Where AI and People Meet

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Chalenge Masekera: Last year, I thought of AI as a tool, as in, it doesn't do anything until you go and prompt it. It's actually becoming more of a collaborative partner. And also, how we use it in 2025 going forward is more of an agent. 

Vaneese Johnson: It just makes it much more efficient. And you really start to look at AI more as your partner, as opposed to something that you need to fight against, or try and work against. 

Jill Finlayson: Welcome to The Future of Work podcast, with the Berkeley Extension and EDGE in Tech at the University of California, focused on expanding diversity and gender equity in tech. Edge in Tech is part of the Innovation Hub at CITRIS, the Center for IT Research in the Interest of Society and the Banatao Institute. UC Berkeley Extension is the continuing education arm of UC Berkeley. 

As we look forward to 2025, we're reflecting on how much AI has made deep inroads into our future of work, from creating new opportunities for automation and entrepreneurship to its impact on how we hire new talent. AI will no doubt continue to stay at the forefront of our conversations, but we need to remember there are actual human beings coding the AI, responding to the outputs, and implementing change. Where does the intersection of people and AI convene? Are we embarking on a new set of technical and people skills? 

To futurecast what this relationship might look like in 2025, we're excited to welcome back esteemed guests Vaneese Johnson and Chalenge Masekera. To reacquaint you, Vaneese is the boldness coach and helps leaders bring authenticity, intrinsic values, and new levels of engagement to their work. She is also the author and founder of Girl, Get Your Business Straight and Girl, Get Your Career Straight. 

Chalenge is a data scientist currently working at Pharos AI, a company dedicated to enabling enterprises to get invaluable insights into their engineering operations. His passion lies in harnessing the boundless potential of AI and data driven insights. Welcome, Challenge. Welcome, Vaneese. 

Vaneese Johnson: Wow. I've been waiting for this topic. Like Christmas. This is going to be a very interesting conversation. 

Jill Finlayson: Absolutely. Welcome, Chalenge. How are you doing? 

Chalenge Masekera: I'm doing great. Excited to be here. It's been a year since we last spoke, so there's new stuff, and yeah, always excited to be here. 

Jill Finlayson: Absolutely. And we have discussed AI previously, but it really seems like generative AI or ChatGPT, Claude, Perplexity, and many other systems have become mainstream, been adopted in 2024. So before we look into the future, how would you say your own jobs have changed or evolved over the past 12 months? And did you find yourself using AI tools more often? Vaneese, why don't you kick us off? 

Vaneese Johnson: Yeah, actually, I started experiencing the changes in my business using AI in 2023, when I was first introduced to AI. And at first, I brushed it to the side. And I'm, like, oh, it's something else new I gotta learn. 
And then one day, I think I was struggling with a task. I was writing curriculum and trying to be creative with ideas. And so one day I said, let me try this chat thing-- [LAUGHS] --this ChatGPT thing, and see what is it all about. Literally, as soon as I gave it a prompt and it gave back to me information, ideas, ways to think differently, I was, like, whoa, wait a minute. What is this? 

And from that point forward, for the last two years, I really have been incorporating different elements of AI into my business to help me to really be more competitive in the marketplace. I've started incorporating it to help me to have enhanced customer relationships, client relationship management tools. I've incorporated it to also help me with managing my time, as well as mundane tasks in my business, and also for some fun. 

So that's how it's impacted me. And I'm really looking forward to what's to come, what else I can learn with this tool and teach others. 

Jill Finlayson: And Chalenge, same for you, you're more in the tech and engineering software side of the house. You've been using AI perhaps much longer. But has 2024 changed how you've seen it used? 

Chalenge Masekera: Yeah, I think there's been actually really good changes that has happened, as Vaneese has said. I think there's more people who've actually started embracing it more than they would have normally done. And personally, I think the amount of time I've spent using AI has grown. 

Even more so, I think it's just come from being something that I think about as in, like, I'm stuck, I need to do something, to something that's as I said, the first episode AI native, like, I think in terms of I want to do this, how can I use an AI to make my life better. 

Jill Finlayson: That's interesting. So from troubleshooting to now being a starting point. 

Chalenge Masekera: Yes, absolutely. It's so much more productive for me. And like, I don't know if I'm losing something, but my productivity has gone so much higher because of how I use AI. 

Jill Finlayson: Well, that reminds me. You once referred to AI as an accelerant. What does that mean to you? 

Chalenge Masekera: What I think of it in terms of an accelerant, I think what's the one thing that you want to have in life, which is time. You want your time back. And using AI has given me the time back to do other things, or just be able to accomplish more in everything that I do. So in that case, I think of an accelerant as you have an idea, how do you get to accomplishing that idea in much faster time. 

Jill Finlayson: And when you think about AI, do you think of it just as a tool or is this something different? 

Chalenge Masekera: I was waiting for this question. The answer is yes. And by that I mean I think the big change that has happened for 2024, last year, I thought of AI as a tool, as in it doesn't do anything until you go and prompt it. But what we're seeing now is it's actually becoming more of a collaborative partner and also what's going to be probably how we use it in 2025 going forward is more of an agent. 

I think we were getting into this world where there's two types of, if you have a business, there's two types of labor, which is the human labor and also the AI labor, or machine labor. So we're seeing people, actually, or companies adopt agents that run independently. And I think at some point we as humans will be able to, just like in a normal life, have this AI-powered agent that will do the work that you want independently, autonomously from you, and you can just come and review. And I think that's where the world is going. 

Jill Finlayson: That's amazing. How would you define an AI agent for people who haven't really used that term before? 

Chalenge Masekera: This is one of the fun ones where it depends on who you're asking, because there's so much branding that's going on. The classic definition of how it's being branded right now, it's called an AI-powered assistant. And when you talk of an agent, it's somebody who's doing something and working. 
So these AI-powered agents are-- I don't want to say human replacements, but tools that are AI-powered and machine learning software that's able to do tasks autonomously without humans. 

Jill Finlayson: Yeah. So, Vaneese, are you seeing this with individuals and companies that you're working with? Are they taking on these AI agents?

Vaneese Johnson: I think what's different with this side of the coin is that the individuals working in the organizations are starting to embrace them as it relates to some of the mundane tasks in their work. However, the corporations themselves are not embracing it as fully, and because there still are a lot of undefined areas with AI in the workforce. And I think companies are just approaching it cautiously as they are trying to figure out what type of guidelines need to be in place. I think companies do want to use it, and they want to be efficient with it, but I also think they want to be effective with it so that it's not doing a huge shift in business overnight, and I will say some companies that we've seen and that I've seen, some of my clients in some of these areas, more on the retail side, when it comes to inventory management. 

