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Welcome to Using AI at Work.

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I'm your host, Chris Daigle.

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Each week we'll be learning how today's business owners, entrepreneurs and ambitious professionals are.

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Getting more done with smart use of tomorrow's tech.

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Let's get started.

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Right now, every business leader is asking the same question. What are we going to do about AI? If this is you, chiefaiofficer.com has the answer. We give you a simple path forward where we provide executive and team training so your people know exactly how to safely use generative AI in their day to day.

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We also manage the deployment and implementation.

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To make sure tools actually get adopted and deliver results. And we'll also guide company wide transformation so AI becomes part of your operating system, not just another shiny object. The companies that act now will increase productivity, cut costs and grow faster than their competitors. Those that wait will get left behind. So if you want to make AI work in your business, visit chiefaiofficer.com and see how we're helping companies of all sizes finally get results from AI.

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Okay, today's episode is going to be a little different. Normally I'm the one interviewing individuals and kind of, you know, sussing out their expertise and insights. But today, with it being at the beginning of the year, I wanted to share with all of you kind of the recommended tool stack that we're encouraging our clients and students in our certifications to kind of use. Look, the tool landscape is only growing. And it's always, I mean, ever since we got involved in this in early 2023, it's been the number one kind of point of confusion for most executives and professionals who are using these tools. Which tool should I use? Where do I start? And we've seen a lot of tools come and go. We've seen, you know, GPT wrappers, we saw GPT plugins, we saw all kinds of stuff that people thought was going to be a huge opportunity. And then the models kind of just introduce that functionality in their core offerings and there goes an entire industry. So the tools that we're going to be sharing with you today are things that we feel are, A, best in class, B, they're going to be sticking around and C, they're, well, see, they're easy to use and D, they're going to give you immediate benefit just as a knowledge worker. Right. So before we jump into that, I kind of want to share a couple of concepts that we always want. Somebody who's going to be leading an AI, whether it's conversationally or actually, you know, driving it inside their Organization. There's a concept that we want to make sure that people understand right out the gate. And that's this concept of thinking in AI, something that we've been talking about. I guess, you know, we noticed it happening early on, but we haven't ever really like codified what that is. So to me, thinking in AI is that moment when you or somebody on your team, they're working with a tool or they, they're, you know, in some training or something happens and that they have that aha moment. They're like, oh, wait a minute, if Chad, GPT or Claude or whatever can do this, that means it can do this. Oh, then it could do this and this. And just really the matrix kind of opens up for the individuals and they go from thinking about using generative AI in this like discrete application such as, oh, I'm going to use it to reply to emails. Oh, I've got all these reports. I probably need to get the, the TLDR from right? To somebody who every time they're, they're taking an action in the business, they may not use AI, but they're at least thinking, okay, how could AI support this? How could generative AI, how could this tool support that? Right? So it's, it's, I think Ethan Mollock called it the cyborg in his book CO Intelligence. But it's this idea of this seamless transition, I guess, that you make from doing the old way to the AI empowered way and back and forth and back and forth where it makes sense. Now once that, that aha moment happens, the next step in thinking in AI is it becomes that new reflex where you're encountering a situation or an opportunity in the business or in your role and instead of going, huh, I wonder what your reflex is? Oh, let me ask the models, I wonder if we could. Let me ask the models. How would I, oh, let me ask the models. It just becomes that new reflex, right? And then the third step in thinking in AI is that you share that aha moment. Like you start to evangelize inside and say, oh, hey, oh, let me show you what I'm doing. Oh, you know what? Instead of doing it that way, maybe try this and you walk over and you lean over and you show them on the keyboard or you shoot the loom video to help your team understand how to do stuff, right? You spread this awakening because you being an AI fluent individual is great, but the real impact is going to come from your entire culture and your business being one of knowledge exchange, excitement and enthusiasm about using the tools and people being recognized when they are doing something clever or novel with the tools in their workflows or processes. All of this should be done through the lens of governance. And we'll talk about that on a future episode for sure. But