GPT-5 is getting all the buzz. But the new open models of AI matter more

Why should businesses care?

Democratizing Access to AI Agents

ChatGPT maker OpenAI made headlines this month with two major launches: the release of two so-called open weight models and the debut of the long-anticipated next generation Chat-GPT 5. While most of the media and industry buzz focused on the latter, it’s the open models, and the rapidly advancing ecosystem around them, that could make a bigger difference for everyone from researchers to small businesses.

The idea of open versus closed (or proprietary) models is familiar to anyone who has worked in software, and the definition is the same when it comes to AI. According to our partners at the Open

A Morning Consult report from 2013 identified cost and privacy as the primary barriers to AI adoption for small businesses. The arrival of open models has the potential to address both concerns: they can be deployed offline, enabling greater data privacy, and they are free to use.  

Proprietary AI models often deliver stronger performance, but they require costly infrastructure and must run on an external provider’s servers, which requires a business to hand over its data. Open

AI is becoming a lot more practical for Main Street businesses. What’s new isn’t just that open models can be a fixed-cost asset instead of a metered service. It’s that these self-hosted, affordable models are getting good—really good! Small businesses can now keep customer data in-house, avoid surprise price hikes, and spin up niche copilots like a “local operations assistant” or a “custom cake-order concierge” on their own terms, without needing to be AI experts or train models themselves.  

Open models also come with built-in transparency. Business owners can get a direct view of how the AI works, and the ability to store data in-house offers a surer way to meet compliance obligations. This is particularly important in an era where centralized data storage systems have been the targets of data breaches.

Having full control over the AI stack also means businesses can adapt and integrate models into the parts of their operations that matter most, such as loyalty programs, supply chain workflows, or customer support scripts, without worrying about vendor lock-in or shifting API terms. That kind of control turns AI into a strategic asset and helps businesses create more tailored, differentiated experiences.

Aside from this ongoing improvement, there is another cause for enthusiasm: open AI models aren’t just static prediction engines, they’re becoming active helpers. When paired with tools that allow them to take actions, these models turn into “AI agents” that can execute tasks automatically. Consider open

Goose also runs on your own computer (not on Block’s servers) and can connect a language model to real-world business actions, from drafting emails to updating spreadsheets. In practical terms, this means a small business could have an AI that not only suggests answers, but actually logs into their inventory system, finds the relevant data, and helps complete a task, entirely on-site. 

Imagine automating your invoicing, email replies or appointment scheduling with an AI that operates like a diligent virtual assistant, and doing it without sending any data to the cloud or paying per-action fees. Open

None of this is hype or sci-fi, it’s the emerging reality of open