So when you see that, because you want your customers to be able to go and order product-- I mean, we're in the holiday season. So you want to be able to get people what they need quicker, sooner, faster. But you also want to be able to know, from an inventory control perspective, what do you need to be stocking up on. Because that's going to impact the revenue, and it's going to impact the bottom line. 

So in that instance you're seeing more of the adaptation of it quicker, sooner, faster. But on the other side of the coin, where you may have more human interfacing, you may have more administrative type of roles in organizations, you're seeing a very slow adaptation, and especially if a business is not inside of the IT world. 

Jill Finlayson: So share a little bit of those specific use cases where you're seeing individuals starting to use it and then, maybe, Chalenge, you can explain how can companies create more of those guidance to enable this to happen. But what are some use cases that you're seeing where people are slowly bringing it in to be faster and quicker?

Vaneese Johnson: What I'm seeing is more from a data literacy perspective. So a lot of people now are using it to be able to do research a lot quicker, sooner, faster, and then allow AI to help to interpret the data, to help them to be able to get to the next steps of a project that they're working on. So in that case, I see that. 

Also, I see it with communication. A lot of individuals are starting to use it. We've had Grammarly for decades now, an AI tool. [LAUGHS] And so now, people are starting to see more of the value of AI, because the cross-cultural communication is really important, and understanding what's appropriate and how to communicate with colleagues, with other global partners. So you're seeing that embraced, those areas. 

And also, the other part I'll say is innovation and creativity. You're seeing that now, where people want to really explore a little more with some of the work that they're doing. I'm seeing that when it comes to presenting presentations. 

A lot of my clients that I go and do training with on presentations, they're taking now into consideration their target audience, what would be important for this audience to hear, and what would be really key points to zero in on? What is it that you say less of? And so a lot of them now, in the corporate space, are using these AI tools to build their slides and/or enhance their slides so that they can communicate more efficiently and effectively. 

Jill Finlayson: I really like that prompt engineering where they're asking, here's my deck, but please customize it for this audience or for the needs of this group. And making it more personal, but also more relevant and more compelling. And the employee feels better, because what the employees now are experiencing is like, oh, I don't have to stay up all night trying to figure out what to say. I don't have the pressure and the stress behind, what am I going to put on the deck. 

So now the employee-- when I get together with my clients, now we can build it in a short amount of time. Then we can get to practicing the delivering component of it, and that's where the magic happens, is that AI isn't delivering your presentation for you. That's where you, the employee, get to shine in your innovation and creativity. 

Chalenge Masekera: You hit on the key point that I actually like the most, is like most of what the gen AI product has been able to help us is the mundane Stuff. What's important for you, I think, is for your clients, is being able to make the presentation and actually show what their value is, instead of creating the slide deck. That's not what you want to spend your time on. And that's what sort of gen AI, at least in the past years, has been able to make strides in. 

Jill Finlayson: It sounds like the folks that Vaneese is working with are sort of where you were a year ago in terms of using AI to solve problems, but not making it part of their daily routine. What do you think, Chalenge, has to happen to make AI more integrated into workflows? 

Chalenge Masekera: It's a journey. It's like a journey of every tool or anything that you start. You start somewhere. It's like, oh, maybe I should, like, just sprinkle a little bit. Then over time, as you adapt and you become more comfortable with it. I'm like, on the privilege end maybe, or on the high end of the spectrum of tech. I'm kind of forced to be using it because we also work on building AI products. For me, it's something that I have to actually embrace. 

But I think what's happening now is, like, we've come from ChatGPT came out, and all these other large language models came out. It's a prompt box. It's very, very generic. It hasn't been, like-- but we're getting to a place where they're building more sort of specific models, or specific use cases, for tools. I think Microsoft now, they have their own copilots, which are very specific. Like, you're working on a Google Doc, or you're working on a Sheets doc. They have an AI that's specifically built for that. 

So as people start to, I think, as companies adopt, pay into these copilots, we're going to see people just naturally be able to use them. I think once you have it, if you have a copilot, after a while, you're going to be forced to just say, hey, what do you think about this? This is like where you have to go somewhere else and say, hey. I have to open ChatGPT and ask this question. I think as technology becomes more embedded in sort of all the applications that we use, we're just going to see the adoption grow. 

Jill Finlayson: And the tools are making it easier as time goes by. You still have to have a little bit of tech expertise to do some things. But increasingly, that's going to go away as well. One of the things that I've really enjoyed in, I worked with a student to create a RAG, or a Retrieval Augmented Generation, where we got to use the ChatGPT interface to ask questions of a small subset of data. 

And that, to me, was really actionable and valuable because every company has their own rules. And being able to access those rules more efficiently seems like a great use case. Are there other use cases that you think, as you're talking about kind of onboarding, we go from problem solving, what are some of the use cases that you would see companies sort of taking steps to more adopt? 

Chalenge Masekera: What I'm seeing a lot, depending I think a lot of people I've worked with, is basically anything that you want that needs speed and performance. That's where [INAUDIBLE] or what Vaneese told, like, the novelty, where your style, where your personality comes through. I see people more using the LLMs, more that, just like the AIs. So anything that's like, oh, I need something generated super fast, or can you synthesize this information super fast. 

So you can see one typical example is, you get on a sales call. I need a summary of what we talked about. What do you think was sort of the main point that my customer, or this customer, or what's important to this specific individual? I'm seeing a lot of adoption. 

Jill Finlayson: That's a good point, because getting a summary is one thing. Getting a list of action items from that call is a step ahead. 

Vaneese Johnson: There are AI tools that you can plug into other platforms that will summarize a meeting for you, and then tell you, here are the next steps that you need to do. It'll summarize the meeting so that you can send a summation to the client. You now get your next steps on how to move forward in the sales process. And so like Chalenge is saying is that it just makes it much more efficient. And you really start to look at AI. You can start to look at it more as your partner in this as opposed to something that you need to fight against, or try and work against. 

Jill Finlayson: And I think this is all about business intelligence, getting information, and summaries, and insights more actively, more efficiently. We've talked about using that for business. But is there something that would be. I don't know, a career intelligence equivalent, Vaneese? How can we use AI for our own personal development? 

Vaneese Johnson: Oh my goodness. There's so many great uses. But what I tell clients initially, when we start the beginning of this conversation, because I don't think a lot of people really are aware of how prevalent AI has been in our lives. And so that's the first place that I start. When we look at the echo, we look at Alexa, when you look at talking to your phone, you look at when you're getting ready to use your GPS, we already have been using AI. It just wasn't called that. 

