Leveraging AI

146 | The Best AI Training Option For Accelerating AI Adoption in 2025

• Isar Meitis • Season 1 • Episode 146

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What’s the one factor that can make or break your AI implementation strategy?

You’ve invested in cutting-edge technology, fortified your infrastructure, and secured your data. But here’s the reality: if your team isn’t trained effectively, your AI efforts could fall flat.

In this episode of Leveraging AI, Isar Meitis explores the game-changing role of comprehensive AI training in driving successful adoption and measurable ROI. From bridging knowledge gaps to fostering excitement, discover why training is the secret sauce behind every effective AI rollout.

Recommendation: Start with a hands-on workshop. Whether you’re just getting started or looking to accelerate existing efforts, in-depth, tailored training can yield instant, tangible benefits, boosting efficiency and inspiring innovation company-wide.

In this session, you’ll discover:

  • Why most companies fail in their AI implementation—and how to avoid their mistakes.
  • The four proven training formats to meet the needs of any organization.
  • A real-world blueprint for conducting a transformative two-day AI workshop.
  • How hackathons turn training into working AI solutions your team can use immediately.
  • Examples of AI-driven solutions that saved companies hours—or even days—of work.
  • How tailored training builds momentum and excitement for continuous AI adoption.

Isar Meitis is an experienced CEO, AI trainer, and business transformation leader who has scaled and exited multiple companies. With a proven track record of implementing AI solutions across industries, Isar provides practical insights that empower leaders to revolutionize their organizations.

About Leveraging AI

If you’ve enjoyed or benefited from some of the insights of this episode, leave us a five-star review on your favorite podcast platform, and let us know what you learned, found helpful, or liked most about this show!

