and precision that multiple models from multiple companies in the same application gives you. Do not rob yourself of the flexibility by locking into just Copilot, Claude, or ChatGPT.

2. Build the vehicle, plug in different engines.

If your tools and systems are the vehicle, the AI model is your engine.

Build the metaphorical truck. Then connect the engine, the AI model. And when that AI model is no longer the best option, switch out the engine for another. If built correctly, you get to choose the engine you want based on the need you have.

Need horsepower? Put in a diesel engine (a frontier model that has high token cost, but has the best answer providing potential.)

Need gas mileage? Put in an electric motor (an open model that runs off-line and uses very few token to give you very specific answers.

When you build the vehicle without locking it to one engine, you have options without changing your application.

And remember, you want to reserve the flexibility to change models in the most cost effective way, because you'll have to switch or add models as today's models are retired for their more advanced versions. More on that next week as we dive into:

"AI models change constantly. AI models aren't like Windows software. Models change in real time and can be deprecated (killed) with little to no warning."

Around the Data and AI World

Speaking of Vendor Lock Last month Okta, an identify and access security firm, announced the Blueprint Alliance, "a coalition of industry leaders established to build a practical framework for securing and governing agents at enterprise scale." The Blueprint Alliance includes founders members such as AWS, Google Cloud, Salesforce, ServiceNow, CrowdStrike, Databricks, Docker, Zscaler, Proofpoint, Lovable, and Wiz. According to blueprintalliance.ai, the alliance was created to bridge the gap between AI adoption and security controls: The Alliance is built to answer these four questions: Where are my agents? What can they do? What are they doing? How do I respond? No doubt, four important questions for every organization to answer. ​But as Steve Tout at cio.com points out, this model is ripe for multi-vendor lock: 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 are Tout's 5 signs 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.

Fun and Games

For week 2 of our series on the conversations we're having with clients that we wish all data and AI leaders understood in October 2026, we're covering the risk of ever-changing AI models.

Have questions you'd like us to answer? Hit reply and ask away!

Off to make a big data bowl of chili,

NATE WATSON CEO, Contemporary Analysis

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