And we saw the efficiency of it. So when I'm starting to point that out to people, they're like, oh. That's what that platform is? That's where-- yeah, that's AI that you're using already. So if you can tell it to turn things down, turn things on, turn things off, you're essentially talking to it, and it's helping you like a helper. 

The other component is people are concerned about, Jill, is this going to take my job? I think the thing that we also forget is that we as a people, and as a culture, we have already been through several different stages of evolution in the economy. We were in the information age in the 1950s when computers were first introduced. Guess what? We adapted. 

Then we went to the digital revolution and the automation age in the '90s. Guess what? We adapted. We also went through the digital age. Remember the digital divide where we felt like, oh, the computers-- everybody needs a computer. People are not going to have a computer. What's going to happen with the people that are in certain jobs that don't have access? Companies found a way to make sure that we try to equalize it as much as they could to make sure people could get access to it. 

And here we are now in the AI revolution. And so there's an opportunity for us all with upskilling and reskilling. What we have to help us to better position ourselves as employees of firms to really leverage this technology in a way that can help us to advance professionally, but also to help us advance personally. You can get your own coach now. You don't have to wait, and go find, and pay for a coach. AI can help you in ways that you can become coachable. 

But that has to do with you engaging with the tools so that it starts to learn your personality, your skills, what makes you shine, where your deficiencies may lie. So the more that you use AI tools, that can be a benefit to be able to help professionals to really figure out, where do I go now in my career with the change that's happening in the market? 

Jill Finlayson: So how are you advising people to update their resume? How do they even talk about these skills? 

Vaneese Johnson: Yeah, so that's another thing we look at. And I always tell this to my clients is to really look at-- number one, write a career vision. You need to know where you're going. Even if your vision is to retire, you still need to have a vision for what's next for you and your career. I also tell them to look at what's happening, the trends, for the next five to 10 years in their industry, and also with their profession, because when you can be future focused in terms of what's coming down the pipeline, it allows you to better prepare today for what's going to happen tomorrow. 

And sometimes, today really does come tomorrow, tomorrow, like in 24 hours, because sometimes, these tools get thrusted on you. Or the type of work that you may do gets thrusted on you. And you have to really figure out right away what to do. I mean, a lot of employees are experiencing shortages. So when I tell people in advance to get prepared, and then I ask them to back into it. So now that we know, or have a sense of what's happening in the next five to 10 years, so now, let's dial it back and let's look how technology is going to impact the work that you do, your profession and how it's impacting your industry. 

And so we just drill it all the way down. And what I do is I allow them to use ChatGPT. And I say, well, let's play with Chat and let's just see. Because guess what? I'm not going to give you homework that you got to go try to figure out the answer to these questions. We can get answers to them immediately. And then that within itself gives people a different perspective of, OK, so now we can put together a game plan. 

So people are feeling more confident. Also with the resume writing, people are looking at ways that they can enhance their resume with the right words, the right phrases, qualitative information, quantitative information. And so they're no longer just waiting on a resume writer to do that for them, because sometimes, the opportunity comes from you networking. And you may have a very short window. Or you may be limited in terms of financial resources that you can't necessarily pay for that kind of support. 
So I think when people start to envision these tools in a way that it's not just specifically for work, but it also can enhance your personal and professional development, I think it'll be a whole different kind of relationship as they move forward with it. 

Jill Finlayson: And Chalenge, sort of a flip side of that question for you, how are job descriptions changing? What are new roles that are coming up? 

Chalenge Masekera: Vaneese mentioned a great point, which is as any new technology, especially if it's, like, transformative comes, there's always a reshifting, reskilling, and some people will get upskilled. And I would be lying if I say there's not going to be jobs that are going to be lost because of gen AI. I think we've already seen that. But there's also new roles that are also coming up. I think one of the sort of fun ones that I kind of like is what's called a prompt engineer. 

There are specific focus is like interacting with the generative AIs and predicting what people ask them. So somebody's job is, like, questions that somebody is going to ask ChatGPT or any other chatbot. And we've already seen sort of a explosion of those roles. There's also now people who are in charge of the basic stuff like AI safety. How do we put a wire fence like AI so that it can be safe and be used? What are the legal implications? What are the cultural implications of AI? 

So there's always something new that evolves from how any new technology that's coming. And for people who are like me, you become an AI engineer. 

Vaneese Johnson: What I'll add to that too, Jill, and Chalenge, on that is that even though we see AI kind of opening the door for more tactile skills, it's also going to create an opportunity for people to really become human centric, because AI can't really interact with you human to human. It can only give you some suggestions. So this is going to be an opportunity from a leadership perspective for leaders to fine tune their interpersonal skills. It's going to be an opportunity for individuals, professionals, to enhance their emotional intelligence skills, and an opportunity to enhance their communication skills. 

So there's the hard and there's the soft. And I think it's going to be important to understand that it's a marriage between the two so that one isn't lost on the other. But again, they are collaborating to enhance this person personally as well as professionally. 

Jill Finlayson: I like that balance of gaining more technical skills, but also gaining more human skills, and more leadership, and communication skills. I think we do need a blending of the both. Do we have to go back to school to get these skills? Or is there some other way? 

Vaneese Johnson: So there's a couple of things that employers can do. So one of the things employers can do to help in the environment, because this is-- work is where we spend the most of our time, right? When you get off work, I mean, let's be honest. Who's going home to say, ooh, I can't wait to get home to learn more about ChatGPT? 

But what employers can do is to start creating AI learning environments, where there's training that's happening for employees to become more familiarized with the tool, and more specifically, how they can use this tool to enhance their productivity, and as Chalenge mentioned before, to give them time back. I think approaching it from the give yourself time back is more of a game changer than it is to approach it and say, you need to learn this tool. 

Jill Finlayson: Yeah, I think you're hinting at a brilliant idea. And I don't know if anybody's doing this, but if there was peer-to-peer coaching, like if you're in an accounting role, here's what other accountants are doing. If you're in a administrative role, here's what other administrators are doing. I feel like the people who have figured it out should tell the other people. 

Vaneese Johnson: Yeah, that's going to be important as peer-to-peer mentoring internally. So you've got training for more of the technical skills, the hard skills. And then there is peer-to-peer opportunity for training. And then there's application training, where individuals get to actually go and apply what they're learning in that peer-to-peer connection, and also what they're learning in training. 

But I think it needs to become normalized language when it comes to work performance, and use it from a perspective of enhancing the output of work as well as saving time. Also, it's a way to invite individuals who have been less prone to be creative, less prone to be innovative in their role. I think it will invite and create an opportunity for those individuals to play a little bit. 

And I think it'll make it more acceptable to be able to come to projects and meetings, and saying, hey. Here are a few different scenarios that we could possibly look at. Or, here's a different way to interpret the data with these different models that we're doing sales or client relationship management. So I think there's still a really great opportunity to create the environment that's important to allow us to thrive. 