this is just conceptually like what does this look like for your company in 2026? Another topic is AI ready to replace jobs? You know, ever Since, I guess ChatGPT 3.5 came out, there was this concern of, oh no, it's going to AI is going to take my job. If you're using the tools, you realize that like AI is not ready to take your job yet. It can certainly augment, it can certainly replace parts of your job. But there's this concept of human level AI and economic level AI, and I think that I first got introduced to this by maybe the folks over at the Marketing AI Institute with their fantastic podcast called the Artificial Intelligence Show. But if you think about what a job is, a job is made up of projects that somebody does and those projects themselves are made up of multiple tasks, right? So again, if you think about a job is made up of projects, projects are made up of tasks. And for AI to be able to take your job, it would need to be able to perform most of the activities at the task level and the project level. Currently we're not there. Even with the excitement about Claude code and the powerful automations that are being built and the agentic platforms that are quite capable, it's still not there yet. I think that the statistic that was shared was that the current capability of the tools. Now this was data released in December through an MIT report. But the current capabilities of the tools can address about 12% of knowledge work that's taking place in the developed world. Right? So now that's. Can it do it? Yes. Is it doing it? Well, that's up to the individuals or the companies. Have they introduced the stuff? Do they have somebody in their team? They have a chief AI officer who's saying, hey, we can use this in this department. Oh, this workflow can work over here. So what it can do and what is being done, there's a gap there, right? So, but even now, if you were fully enabled with the technology, only about 12% of the knowledge work that's occurring in your industry, your business, can be handled by AI. Now that's a far cry from doing their job. I mean, that's a good start. But now I am going to say I expect that number to track along with every other number related to AI. It's getting better all the time. It's going to be consuming the market pretty quickly. So if you think about it, AI is great at the task level stuff. Drafting the email response, summarizing the report, analyzing the spreadsheet, researching the competitive landscape. And it's starting to be good at the project level, maybe managing the entire budget cycle. It can certainly support it, but it still needs human oversight. Running a marketing campaign from start to finish can do a lot of the heavy lifting, but it still needs humans to give it that direction. AI is not ready for that job level work of replacing the cfo, replacing the sales director, replacing the operations manager. And the main reason is that jobs themselves require context, relationships, judgment, strategy, accountability, that in its current state at the beginning of 2026, AI cannot provide that. But if you think about, let's say, okay, well that's great. Should we still focus on this? I mean, helping with it with emails isn't that big of a deal. No, but I want to give you the math on this. The average knowledge worker in their job has, let's say 15 to 25 ongoing projects per year. And in each of those projects, maybe it requires 20 to 50 tasks. So that means in the course of the year for a, let's not say an A player, even just your B player knowledge worker in your organization, they'll be performing somewhere between 300 and 1,000 tasks over the course of the year. And if we look at this economic level opportunity with AI, again, not the human level, but the economic level, we know that AI can currently, let's say, fully automate 10 to 15% of those tasks. It can significantly assist with 30 to 40% of those tasks. But there's still going to be about 40 to 60% of tasks that the help that AI can do is going to be limited or no help at all because of that requirement of the context, relationships, strategy, all that stuff. Even so, the translation is that on those B level employees, AI should be able to start saving them 100 to 300 hours per employee per year impact, certainly, and in some cases a lot more than that. But if that's what you got from your AI enablement efforts inside of your organization, that matters. Depending on the size of your organization especially, it really matters. So it will be impacting the economics of that role, but it will not be replacing the employee. That's my prognostication. So with that out of the way, let's talk about some of the tool stack that we usually recommend for executives or leaders in a business. Now, the first one if you don't have an AI meeting taker showing up to as many of the zooms that you're on and teams meetings that you're on and that sort of thing, huge miss. One of the big wins for AI is that if it's got, if you remember we talked about it can't do the human level jobs or replace the humans yet because it, it needs context, it needs to understand well and you know, in the last meeting Bill said this and now Terry's saying this, it doesn't have that context. But by you starting to document all of these calls that are happening in your organization, client calls, internal teams calls, interviews, one on ones, whatever those are. A you can focus on the call. The you know, immediate benefit of being able to focus on the call and not worry about missing anything and knowing that you've got the ability to go back and reference that call when necessary. But on a more macro level, you're