Today, VentureBeatreported that the agentic AI hype met the agentic AI reality. It wasn’t just some bad news; it was a war alarm.

Google cut off OpenClaw users from Antigravity. This was not just a ‘sorry – no longer available’. Some were even losing access to their Google accounts.

The alarm was also heard by companies that struggle to control their internal AI infrastructure. At the same time, today,McKinsey ran a webinar telling executives it’s time for experimentation. Helloooo???

In my humble opinion, the initial freedom to experiment with ChatGPT in 2023 was the way to go. But by mid-2024, we already warned enterprise leaders about “Shadow AI”. Some IT departments began establishing clear rules prohibiting the use of any random prompts or agents within the company. Others didn’t.

WHAT’S THE REAL RISK

Autonomous Agents can be built with hundreds of tools and perform tasks that help users to ease their daily routines, delegate tasks, or help create tasks digitally. This is an amazing advancement – we thought. Even within our own board, we heard that we should do that too – maybe just for fun or just for a while. We did not. If 1,000 of 10,000 employees build their own agents or have even authorized developers who do so, who is in charge? Who coordinates the development? Who takes responsibility?

TODAY’S WAKEUP CALL

I don’t try to spread fear. I don’t even want to list what could happen, and that list would be long. But I want to make sure that whoever builds DIY Agents NEEDS TO KNOW EXACTLY WHAT THEY ARE DOING. And that is not easy when you don’t know what you don’t know. Just two days ago, we discussed this topic in our “Enterprise AI for Executives” training. Little did we know that 48 hours later, one of the biggest cloud providers would be forced to make a decision of epic proportions.

WHAT CAN YOU DO – AI ASSET MANAGEMENT

1) Understand the value of your AI Assets.

All those AI Assets (Prompts, Agents, Multi-Agent structures, and entire AI Applications are highly intelligent, powerful, and valuable Assets. Take those assets under control – all of them – no exception.

2) Look for AI Asset Management.

An Enterprise AI platform needs to provide AI Asset Management. This makes them discoverable, puts them in libraries, and makes them measurable. Ensure you know who created the AI Assets, make an exact description mandatory, and measure each Asset’s productivity. And finally, let users rate them, provide feedback on each asset, measure usage, and manage maintenance, quality, and safety. BlueCallom’s AgenticBlue Platform has AI Asset Management built in from the ground up.

3) Platform-controlled IP Protection.

An Enterprise-grade Platform is obviously more than just a management and control instrument. Your Prompts, Agents, and full-size Agentic AI Applications have an inherited Intellectual Property Value. Even if you buy an Enterprise Application, there is a lot of corporate knowledge included that needs to be protected. While everybody should be able to use those applications, nobody should have access to the IP, whether it’s the inner workings of an agent or the custom configuration that makes a difference.

4) Access to powerful resources

Not only do you get your AI Assets under control, but you can also give all your assets a powerful, yet controlled access to countless resources like mail servers, APIs to other applications, full integration into your Enterprise AI applications, and even controlled database access if necessary. Moreover, you can connect them to the analytics or report engine, let them access deep research, and more. BlueCallom’s AgenticBlue Platform even provides a complete agent- and multi-agent-development system, GPTBlue, for creating float-stream applications, parallel processing, and non-linear (lateral) workflow execution.

More about Enterprise AI: https://bluecallom.com

What can happen to individual users is bad enough. But having it happen in Enterprises will soon be considered irresponsible.

We’re happy to invest some time exploring your individual business situation, what you’re trying to achieve, what you want to get out of AI, and what your hopes are for future collaboration with AI. AI is a mindset, a journey, and start for building a cognitive enterprise.