Jill Finlayson: Almost a bottom-up model of people solving the problems that they need to solve, and then telling the administration, this is how we're going to do it. 

Vaneese Johnson: Yeah, yeah. And I think the administration will be open to embracing, because the administration still is leading. The administration is really looking at data analytics. The administration is really looking at technological tools to enhance the way that it does business. So it cannot do everything. 

And so if you're more on the ground floor, if you have more high-touch customer service type of positions, or you have more high-touch type of work across the organization, or if you're working with global partners, again, this can just enhance the output and the productivity. And the person that's doing the forward reaching, they can start to feel that much more better about the work that they're doing. 

Jill Finlayson: Chalenge, I feel like you also said you've had to do this because you're in an engineering environment. So you've needed to adopt these technologies. Is there something that we can learn from the software side of the house about continuous learning? And how have you been allowing people to test and try new things? 

Chalenge Masekera: It is my bias because I work in tech, and we are always trying to-- at least the way I wear my head is we're always trying to be the cool ones, trying to be ahead of the curve. I think, but one of the things, I don't know if many people about which Vaneese mentioned, is at least in all the places that I've worked so far, we usually do what are called, demos. Sometimes, they're like, oh, this is what I worked on this week. But sometimes, it's just like, oh, I found this really new thing that I've been testing out. And at least in our company, we're super slow. So we kind of have that fun and ability to try out things. 

And our demos nowadays, they set it up all being engineering. But now, it's pretty much everyone across the company. And especially when that first wave of AI came, we're seeing a lot of people, sales people, marketing people was like, hey. This is what I found this week. And I've been using this tool. This is what it did. Like, oh yeah. We were talking about next steps from a sales call. It's like, I was trying to create this marketing image that we want to put on our website. 

And I put it in one of the other AI generative tools. It created all these images. Something that I would normally have taken half the day, it took me a couple of minutes. And I think that sort of way of thinking about things, bringing back the fun to work sometimes, saying, hey, this is what we should be focusing on, or this is what we should be doing. And this is how we can get better at the things that we're doing will help organizations a lot. 

And even as an individual, I remember when I was still in school, well, it didn't happen to me, but I'm sure some people were like, don't use calculators. It was frowned upon that you should not use a calculator. But now, nobody, if you go to school and-- yeah. So I think that sort of mindset of, these are the things that actually provide value to the company, and being able to focus on those, than sticking to, oh, this is the way we've always overrated. 

And also being able to have those open conversations with the management, like, hey. I think we've been doing this. These are the things that we can do better. And these are the AI tools that are coming up, or just like any other tool that we've found that will help us be more productive. 

Jill Finlayson: I want to hashtag that, bring back the fun. How can we make people really feel ownership and be like, hey, I think I found a better way to do this, or I found a new tool to do this better or faster? I think that is part of making organizations, academia, businesses, more innovative is to empower people to try and solve things in new and better ways. I would love to see that adopted by other divisions outside of engineering. 

Chalenge Masekera: Yeah, so it's actually funny. When I was, like, reading through for this, I was going through, I think it's BCG. And one of the points that they were talking about, what are the inhibitors of AI being adopted? It's like, management support. I was like, this is interesting. And I'm pretty sure almost every sort of consulting group, any recommendation for anything they talk about, is always management support. There's always that slide for management support. And I think that's sort of usually where sort of the focus and the problem is. 

And as long as senior leadership doesn't provide a way for lower or middle-level people to embrace new technologies, or just adopt new ideas, it's going to be pretty hard. 

Jill Finlayson: I always have to temper things with a little bit of skepticism. With all this increased productivity, is AI actually making us better? Are we actually getting more free time? Vaneese, what are your thoughts? 

Vaneese Johnson: I will speak for myself. And the answer is yes. I remember pre-AI, pre-chat, that when I-- I am a corporate trainer. That's one of the hats that I wear. And I remember literally having to set aside between six and nine hours to write curriculum for a course. And I literally did that for years. 

And so my brain was trained to it, I made sure that I had nothing else to do, because I was literally going to be all day writing curriculum, and sometimes all night trying to find the right images that conveyed the message, trying to find the right design layout for the slide, researching all of the different articles and papers, all of these things that I was researching because I wanted to make sure that the curriculum is valuable content, and it's rooted in the information that I'm providing, it can support the data. 

And so when I got introduced to ChatGPT, it cut down my time 75% of the time. So now, instead of me spending hours of researching, I can ask Chat and other research tools to bring that information to me quicker, sooner, faster. And then that allowed me to be able to sift through information quicker so that I could zero in and extract exactly what I wanted to share. 

Also, like PowerPoint, PowerPoint has enhanced that software so much with AI tools. So now, instead of me having to figure out how to design a background. So now, PowerPoint can give me different iterations. Even in their own toolkit of imagery, of videos, things that are in action that people like to see movement. So it really has given me some time back. So I literally can go to bed at a normal time of night when I have to deliver-- preparing for curriculum. 

Now, I can just put more time on the front end of talking to the clients. I can spend more time interviewing the participants in the training program so that I can better understand their individual needs and expectations. Now, I can take that and plug it into part of the research process. I couldn't do that before, because I didn't have the time. 

Jill Finlayson: And it gives you a more polished look as well. I remember the days when people would be putting orange and gray together or-- no 18 different fonts. And now, you get the template and it just looks a little bit cleaner as well. 

Vaneese Johnson: Yeah, and then I can look and say, I can put what my outline is into Chat and say, how does this flow? Is it a progressive flow in doing this? So I think it's really important is to look at perhaps some of the mundane areas of a person's job to really see where you're spending most of your time on. And is where you're spending most of your time on things that you really enjoy in the work that you do? How productive does it allow you to really be when you're doing that specific work? 

So I think when we start to treat our careers, you may have heard me say this before. And this is new to Chalenge. But we start treating our careers like a business, and we step back, and we start to take more of an overview of, how are we doing the work we do? 

And then when we also look at the vision that we have for ourselves in the next step in our career journey, I think it allows us to be able to see, OK, what type of tools can I use from AI to help me to get there quicker, sooner, faster, but yet being efficient, and allowing me to really showcase my own professional brand that is of value? I'm not showcasing the brand of AI, but I'm getting to really showcase the brand that I have as a valued contribution to a team.

Jill Finlayson: And are you realizing time savings as well, Chalenge? 

Chalenge Masekera: Yeah, of course, even if I have to say that. But I actually, a good chunk of the work that I do, I think that I'm actually seeing a lot of time savings. Things that used to take me like maybe a day, I can do some of these things now in a couple minutes, because now, what I've been sort of playing with is, like, if you use any of these sort of generative AI models, they have these context windows. 