building context of what's happening in the business at a granular level. Very important. So the tool that we use for that is Fathom. And if you go to chiefai officer.com fathom I think we've got a redirect to their site, number of reasons why we like it. There's plenty out there that are great, all that jazz, but that's the one that we use now. If you're not using Perplexity, and I know that this is an AI forward audience listening to this podcast, of course, and if you're not using it, no shame. However, I would encourage you that for any type of online web research, just at the basics, it does a lot more than that now, but have this replace Google you next time you need to Google something, plex it instead. That's kind of what they call, you know, perplexity activities. I'll leave the surprise of the experience to you, but suffice it to say that that has become, I don't know when's the last time I did a Google search outside of maybe looking for a restaurant or Google Maps. But for any knowledge that I need that is current event, time sensitive, that sort of thing, Perplexity is your new search engine. And to piggyback on that, Perplexity has released a Chrome based browser. So your browsing experience will be just like what you're doing now called Comet. Comet is free, but Comet is essentially what's becoming agentic web browsing with this browser. And we're not going to get into it on the podcast here today. There's plenty of tutorials out there, but this is one that needs to be on your short list of going to test the Perplexity comment browser. Now, Chat GPT has the Atlas browser and there's some benefits to using that because it's going to have all of the context and memories that is coming from your Chat GPT account. But my default has become Comet and not Atlas NotebookLM. You've definitely heard of it and may not know it. You've definitely seen output from it. If you're paying attention to what's going on in the AI space and may not have known it, but that tool right there is a fantastic resource for creating a learning environment, a knowledge environment for you personally or your team. Gamma Gamma app or chiefaiofficer.com gamma if you go to Gamma, it is our default tool for creating presentations. It will spin up a PowerPoint slide deck in two minutes. That is very attractive and high quality design. And then for image generation for really anything you need. Currently Nano Banana funny name, I know, but Google's AI image generator is the kind of top of the pack today as of this recording. So that would be the suggested tool stack that I would recommend that you start to investigate if you aren't using them currently. Fathom for your AI powered meeting assistant Perplexity just replaces Google. The Comet browser from Perplexity which is introduces you to agentic web browsing NotebookLM from Google it's just a smarter way to learn. Gamma App, it's essentially instant executive level decks, slide decks from a prompt and Nano Banana which you can find in the Gemini interface with Google but for creating images related to really anything you want. But you'd be surprised once you get in the hang of once you start thinking in AI how many uses you have for image. Custom images being generated in AI, we use them all the time. So this was kind of a short episode, but it was really, you know, an opportunity for me to share with you what we're thinking about, what we're focusing on and how we're seeing the use of tools at the executive level. And really any level doesn't matter if you're listening to this, you're going to get benefit from these tools so that you don't have to go out there and sort through all the hundreds or thousands of tools. That's what happens. That's what the chief AI officers are doing. In our chief AI Officer community, you're more than welcome to pop in and say hello and see what else they're up to. But that's the benefit of being plugged in. And that's another last bit of advice I would give you. If you're doing this on your own, you're missing out on the power of this kind of like collective intelligence. There's so much happening at speed that you trying to have, you know, a full spectrum optics on what's happening is impossible. Plug in somewhere, find that group that you know. You've got some people from different domains. You've got the finance expert, you've got the operations expert, the engineering expert. They're looking at it through the their lens, right? So they're bringing back information and tools and processes. Look at the individuals who are tech forward versus those who are a little hesitant and they're not techies having that, that collective perspective allows for the filtering of all of this information to be coming through all these biases and you get the benefit of knowing, hey, I got a question about this. Oh, I got somebody, Hey, I got a question about this. Oh, she's really good at that, right? Trying to do this on your own, it's better than doing nothing for sure. However, it is going to be a challenge. So my advice would be plug in to an organization or a community where they're as enthusiastic about discovering AI and becoming fluent in AI as we are at the Chief AI Officer community. So with that, we'll catch you on the next episode. Thank you so much for listening and if you get value out of the episodes that you've listened to, I would really appreciate it if you would help me help other people find out about this through a review or a shout out somewhere. But if you go to the your podcast platform of choice and just leave a review, I'd really appreciate it. So anyway, go out there, use AI. We'll see you next week.