Mastering AI: Five Key Traits for Success

My latest articles on AI, specifically on LLMs, have focused on the value that these tools can deliver to companies. In summary, there are four areas of value that AI can (and is) delivering:

· Easing simply tasks

· Simplifying complex tasks

· Acting as a thought partner

· Becoming a flexible interface

I have heard several podcasts and read more than one article where someone says: “AI won’t take your job, but someone who knows how to use AI will.” This statement is true on its face, but what does it mean? What capabilities or experiences should become the focus of our training in interacting with AI?

To get to the answer to this question, I identified three personal sources of value in interacting with an AI (specifically an LLM):

· Faster arrival at what I already know. LLMs are terrific at summarizing and bringing together information that I already know – what emails did I send, what is the specific language for this OSHA regulation, what are the take-aways from the meetings I attended this week.

· More thorough application of what I already know. AI can serve as a check to make sure I am not missing something obvious, such as a note in a material specification document or language in a contract.

· Exposure to perspectives that I have never had access to. Because of the broad scope of LLM training, the AI has access to writings by people who have very different experiences. This is valuable in two ways. 1) It lets us check our own assumptions. We all have our own (very well defined) perspective on the world. We can ask the AI to uncover our assumptions and provide powerful counterpoints. 2) AI can provide suggestions to help us succeed in areas where we are not the strongest. Whether it is a task that requires you to work at the other corner of your DISC profile or one of our areas of working frustration (in the six working geniuses), a conversation with an LLM can provide suggestions to help you be successful.

The question that follows is obvious – what are the characteristics we should strengthen in our teams to enable them to fully embrace the AI? I would suggest five:

1. Effective communicator with an AI. Writing a prompt takes some practice. For many organizations, this is the right starting point. What do we want the AI to do and how do we ask it to help us do it? This is, of course, only a starting point. We can also help our teams understand what the underlying algorithms are and how we can use that knowledge to communicate better.

2. Good judgment. Interpreting the output of a conversation with an LLM requires judgement that is achieved through learning, interacting with more experienced colleagues, and gaining experience on your own. The LLM is just another perspective (and one that doesn’t have the experience of you or your team) that is likely to require your discernment to apply it correctly. Taking an AI suggestion without running it by someone (you or someone else) who can judge its applicability to your reality can range from a really bad idea to objectively dangerous.

3. Curiosity. Because the value of an LLM’s conversation is its opportunity to provide broader exposure to other perspectives, people who take best advantage of AI need to actively seek out other ideas, approaches, and applications.

4. Creativity. One of the personal values of AI is the ability to arrive at what I know more quickly. That creates space for us to be more thoughtful and creative in how we can use our time, rather than simply summarizing what I already know.

5. Intellectual vulnerability. In a discussion with my team, someone suggested that the LLM never gives them good suggestions on how to improve their documents. It is entirely possible that the prompt isn’t giving them perspectives they haven’t considered, but it is also possible that they have discounted those perspectives.

To use AI effectively, we need to approach the conversations with curiosity, openness, and quite a bit of skepticism. Training our team to write good prompts that challenge their assumptions, think through the applicability of the suggestions (both alone and as part of a broader team), and creatively adopt the best output of the conversation is our task. Every company needs to step up to this task. If we don’t, a company that has done a better job preparing their teams will.