So I actually have some which have been running for, like, six months. So and I've been kind of training it every time I work on something that's very close to it. So now, there are some things that are like, hey. I want to start working on this and like, can you copy what we did last time, make these few changes? Then I have probably 200 lines that are, like, written. 

Some of it is very boilerplate, but it's still, I would have normally had to do it myself. But then all I now do is what Vaneese said. I just want to start reviewing it. Then I can iterate with it and say, hey. No, make this few changes. And you start having that collaboration. 

So I actually do see a lot of that happening. And I think as the tools become better, it's just going to help me do more things, giving me time back. It's going to be hard. 

Jill Finlayson: So if you're both individually saving a lot of time, why might companies not be seeing it, not rely on AI at this point in time? Is there something that companies are not doing right in terms of using AI? What are you thinking, Vaneese? I see you nodding. 

Vaneese Johnson: What I'm thinking is, the components that scare corporations are policies, ethics. Because right now, without those guardrails in place, a company is like, hands off. We don't know where this is going to go. We don't know how people are going to respond to it. We don't have a way to respond to issues, challenges. We're afraid of lawsuits. 

So I think the best thing that a company can do is to have its leaders first, to really start to become educated on all of the different important facets of how AI would impact a business. I mentioned in our just pre-workshop that I recently took a course at Haas School of Business. And it was AI for Executives. And it was an intensive course for three days where there were 60 of us in the room. And we all got a chance to really collaborate as thought leaders around what we were learning. 

We saw the value of the direction of the future of how AI is going to impact the workforce. But we also saw the value as leaders. How can we start to embrace this tool? And what are important components that will support us in going back and pitching it to our boards, pitching it back to our teams. And I think one of the biggest things that I can say that we learned was that, you can do this in small stages. You don't have to do a complete whole rollout in a short amount of time because the learning curve can be so steep. 

Also, what we learned is that when some companies didn't employ really a rollout strategy, there were penalties. And I think companies are kind of more hampering towards the penalty side versus looking at the value side of that. And then the other part that I'll add is that there are case studies out there already where companies are doing this efficiently. There are municipal organizations that are rolling out AI that we-- of course, we've got the tech side, then we've got the consumer goods side. 

So there are some industries that actually are rolling this out and doing this successfully in different increments. So corporations and leaders need to ask which pieces of these components can we adopt that are in alignment with how we run our business, and alignment of how we serve our customers, and ultimately in alignment with how we want to enhance our workforce. 

Jill Finlayson: Yeah, Chalenge, obviously, we're also talking about a lot of data and privacy. And there's a difference between, obviously, a paid version of ChatGPT and an enterprise version of ChatGPT. What are you seeing that companies need to do to set things up correctly? 

Chalenge Masekera: Like any sort of technology, or partner, or any person you collaborate with, it's generally, it's a question of how well you use the technology. This is, like, what the technology is. Especially if it's coming from the top, we're now having these AI evangelists who are coming to organizations. They don't have to be tech companies, but trying to find those niches, like for our specific organization, what are those things that actually we can adopt these technologies to make our organization to be much more effective. 

And I think that's where it starts is like, before you sort of, like, let's say, all right, let's all start using Copilot, you need to take a step back and say, OK, what exactly do we want to get from it? What are the sort of low-barrier entries that we can actually adopt this technology and be successful? Then the second part is it always matters the quality of the information that you have. So whether you're a person, your experiences, what books you've read, what you've learned. And it's more true for sort of AI with these large language models.

I think inasmuch as I'm a super optimist, I think there's still lots to be done for them in terms of general quality. So to say we're going to replace all our knowledge workers in the short term, yeah, that's completely out of the question. So just sort of to tie the two points is the quality of the model mostly matters. So you have to figure out which ones are very good at adopting, or which ones work well for the specific use case you want to have for your company. ChatGPT may be good for this, but now there's no Gemini from Google. It's very good at other things. 

At least for me, for programming, we have Anthropic. It's better than ChatGPT for that. So I think having that layered way of thinking of, like, this is what we want, what are the skills that our people have? And what are the problems we're trying to have? And then having sort of this exploratory is like, I think we can start with this. Then building onto that, and just exploring the tools that are there. 

Jill Finlayson: I really like that layered way of thinking, and that there are different tools that are better for different needs. So really understanding where this will be adding value as opposed to being a distraction. 

Vaneese Johnson: Jill, I want to add to that that companies also can build their own AI. That's really a value add that I don't think a lot of corporations are really aware, or having the conversations around, because there's a concern about privacy, intellectual capital, trademark information. So that's a huge area that I think it's important to address in this conversation that corporations, they have the power to design AI program that really caters to that specific company, and that business line of that company, and be able to put those guardrails. 

So creating jobs where someone actually is monitoring AI tool, I think that's another important component. And when I say monitoring, not just somebody that's sitting there from 8:00 to 5:00 looking at it, but this needs to be a 24/7 operation, where the person is monitoring that. Also, they have to-- looking at ethics and biases, depending on what is being used, or how this information is being used, and what you're plugging into that information. 

Health care is shifting for all of us. And there's a lot of AI in health care. The good news is that it can make a patient visit more personalized because it learns you. The other side is, how do you protect the data of that patient that you are now providing that customized personal care to? So I do think that companies get to have the conversation with people like Chalenge and others in his field in terms of, how do we build a model that really works for our business and our employees so that when we are giving them some level of freedom and level of autonomy, that they can feel comfortable innovating and being creative? But we as the company, can also have a level of comfort that we have some guardrails in place. 

Chalenge Masekera: Yeah, I think it's one of the sort of tough conversations, especially in tech. Because as a tech person, I think there's always like, let's move fast all the time. And then, deal with the consequences later, which is fun being part of it. But I think there's always, we've just had too many instances of where this technology has actually had really, really bad outcomes. And at least from what I see, I think for the most part, I think anybody building an AI tool, I think that hat is now there. 

We've gone from the wild days of the internet where it was just like, let's build it out and throw it to people. Now, there is some focus. I wouldn't say it's there where it needs to be. But I think having that mental model of, this is what we want for society and, like, what are the ethical and safety implications of our models is becoming forefront. I think the beauty of technology, especially with AI and all these new things, they can reach-- they move fast, but also if they're uncontrolled, they just also spread harm, and at a much faster rate than anything we've seen. 

So I think it's very important. If you are using AI to figure out what are the ethical implications, and also if you're a business that's adopting it, actually making sure this is what-- these are our priorities. And like, will this AI serve us to the fullest of our abilities, and not put us in trouble? 

