Ep. 59 Can AI Solve FOMO?

Knowledge workers—especially people managers—feel constant pressure to stay on top of everything happening across their teams, companies, and industries.
AI promises a solution: summarize everything, surface what matters, and eliminate the fear of missing out (FOMO).
But does it actually work?
In this episode of Talk To Me Petey D, we break down the reality:

Why AI can’t solve the “infinite buffer” problem
How frictionless tech (like email and AI) actually increases information overload
The real limit: human cognitive capacity
Where AI does help (better organization, search, and reducing context switching)
The hidden risks around privacy, behavior change, and over-recording conversations

Most importantly:
Why embracing JOMO (the Joy of Missing Out) might be the real productivity strategy for leaders.
If you’re a manager, knowledge worker, or anyone trying to keep up in the AI era—this one is for you.

👉 Key Takeaway:
AI can help you organize and retrieve information—but it can’t decide what matters. Prioritization is still your job.

📌 Check out more:

Book: https://www.amazon.com/People-Management-Ground-Up-Aspiring/dp/B0DBGQ57XT
LinkedIn: https://www.linkedin.com/in/pete-dempsey/
Partnering with AI Agents for Business Success: https://www.linkedin.com/learning/partnering-with-ai-agents-for-business-success-by-pearson/
Website: https://peterdempseywrites.com/
Newsletter: https://peterdempseywrites.com/newsletter/
Bluesky: https://bsky.app/profile/petedempsey.bsky.social
YouTube: http://www.youtube.com/@TalkToMePeteyD
Apple Podcast: https://podcasts.apple.com/us/podcast/talk-to-me-petey-d/id1745885025
Spotify: https://open.spotify.com/show/4NrlsWzansuCfuApMCZzj0

👍 Like, subscribe, and share if this resonates.

