Here at TomorrowZone, we regularly experiment with AI. As an industry leader in the AI conversation, we lead by example. We assess our tech stack on a consistent basis and are not afraid to investigate new technology, particularly artificial intelligent agents. We believe strongly in the power of human and machine collaboration. Let’s be honest, we all have parts of our jobs that we prefer not to do and often find ourselves bogged down with mundane items on our to-do lists. At TomorrowZone, instead of becoming overwhelmed, we recognize that a stacked to-do list is an excellent opportunity to delegate to an AI. 

It is important to have basic guidelines for experimentation with AI. Our process is to first check for some basic must-haves, namely security and integration with our current tech stack. Then, we experiment, assess, and decide.

Experimentation is the fun part! The process isn’t perfect and as is often the case with those scenarios, can be quite funny. Like many professionals these days, one of the areas we have adopted AI powered automation is with AI notetakers. When our AI agent can join our virtual meetings and take notes on the call, our human team members are better positioned to focus on the content of the call and each other. It is a case of AI enabling us to be more human. 

We consider the AI agent to be a member of the team with a narrowly defined job. If you are not familiar with AI notetaking apps, there are many options from which to choose. Most AI notetakers will record and transcribe a call and will offer a summary of the call’s high points in addition to the full transcript. The investment in this robotic teammate has paid off in helping us to focus on the people in our calls and accelerate our work through rapid follow-up. The AI note taker doesn’t get tired or bored with the job, and consistently delivers meeting results on time.

Even with all the benefits, occasionally, the way TomorrowZone’s robotic team members summarize and interpret interactions, provides some hysterical moments for the TomorrowZone humans.

For instance, on a livestream planning call, one of the participants was getting over an illness. In the assigned follow-up tasks section of the summary, our AI assigned the following task, verbatim, “Recover from illness and prepare for the upcoming livestream discussion.” Think these AI developers are training on empathy? 

Name interpretation is another sure-fire way to find AI comedic relief. On a recent transcript for an industry roundtable hosted by TomorrowZone, our AI notetaker interpreted TomorrowZone’s human team member, Jennica Burgh, as “Jonika Bird.” That’s a new one. Turns out Jennica’s name is confusing for both humans and machines!  

Sometimes AI’s just completely miss the mark. You may have heard of “hallucination” in the context of generative AI. That is when the AI, as it generates meaningful content, also generates false results. Here is an example of a note taker hallucinating. This is an excerpt from the summary portion of the same roundtable transcript, “Deborah asked Kim to mute herself and stop speaking, while Jennica expressed gratitude for Deborah’s instruction.” Here the AI completely missed it. There wasn’t even a Kim on the call and the TomorrowZone team never would have called out a participant like that publicly. This was so out of character. We found it hysterical. But also, an important reminder of the importance of humans in the loop for content audits, especially when content is generated by AI agents.

One important factor to remember is that AI notetakers are just that, notetakers. Programmed to report everything they hear; they do not discriminate on whether the content has anything to do with the main topic of the meeting. The AI agents can recognize small talk, but don’t have the human intuition to distinguish the importance of the small talk to the point of the meeting. Our robot teammates are very thorough. We have notes from favorite grocery stores to favorite health supplements. One time, the AI reported that a client was very interested in sandwiches with massive amounts of fresh tomatoes (which, of course, resulted in uncontrollable giggling from our human team).

The point in all this is that experimentation is just as described, simply an experiment. The goal is to learn, practice, and assess as you go. It will not be perfect, and it may be funny! If you are considering experimenting with new technology before adoption, remember a few important guidelines. 

  • First, start with security and compliance. Make sure that any tech you are considering has solid security in place and fits within your company’s compliance standards. 
  • Second, enjoy the journey of experimentation. Play a bit. Explore what’s possible. Many new technologies have a free trial period. Maximize that opportunity. 
  • Third, remember that humans absolutely must be involved. Think of your AI as a brand-new intern who needs a lot of supervision. It may be able to get you off to a great start, but humans absolutely must evaluate and make final decisions. 

Crank up your curiosity. Don’t be afraid to experiment and learn forward. At the intersection of human and machine collaboration, we find amazing opportunities to raise the standard, change the game, and make awesome happen.

If you want guided help evaluating your technology strategy or understanding where AI automation capabilities can fit into your business processes, reach out to us at TomorrowZone today.