Jill Finlayson: Yeah, making sure the purpose itself is ethical, and responsible, and then having accountability that I don't think any company sets out to do the wrong thing. But if you aren't monitoring, to Vaneese's point, you could be causing harm. And I think there is a greater push on accountability for the companies that are producing these. 

Vaneese Johnson: Yeah. Yeah, you cannot implement a program, an AI program, institute that in an organization, without having discussions of ethics. You can't have that security. They have to be at the table of the conversation. 

Jill Finlayson: Well, can I turn to a more mundane question? With AI autocorrecting, finishing our sentences, predicting what we're going to say, I worry about the sea of sameness, everything starting to be very generic and one size fits all. And I don't think it one size fits all. So what are some of the downsides to using AI? And how do we avoid them? 

Vaneese Johnson: I'll say my experience on this. And I know Chalenge has got the engineering side of this. My experience on this is the more that I have used AI tools, the better it learns my personality, and who I am. So whenever I'm doing prompts for-- I was working on my bio. I was fine tuning my bio for a speaking event that I was speaking at. And I put in what I had paid someone to do for me last year, really great writer. And I asked Chat based on what it has experienced in me over the last year, update my bio, but make sure you're adding my tone, my brand tone, and my brand personality. 

And so it's giving me information back that really reflects words I do say, the energy of the context in which that information is there. And sometimes it's like, wow, that was really good. You really know me. So for me, the more that I'm using these tools, the more that I feel a level of okayness with the output of it. 

The other thing that I'll say is, AI is showing up in other areas of our lives, on our phone. AI will tell you, hey, Vaneese. You normally call Jill on this day at this time. Would you like to call Jill? Sometimes, that might be a bit overwhelming. Like, wait a minute. How did you know I call Jill? Well, I'm using the computer. And so other times, it might be like, oh my goodness. Thank you for reminding me to call Jill. I get in my car. My phone tells me how long it's going to take me to go home, to get to my house. 

And so there are aspects where AI really does bring some value, but I think it's important if we're using these tools, and we're in that continual learning mode, that we are training these tools as much as possible about who we are as the individual. 

And when you put in those prompts in there to really stay away from trying to ask questions, to be like somebody else, to really approach it and use it from a place of personal identity or personal information versus, again, trying to be like somebody else and trying to come up with, being Beyonce's formula. Give me Beyonce's formula. I don't want Beyonce's formula because I can't deliver at that level that Beyonce does. 

Chalenge Masekera: I totally agree with Vaneese. Right now, where we are, like, if you look at AI tools that we have spoken about, like ChatGPT, Gemini, whatever you can think of, there are these one super large language model that's OpenAI hosting their system. But even with that, we're starting to have these contexts where you talk to it, like, oh, you're asking it. It starts to get you. It's still this model, but we're going to get to a point where these are all going to become commodities. 

If you look at your phone with an iPhone or whatever, if you look at how you type, I type, I'm from Zimbabwe. So we have another language. So when I talk to my friends back home, I use like what we call Shonglish, which is a combination of Shona and English. So some words are half English, half Shona. The first time I type it, it'll autocorrect me. It's like, what are you trying to say? I keep doing it, and after a while, actually, if I misspell those Shonglish words, it will actually correct them. 

We're going to get to a point where everybody's going to have their own personal AI, which actually understands them pretty well, either on your iPhone or whatever the next generation of the technology that we're going to be interacting with in your pocket, or whatever, that understands you and knows as much as you, or even sometimes [INAUDIBLE] better than you that we're going to use. 

But however, I think when you interact with it for the first time, yeah, there is that sort of lack of novelty that you find when you interact with somebody. If I talk to Vaneese for the first time, I'm going to get Vaneese's personality. But if you talk to all these AIs, if I just ask for something, like especially, sometimes I play this game where I just, somebody text me, then I go to ChatGPT and say, can you respond to this? And I'm pretty sure I'm going to know what it's going to say. 

We're going to-- initially, there's going to be some loss of it. But I think interact with it a lot more. It's going to get more customized, and then more personal. 

Jill Finlayson: I like that. And I like the fact that it will get better at helping you, because it'll be doing it more like you as a person. But I also put my shoe on the other foot, as it were, and say, OK, people are applying for jobs. They're applying for awards, or grants, and they're no longer writing those. They're writing the first draft, they're instructing the AI, but the AI is churning out an essay. How does this affect the people who are trying to choose the people to let into a program, or into a college, or into an award? How did they assess this program that has really not necessarily been written by the individual themselves? 

Vaneese Johnson: Yeah, I think this is an important question, because I know that the red flags were raised, especially in the academia environment about people submitting papers that are not really their papers. And we also heard that infamous case where the lawyer was there doing an argument and he presented an argument, but it wasn't really real. It was AI generated. But I think what's still important in that component is the human-centric connection. 

I still think there's an opportunity for whomever the person is submitting any type of documents to, especially when it comes to something that's kind of personalized in a way, I'll speak on both fronts, career and business, is to interview that person. Because you're going to be able to tell right away. Whenever someone gives you a resume, and the resume looks amazing, and you start interviewing that person, you have two options. Either you realize the person wrote this content, or you realize the person did not write this content. 

So I think those components still will be an important factor that whomever is on the receiving end, that they get to take it a step further. As a teacher and instructor myself, I know the personality of the students that I teach. So I can tell. And I recently did this. I introduced ChatGPT to a group of women entrepreneurs that I was training in a 10-week business planning class. 

And when they would submit their homework, Jill, I would give them feedback. I was like, this is a good start, but this is Chat personality all right here. What I need you to do is I need you to rewrite it in your personality. Because I use the tool, I'm able to recognize when something just looks a little too polished, given the fact of where it came from. 

On the other side, when a business is submitting for grants, because there are AI tools out there that will review proposals and help you to write a proposal, you do need to read that proposal and make sure that you're putting the human side, the relatable side, of the people that will be delivering the project, of the organization and the work that it has done, in the field that they are responding to the grant with. You still have to bring that human-centric component into that. 

And if those people reading it on the other end, they know their field. They've seen hundreds of thousands of proposals. They should be able to, and may be able to detect, when something's a little off. But at the end of the day, the human-centric component and connectivity still needs to be a part of that process. 

Chalenge Masekera: When you said it feels a little too polished, you're being generous to all these AI tools. They're mostly too robotic, at least in my experience. And I think if you have used any of these, especially these generative tools, they all kind of sound the same. And you can just tell that this is not written by a person. And I think if you're going to submit that and say, this is my work, anybody who has actually played with it will, a couple sentences in will be like, this is not written by a human. 