Transcript

SPEAKER_00 0:00

Knowledge workers, especially people managers, often want to keep tabs on everything happening in their organization, company, and industry. This professional FOMO, or fear of missing out, is real, especially in times of job insecurity like today. AI is often pitched as a tool to effortlessly keep up with everything. Can it deliver on its promise? We'll dive into the topic today. This is the Talk to Me PDD Podcast. I'm your host, PDD. This is the show where we talk about all things tech and society, knowledge work, leadership, management, and of course, AI. Please like and subscribe, support the channel. Love to keep this content going. Love to hear from you. What topics are you interested in? What resonates? What do you want to hear more of? This is episode 59. Can AI Solve FOMO? You know, my perspective is that there's lots of questions here, and I'm not sold that it's a total solution, and I'll go into why that is. But I also think there are some areas where AI can really help and extend some of the productivity systems that have already proven to be to be effective in this space. So AI is pitched as being able to summarize lots of different information, pull out the important bits, maybe get to know a bit about kind of how we as an individual work and what might be important to us and the type of systems that we have. So this is kind of how I'm how it's pitched as a way to keep tabs on more things than what you're able to do with without it. Now, what are some problems here? And I'm gonna I'm gonna draw from Cal Newport, who's talked a lot about productivity, and there are a number of other people in this space, kind of in that sphere. So one is this idea of the infinite buffer problem that sort of the more information you're able to pull in, the more things you're able to do, the more tasks and that sort of thing. You're never gonna get to the end of it. There's always more there. There's an infinite amount of things. Um, so at some point, you're always going to have to prioritize or say no. So I think that's something that we don't necessarily think about with AI and using that to uh capture and summarize all of the different data that we might have access to and all of the things going on, um, that we're never going to get to the end of summarizing every possible thing that we can look at. So um that's not something that AI is going to be able to solve. Another challenge has to do with friction and technology and how technology can make certain tasks um frictionless, you know, having less friction, and this is just how difficult things are to do. Um, so a good use case historically is to look at email and electronic communications. Email technology made it much less caused much less friction, much less effort and work to be able to communicate with someone, which is great. But then a side effect of that is because it's frictionless, you tend to communicate more and the volume increases and the specificity of the communication um goes down because it's so easy to send messages when you had to write somebody a letter, say, or walk over to their desk, um that was a bigger commitment. So you had to spend more time up front thinking about how you're going to communicate, what you wanted to get out of it. So you weren't spending a lot of time going back and forth because it wasn't easy to go back and forth. So I think there's the same potential um sort of side effects of if AI is getting really good at summarizing all of this information, informing us so we're not missing out. There's just going to be more and more stuff kind of going back to that infinite buffer problem, why that's happening. Um even now, you know, you're gonna have AI tools creating content. Um, so while you're sort of racing to summarize everything and keep on top of everything, um, you've got more and more content ever than ever before, and a lot of that content created by by AI-related tools itself. So um a lot of challenges there just from a capacity perspective, having AI capture everything that you might want to know about. Um, but even if it could, I think the reality is you're gonna run into some cognitive capacity limits. There's even without AI, even without um digitized information, um there's so much out there already, even if it was summarized well and sort of organized for your own particular interest, your own particular capacity to synthesize, to take in that information and to make use of it, to not just kind of throw it out and lose it after you've read it, is is limited. And that's that's a human limitation, and that's not going to go away. Um, there are things that we can do to train that and try and increase that capacity, um, but it is limited at some point, and I think it's far more limited than what AI is capable of summarizing and bringing to us. So that's a real limit there, and that's not going to go away. Now, I do think there are some areas where there is hope. One of the scourges of productivity, especially in modern knowledge work, is having to context switch, to go back and forth between many competing responsibilities, being interrupted by emails or or messages or meetings or things like that. Uh, this is something that's talked about a lot in the book Deep Work, how it's so hard to have focus time. And whenever you're interrupted, that takes you, you know, 20 minutes or so to get back in that mental focus state. Um, so this is an area where I think that AI can help us. There are some manual productivity systems now that are based on sort of batching around similar concepts. So let's say you have a couple hundred emails to go through. If those are organized into different categories, maybe by project or theme or audience or things like that, you're doing less context switching if you work on a batch that has the same cognitive context than if you just try and go through maybe in systematic order, the order that they were received. Um, because with each one, you're gonna have to switch back and forth on context. With you're doing it in a group, um, then it's it's much easier to avoid that context switching and to focus on a particular area. Um, so there are already some you know simple tools that can be used to label emails or communications or things like that. I think broadly there's a lot more opportunity where where AI tools or agents or capabilities built into existing communication tools could help do that. So then if you are taking this summarization or organization piece and you're able to define the categories or sort of the groupings that you want, or their AI is able to learn those from watching your behavior, then I think that can be really helpful and make it easier for people to keep track of the things that they care about. You still have to define what those things are and what the prioritization is to you, but it does have the opportunity to automate some of that organization. Um, also, I think in a lot of the tools that we use for communication and data handling, um search and being able to find things is just not very good. The technology is there, it could be better, but be that as it may, um it's difficult to find information. And I think people feel like they have to be much more active on manually tracking it and reading things in real time because it can be difficult to go back and find that information if you haven't processed it as it comes in. AI has helped fill that that gap. Um, maybe it's a little bit um more than you need in a lot of these situations where a more basic search could do the job. Uh, but since it's not there, um, AI is pretty good at doing that. And I think there's less worry about FOMO if you can go back and find these things after you've seen them initially, or you don't have to be monitoring monitoring them in real time. Um, and that's something that I've really seen as a benefit from AI in terms of information retrieval, is it's even though some of these things are possible with search, they're they're just not there for whatever reason on a lot of applications, and AI can fill that gap and help you find information. So you'll you're less worried about missing it and feeling like you have to see it in real time. Um another kind of going back, those are those are good things, and I think positive things to look at is um maybe some potential downsides uh of using AI to summarize and collect all this information. There's now this incentive to digitize everything so you can go back and have these your AI's tools use it to learn from it, to find that information. And there are, of course, privacy implications to that. Not every type of data you necessarily want recorded or used in that way. And there's not a lot of granularity on how to do that now, how to manage data retention, things like that. Um, but then it also can actually change our behavior. If you know that an AI is recording something, um you may change the way you talk, you may say things specifically so they get recorded and then can later be used by an AI system, which if you're talking to real people as well at the same time, it's going to be a different type of conversation. And it may also discourage people from having sensitive conversations. Let's say you have a team meeting that you always have recorded so you can leverage it for various AI systems, which may be very useful for capturing that information to solving some of the this FOMO. The downside, and you may not even be aware of this as a team leader or a manager, is that some conversations might just not happen. You might not get that information if people are concerned about it being recorded and potentially being being used in other ways. So something to bear in mind, um, and probably good to have different opportunities where you're not necessarily recording everything. So you don't miss out on that information and give people the opportunity. Um, so let me wrap it all up. I know it's a lot, it's a lot there with with AI and FOMO. We have these these problems of of infinite buffer. There's always more information that then we can possibly process. Um AI and AI summarization and categorization is further going to reduce friction to create content. So more and more content going up. Um, there's only so much that we can process with our own human cognitive capabilities. Things like organizing by different categories and batch processing, so there's less context switching is a real benefit that AI can help us with. Um, but ultimately we still need to do some prioritization, prioritize our focus, determine what's important so we can go and focus on that. So, end of the day, it's okay, be okay with FOMO, professional FOMO, embrace JOMO, the joy of missing out, even in the professional world. Um, as long as you prioritize, it's going to be fine. Um, but you should always have have FOMO on fear of missing out on the Talk2Me PDD content and podcast. So please like and subscribe. Uh, check out my newsletter, I'll have links in the show notes. You can uh find that on peterdempseywrights.com. Um, I have a book for people managers, especially new people managers, that talks a lot about prioritization. So if that's something you're interested in, uh you can check that out. Um, you know, also missing out as a manager can be a way to show your team that you trust them, that you don't need to micromanage everything. Um, so it can actually be a tool to empower teams. Um, you know, please also check me out on LinkedIn. You can follow me there. I have a new AI course out on LinkedIn learning. I'll put the link in the notes as well. Uh I got another one on the way, and thanks for listening. Take care and enjoy missing out on some of the things, and good luck prioritizing what's important and driving impact. Take care.