Two past coaching clients just reached out to ask me about structuring AI into their companies this week. This tells me it’s time to write an article, so here we go.
One of the principles behind Organizational Physics is that you always want to manage appropriately for the lifecycle stage of the project, product, business, or business unit. First you pilot it, then you nail it, then you scale it. AI adoption is no different.
The Pilot It Stage of AI Adoption: Using GPTs
Most companies are already in the Pilot It stage of AI adoption. Employees, especially innovators and early adopters, are using AI tools to be more productive, but the work itself has not fundamentally changed. This means that your social media marketing manager uses a GPT plug-in to create more social media posts, but their job remains fundamentally the same. It’s the same for software engineers, salespeople, and really any knowledge worker using a GPT. Discovering what different AI tools are capable of is fascinating and a bit unnerving. On their own initiative, the leading edge is researching and deploying their own AI tools and often bringing their findings back to the company.
Of course these discoveries raise plenty of questions and concerns. “Wait… what about data security?” “Wait… what about privacy?” “Wait… does this mean won’t have jobs?” These concerns are valid, yet every thinking person can see that the world has changed. If your company is going to survive and thrive, then it must quickly figure out how to nail AI adoption.
The Nail It Stage of AI Adoption: Building an AI Brain
My coaching clients on the leading edge of AI adoption are all on the same mission right now: to create and leverage their own internal, centralized AI brain. […]