At this point, it's easy to tell. They'll get better at some point. But I think, again, like, I think as somebody who's been reviewing stuff, like for a long time, you can tell what's human and what's not. Your client has a presentation, use the tools, the generative AI, to create the content. But then what actually puts you over the hump is your personality, your experiences, which none of these generative models have. 

What makes us special or better than other people, sort of different, is our individual experiences, the way we talk, the way we sort of craft-- Well, it may be at some point, but that human element is what you're going to lose when you just submit AI-written stuff.

Jill Finlayson: Yeah, so you have to give it this specific story, the personal story, and say, incorporate this personal story into my essay, into my answer. 

Vaneese Johnson: I'm applying for TEDx stages. And so you have to submit the application, you have to submit short form bio, you've got to submit a synopsis of what your talk is without it being the talk. Then you have to fill out the application, and you have to make sure that things aren't repetitive. So there were times my coach and I, my coach is a communications professor. So there were times when she went in, and I sent her this, and then she tweeted with AI, and then gave it back to me. 
And I'm like, that doesn't sound like me. This line here, let me change this line here. But 80% of it sounds like me. And so being able to do that. But at the end, I also had to submit a 60-second video. So not only am I submitting you paperwork, but I'm also showing you my personality within that 60-second window. 

And what I asked Chat to do was to narrow down, give me so many words. And I had to narrow down the time to 60 seconds. Chat couldn't narrow it down to 60 seconds on the dot, because I needed to bring the human part to be able to do that. And then as I trial and error, I was able to cut out words, and then give it prompts to help me to really negotiate what I was saying, and what needed to come out. 

So those things are really important. When you look at using them in tandem, I felt like a stronger candidate. I was very proud of myself that I was able to create now a model that I can go and apply with other stages. But by no means do I want Chat to be 100% all of my data, because I'm going to show up. And they're going to be like, you're the boldness coach? I don't see any of that on the paper here. You are not bold, lady. Next. 

Jill Finlayson: Well, I like the personality side. It kind of ties back to what you said earlier about the soft skills, or essential skills, that you need to develop. And I was thinking about the fact that just working with ChatGPT means you have to ask better questions. You have to do critical thinking. You have to analyze what you get back. What are some of the other skills that you think you need to develop to use AI effectively? Chalenge, what have you seen that has been helpful in adopting these technologies, but also skills you had to develop? 

Chalenge Masekera: I think it sort of, like, ties all the skills that I've learned before. I wouldn't say, like, I've rediscovered how I think. One of the things that I sort of had to do back is, always take beginner's mindset as in, like, start from, OK, this is something that I haven't adopted and I've never used before. How do I now try and incorporate it more into how I work? So I started from where I was like, oh, I need help for, like, troubleshooting, to I actually have no idea what I want to do. 

And maybe, just let's brainstorm together. I just have this random thoughts. I'm trying to do this. Then I start from there. I wouldn't say there's more of new skills that I had to adopt. I think it's just trying to put all the skills that you had, just like adopting it and treating it like a beginner's mindset. 

Jill Finlayson: You know that famous garbage in, garbage out? If you put bad information into AI, you get bad information out. There's a new website called gozigzag, which allows you to create a business plan, Lean Canvas, over two seconds. And the only thing it asks you for is a prompt to describe the problem and solution that you're working on. But depending on how good that little prompt is, you're going to get a much better or worse Lean Canvas model from it. Vaneese, what have you seen that has changed how you think about AI? 

Vaneese Johnson: You said it earlier, Jill, at the top of this question, is critical thinking. It's really challenged me to think and ask better questions. And you can tell if your question is not as deep as it could be based on the output of it. And you're like, no, no, no. This is what I mean. So that critical thinking component is really important. It's also helped me to enhance my data literacy in terms of interpreting the data into the story. What is this data really telling me? Do I like the story? Do I need more data to create a different narrative? 

Do I need to have multiple narratives? And so it's really challenging me to learn that. The other component is that AI is challenging me, we mentioned earlier about lifelong learning, is to really look at micro learning. A lot of my clients now, they're asking for micro training. So I've done a whole library now on micro learning is because people really now are looking at, how do I learn something quicker, sooner, faster, and then go apply it, and then make the adjustments along the way? 

Jill Finlayson: I think one of the challenges is that quicker, better, faster that some people, AI can be perceived as the lazy, or the shortcut, or the quick way to get to an answer. But in fact, you have to be very critical of what comes out. You have to change it. You have to re ask your question. And so my concern is people who take the first answer that they get and don't do the evolution. 

Vaneese Johnson: I don't recommend doing the first answer. I always, and I practiced this with my students. And I always tell them, that's a good start. But let's really look and see, what did it give you? Because a lot of times, what I was experiencing was, they would say, it's not giving me a better answer. And it's like, OK, so what that means is we need to ask better questions? But let's really think about, what is it that you really need to know in order to move forward to a next step? And sometimes, I don't know what that is. 

OK, well, let's start at the impact, then. What is the impact that you're expecting this to do? And then let's work back that way. What I found was that developing those critical thinking skills and approaching it from different perspectives can help you to form better questions so that now, you can be able to weigh the output that you are receiving as to what's better. 

And then what I discovered, too, is that when people ask better questions, and we're more applying more critical thinking, they felt better about using AI. The next time, they're like, OK, so now I know I need to ask a better question. So now, they start training the model. 

Chalenge Masekera: You're absolutely in terms of critical thinking. Previously, sort of the evolution of this is like, we used to have Google, then you have, like, seven links. Then you go through each one of them and try and find the answer. But now, you have this very specific answer, which if you can't process the information, analyze, and think critically, you never know if it's the right answer. If you're just going to take it as is, it's not going to be super useful for you. You're going to actually be led on the wrong path. 

The fun exercise to do sometimes is, like, ask any of these AI agents, like, hey. What do you think about this? Or like, can you give me an answer for this? And then you tell it, it's wrong. It'll confirm to you that it was wrong. 

Jill Finlayson: I had a really interesting experience with AI trying to ask it to create an image. I just wanted an image of a person being interviewed by a robot. And of course, the first image was a white male. And I'm like, no, no. I would like to have this be a woman of color. And it gives me this glamorous person. I'm like, no, a normal. And the AI is responding back to me, oh, I see what you mean. Oh, you want this person to be professionally dressed. Oh, I see. 

And the odd thing was that the robot became feminine when I asked for a woman interviewee. And I'm like, why did the robot become a woman? And the AI was like, oh, I'm sorry. Here's the one with a generic robot. So there's all of these things that happen that if you're not asking questions, you could be getting very stereotypical, or biased, or incorrect information. 

