Sharon Gai uses the "beekeeper" metaphor to describe how AI should shift work from endless task lists to orchestrating AI agents. She introduces the Hive Audit framework to identify which activities AI can handle and which need human skills, and outlines five phases of AI adoption, from search engines to integrated connectors across CRM and marketing platforms.
Chapters
In your book, you talk about the busy bee versus the beekeeper. Can you explain it and how that works in the world of AI?
So there's a bee on the COVID of the book, and the reason for that is I think pre-generative AI, which is the year of 2022. We kind of just went about our days with our endless to-do lists and one after another. Monday morning, we open our laptops and we start going down the list. Post- 2022, we should be a lot smarter in handling that to-do list where there's a lot of work is what I call busy bee work. And now with AI agents, you should be, or we should all elevate ourselves to become beekeepers, which are people that in, in a real beekeeping environment, these are the people that create the environment for which bees can thrive. This is the new mindset that we should have, which is how do we become that role when it comes to our work?
What you're describing is the beekeeper as the leader of a productive organization that optimizes everything.
Headcount used to be a very gorilla exercise, like, oh, I have a 100-people company. Next person's like, I have a 1,000-people company. And that was a, like, a point of pride as a point of comparison. I think that's no longer gonna be a number that's gonna be a point of pride. Um, instead it's either revenue per employee or some other metric that we're probably going to come up with because I think this new age, it's how do you work more wisely with these tools that are available to us.
In your, your book, you make a distinction between augmentation of skills is one category, and the other field is skills that AI will replace. Tell me more about that.
I run this thing called the Hive Audit, which is looking at your 8-hour work day and trying to figure out with you how much time are you spending on things that should be outsourced to AI. It's an audit where we are doing this self-reflection lesson of what to hand over and also a realization of what is impossible to hand over because there are things that is, is very hard for AI to take on also. And for us to realize that and for us to be better at those tasks because those tasks are things that will always be with us and just figuring out out how much of our jobs is one or the other is very important for information for the individual to know and also the, that person's manager and director and upper levels to know as well.
How does Agentic AI help sales organizations today?
I also worked in sales and I remember the days of cold calling. You're dialing different numbers, you don't know if they're going to pick up, but you keep on dialing anyway. That's a perfect job for AI. And so now there are all these different companies that are still calling on behalf of your customers, but if it is going to voicemail, it just calls the next number. But if that person picks up, it routes to the human or it alerts the human that this is now somebody that is ready to talk to you. But also now there's also this new term called the go-to-market engineer. So a lot of sales teams are being reorganized that way, whereas before we had a team of sales development reps and their jobs were to get maybe 40 or so meetings, Zoom calls a month with a prospective customer, and they had to find whatever way to do that. All of those things are now doable by AI. So the sales org itself is revamping or, or changing. Whereas before you maybe didn't need that full team of human SDRs and you just need that one go-to-market engineer that knows pipeline very well and the different pieces of that make up a pipeline very well and starting to use agentic systems to go after that. I think in the, and I wrote an article about this too, which is the 5 phases of AI adoption, where the first phase is it's a glorified search engine. And I think we're past that phase now. Stage 2 is when AI is helping you finish things and create things for you. That era is also getting quite mature. That this current phase that we're in is in the connectors phase where this one AI system is connected to all sorts of other enterprise applications that I use, whether it's Salesforce or HubSpot or marketing system that you use or different social media platforms that you use, and you are calling those systems through this one interface that you have. Right now, this is the phase that is nearing maturation, or it's, it's getting closer and closer to becoming more mature. I think also a lot of companies are stuck in this phase where there's different systems that don't connect very well, and so you have to build something specifically to connect it., but there are so many different things that Attentik systems are helping salespeople finish.
You give a lot of keynotes, and I've read that, um, you are using an analogy between vitamins, uh, painkillers, and vaccines, and, uh, you are, you're not the vitamin, you're not the painkiller. You vaccinate people to create immunity against what?
Against disruption. I think I'm somebody who's not that easily disrupted. And I try to do my best to, to write that in a 200-page book, and that once you read that, you are now covered or you're protected from further disruption. It's kind of a mindset. It's a certain way of thinking too, because I think AI is just one of the many further disruptions that we'll have. Um, I think we're sort of at the tip of the iceberg of what is about to unfold and what is about to happen in the next couple of years. So I think it's, it's, it's just one of many. And I think realizing that it's one of many mentally stabilizes people as well, to realize that this is not the one size or one thing that will, you know, or one final blow or one final thing to change everything, but it's just one of many. There's a lot more disruptions in the coming years.