Vaneese Johnson: Yeah. Yeah. And I like the fact, Jill, that you kept giving it more prompts in terms of, and you kept fine tuning it, and narrowing it down. I think that's really important, especially from a new user, is to understand that you need to train the model to help you to get to where you're ultimately trying to go, and not to sit back and say, see? This is biased. I don't like using that. That's why I don't use AI, because it'll give you these kind of answers. 

Well, let's really look at, how are we applying critical thinking to the prompts that we're putting into there? So I'm just glad that you shared that example so that people know that, don't stop. Don't give up on it. Continually prime it. Prompt it correctly with critical thinking so it can give you back more closely-related to what your expectations are. 

Jill Finlayson: And Chalenge, did you see we could tell it it was wrong and give it corrections? 

Chalenge Masekera: Yes, you can give it a correct wrong answer and it will agree with you. 

Vaneese Johnson: I love that. 

Chalenge Masekera: That's how sophisticated the technology is. 

Jill Finlayson: Amazing. Well, as we think about now the future, so we're coming up to 2025, what do you think is going to happen in 2025? We saw a lot more adoption in 2024. How is 2025 going to be different? Chalenge? 

Chalenge Masekera: I'm not so sure, actually. I've thought about this. I think we're at a stage where-- there are some people who argue that we've sort of reached the limit, or we're close to the limit, of this phase of AI, like these new language learning models. So I'm not so sure how much we're going to progress. But what I think I'm going to see, I think over the past year, I've actually been seeing people adopt AI, and in very specific use cases. And those use cases have become really well polished. 

We're in the 50, 60% correct. We're going to get to maybe the 70s. So I think we're going to get more tailored use cases, and of how people use technologies in their roles. I think it's going to get better at the things that it's currently good at, things that are generating text, things like generating videos, helping you polish, come up with plans. 

For me, what I see is the biggest use case is having these automated AI-powered human workers, specifically for industries like service, where you're like, you just want to say, I didn't get my Amazon package. Instead of having humans in the loop, I think we're going to see a lot of more software companies adopting AI-powered agents for that. 

Vaneese Johnson: Yeah, I agree in that too. We're seeing that now, I think what I'm seeing just from the consumer end is that the chat bots and some of these companies are more sophisticated. Before, the chatbot would give you some real kind of simple stuff. Now the chatbot asks you really specific information like, what's your account number? What's your address? So it collects the data of who you are, and the interaction with that company, with that brand. 

And it's able to tailor more towards responding to you around a specific thing versus something general. So I'm seeing that now. I think also, what we're going to see in 2025 are more technological tools that have AI embedded in its use. I mean, Apple has the new phone out that has AI in the phone. So I think consumers now are going to find themselves, professionals and that consumer spot, are going to find themselves interacting and using these tools more from a thoughtless perspective so that they can start to develop levels of comfortability in using the tool. 

I also think that those individuals in the professional sectors who want to advance, I think they're going to find themselves really taking it upon themselves to play with these tools when it comes to career coaching, when it comes to resume writing, when it comes to interview prep, when it comes to research on target clients that they want to work with. I see people now starting to say, hey. It's been around for a while. They were right. It's not going anywhere. So I'm going to really look at how I can start kind of taking bite sizes out of this technology, and start to make it work for me. 

Jill Finlayson: Yeah, I think you both hit on a couple of things, these really tailored use cases where things will be optimized for particular uses, as well as the integration. It'll just be part of the tools, like we've seen with Zoom transcription or these other functions where it's just part of how you do business. 

And we will see it less and less, but it'll be there more and more. So as we think about this new world where it's going to be much more embedded in how we do our work, what are your final words of advice to people as we enter this new year? And what can they do to prepare, and take advantage of it, and really grow? 

Vaneese Johnson: Start really recognizing how you're using it in your everyday life. That's number one. You're already using it in your everyday life. Become comfortable with it, because when you're using it from your home, it doesn't have the same pressure. When you are programming your new TV, when you are programming your new phone that you're going to buy, when you're buying that new vehicle with all the technology in it, start using it on a personal level. So that way, you're not feeling the pressure of it. 

The other part that I'll say from a professional development side, I think it's really important for the individual to take ownership of your career, really start looking at ways to reskill or upskill what you have. Reskill is you're learning a new skill that may be in alignment with the next direction that your career is going. Upskilling may be, how do you do the current job more efficiently? 

So start taking ownership of that, and don't wait for a major change to happen in the organization where you are forced to adopt to using this tool, but you can better kind of manage and assimilate with the change, because it is coming and it's happening. And it's not the employer's responsibility to make sure that your skills are up to par. You have to own that and treat it like a business. 

Jill Finlayson: So start using ChatGPT for your gift guide recommendations for your trip, travel, whatever you need to do for the holidays? 

Vaneese Johnson: Exactly. Because I think when you play with it, Jill, you'll start to say, wait a minute. It's giving me gift guide and vacation? Well, let me see what it can do for my career. What's the best time to take off? What's the best way to save money for the trip? So I think it'll breadcrumb you to where you will create more curiosity. And you'll find yourself using it for information that you didn't even plan on using it for. And I think you can discover the value in that way. 

Jill Finlayson: And what breadcrumbs are you following, Chalenge? What advice do you have for folks? 

Chalenge Masekera: Yeah, I think I would just, like, add a few more breadcrumbs there. But I think I really love what you said. Your careers should be treated as a business. And I think every business, what do businesses do? They always find ways to be more efficient, how to further improve what they're doing. And I think we have gone away from, AI is going to kill us, AI is going to replace our jobs, with oh, AI is here. We just, it's going to embed in everything we do. 

So just finding those little tidbits of, how can I be better at something that I either don't like or even something that I'm good at, like, how can I be incrementally better by using AI, is the way to go? 

Jill Finlayson: So hashtag #bringbackthefun, and use these things to innovate, and make your job better. Make your job better in 2025. 

Vaneese Johnson: Right. And hashtag #treatyourcareerlikeabusiness. 

Chalenge Masekera: I like that. I love that. 

Jill Finlayson: And with that, I want to thank you both for joining me today. It's been a wonderful conversation. And I hope that everyone listening has enjoyed this latest in a long series of podcasts that we'll be sending your way every month. Please share with friends and colleagues who may be interested in taking this Future of Work journey with us. And make sure to check out extension.berkeley.edu to find a variety of courses to help you thrive in this new working landscape. 

And to see what's coming up at EDGE in Tech, go ahead and visit edge.berkeley.edu. Thanks so much for listening. And we'll be back next month to talk about neurodiversity in the workplace. The Future of Work podcast is hosted by Jill Finlayson, produced by Sarah Benzuly, and edited by Matt DiPietro. 

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