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Hello and welcome to Leveraging AI, the podcast that shares practical, ethical ways to leverage AI to improve efficiency, grow your business and advance your career. This is Issar Meitis, your host. And today we are going to talk about the most important aspect that will make or break a successful AI implementation in your company or in wherever it is that you're trying to implement AI, and that is training. Many companies that you read about or companies that I meet either when I speak on stages or when I do training myself or in any other scenario, are failing in AI implementation because of lack of proper training. They buy the technology, they do all the infrastructure, they invest in data security and safety, etc., etc. And they assume that people will figure out how to use this technology in the most effective way because it exists. And the reality is it's not like this at all. The way to get your company successfully implementing AI is first and foremost, a change managing process that involves people and involves training people and getting them excited about AI in order for them to A, want to implement it and B, know how to do it effectively. Now, there are many ways to provide AI training to your team, and I've actually recorded an episode about this that was called four ways to train your team on AI. That was episode 86 back in May of this year and a quick reminder and recap and you can obviously go back and listen to the whole episode. But there are four types of training that at least I provide, but they cover roughly the types of training you can provide to your team. One is self paced courses. So people go online, they Sign in and they take whatever lessons in multiple ways in their own pace and time. This is one of the things that we provide under the Multiplai umbrella. I think this is the least effective way, but it is helpful from a time management perspective. If you cannot get your team together for training, number two is cohort based courses. So that's another thing that we have been providing since April of last year. And hundreds of people have taken our AI business transformation course where people just join the course on regular hours, one day a week. In our case, it's two hours a week. On Mondays, this particular course, but we keep on putting out more and more of these courses. This is a great way to train a team and we do private courses for companies. Option number three is online workshops where we tailor specific workshops to specific company needs. And then there's usually one of two types of focuses, either a department focus where it's going to be solutions for sales, for marketing, for HR and so on. And the other focus is the type of AI training that is needed, such as automation or image generation or data analysis or video creation, et cetera. And so these are three of the types of courses that we provide that are not in person. In person. We provide usually two day workshops, which are extremely powerful and effective. And what I want to share with you in this episode is the lessons learned in the impact. from the recent session that I've done just a couple of weeks ago. So the top questions that people have when it comes to AI implementation is, first of all, how do we get started? The second is, Let's assume that they understand that training is the most important thing. How to provide the training? What training is needed? What topics to train on? What should be the means of delivery? And who is going to provide the training? All of those are questions that we're going to answer In this episode. Also, I'll touch one more thing. While this is important in doing a one time session to get everything started, A. I. Is not stopping. It's growing and moving very, very fast, which means you need to figure out for your organization a way to do continuous educational training. On the changes off a I and that's something that will probably do a complete separate episode about. It's something that I help my clients figure out and implement. But for now, let's focus on a two day workshop and why I believe this is the most impactful way to get your AI implementation started. Or if you already started how to get it accelerated and make it significantly more impactful Faster. So the first question is, how do you know what to train your team about? What are the things that they need to know in order to be successful with AI? And what I do is I start with a survey. In the survey, we asked people in the company and in various levels of the company, and I'm going to touch about this in a minute. We're going to ask them about What are the most tedious tasks that they're doing right now? What things that are just routine that they need to do that takes them a lot of time and that they don't find that's the best way they can invest their time or that they could be doing more valuable things instead of doing those tasks. The other thing is, I share with them a very long list of the different types of training that I provide and we ask them, What of those trainings can help the most in their job? And then the third thing is we ask what is their current level of A. I. Implementation and understanding and all of these questions obviously have a lot more details than just these three high level topics. But it's still a very short survey. It takes people 2 to 5 minutes to respond to the survey, and it gives us a lot of information about The kind of training that needs to be tailored for your team and your company. Again, everything I'm going to share with you right now is based on something I've been doing for multiple companies. The recent was two weeks ago for a large us apparel brand that I'm obviously not going to name, but if I would have shared the name, you know, this company very, very well. But before I dive into the results of the survey, I said, there's different teams and there's different kinds of training that you can do for your company because different levels of people in the company needs different kinds of training. Eventually you will have to train all of them. And the sooner you do that, the better. So you need to start all the way at the top with the board. Your board of directors will need to You need to understand what you're doing and what initiatives you are trying to take and why it's going to cost X amount of money or this kind of resources and for them to be able to support your decisions and to help you in the process, they need to understand different things and obviously than the front people who will actually do the work, but you need to train your leadership team because the strategy of the company will most likely change in the light of AI and the kind of competition and opportunity that it generates. So you need to train your leadership team. You need to train your middle management in kind of like both some of the stuff that the leadership, as well as the frontline employees, and then obviously you need to train the frontline employees because they will make the most amount of impact on your business while using this technology. So different kind of training for different people. But let's dive into what happens after the survey. So once we collect the survey, we go and analyze the results from the survey to see what are people struggling with, what is taking a lot of time, what do people consider tedious work, what do they don't like to do in their day to day. What are these tasks are on the critical path of the company and what out of the training that I suggested from the menu they would like to have. And through that in several different conversations with some of the leadership team and some people in middle management, we define what needs to be the training. So in this particular case that happened two weeks ago, and I want to share with you the sessions that we have picked to align with the needs of the company. I always start with an introduction. So the first two hours is always introduction to generative AI, because you never know where people in the company are. And even the people who say they have experience usually don't have the level of depth that is required to start building on top of that. So we always start with introduction to generative But now I'll go through the other sessions. One was data analysis with AI. We're doing both qualitative and quantitative data analysis sessions. Each of them serves a very big percentage of the company because we all analyze data. They specifically asked to also do an Microsoft Copilot in Excel session because most of them use Excel and they have Copilot licenses and they did not know how to use it properly, meaning they're spending money on the licenses and they're not actually gaining any benefits. And specifically in Excel is something they do a lot on. And so that's why they wanted to focus on that. So we added a session specifically about this. Then we did a special session just for a smaller group of people who are more in the data analysis, showing them how to actually bring multiple large language models into Excel and into Google Sheets in order to do qualitative data analysis at scale with Google Sheets. So things like reviewing customer service complaints, like reviewing Customer reviews online and so on. So you can download the database from Amazon if you're selling on Amazon, but now you have 13, 000 reviews. How do you put them in different buckets and categorize them and review them and understand what are the main things? These are things you can do with AI within Excel itself, which you can still use all the Excel functions of ifs and pivot tables and so on. Together with a large language model in the background, but that was a smaller session dedicated just for a small group of people who are more advanced, who would use these kind of things. We did this while the rest of the team were doing exercises and hands on stuff on the things we taught before. Then we went back with the whole team together, and we did market research with AI. How do you learn about your industry, about your business, about your niche, about the economy, about anything you need with AI, and generate reports in multiple ways, either through webpages that are accessible in the intranet of the company, or podcasts that you can share. Or different kinds of summaries and reports that can be shared with relevant people within the organization or your ecosystem. So suppliers, et cetera. And that was a great session that everybody really enjoyed because it's not something they expected AI to be able to help them with. Another thing that a lot of people mentioned that they're struggling with and that they would love help with is creating presentations. So regardless of which role you hold in the company, you create presentations either to report to your higher ups. Or to prevent present things to the people who report to you or in sales presentations, marketing presentations, et cetera. So we did a session about how to create effective presentations with AI. Then in the afternoon, when everybody's a little more tired after lunch and after a long half day of studying, We did the fun stuff, which is creating images and creating videos. And we did two kinds of videos. So some of them are more general videos based on images and prompts. And the other is avatar videos, where you have a spokesperson that can be used for marketing and for training and for customer service and for onboarding of new employees, et cetera, et cetera. We did multiple types of AI video generation. That was the end of the first day. People usually at the end of that, they feel that they're drinking from a fire hose, but it gives them now time to go and digest. We all went to dinner, had more conversations and Q and a, this was after an hour and a half of Q and a between. The workshop and the dinner. So I stayed in that company and a lot of people came over and ask questions about the stuff that we did during the day. The next day we did three different types of training, just to get started. One was mapping business processes. Lots of business processes that only a few people know how to do, and they're not mapped and not documented. So we showed them how they can map business processes with AI. Then we went through how to build custom GPTs, which those of you who don't know what custom GPTs are, these are mini automations that you can build in ChatGPT. There's exactly the same thing, a parallel of that in Microsoft Copilot, and we showed them how to do that as well, so they can stay within the Microsoft environment they work in. We also did a session just for leadership as a breakout session to talk about how they need to start thinking differently about their business in general, about strategy, about competition, and so on. So that concluded the first few hours of the day in the first day, the first few things that I mentioned were done in the first couple of hours of the day and the leadership session was done over lunch when everybody else was doing the hackathon. So what hackathon, that's what we spend most of the second day on. So the second day, after a couple of hours of training, what we do is we ask people for specific use cases that they think they can use with all the knowledge that they gained in the first day. And a few hours, we actually mentioned that upfront. So we tell people to. As they're doing the exercises as we're going through the lessons to take notes and to write down specific things that they can do with the thing that they've learned in order to help themselves with the day to day. And we give them examples that we take from the survey. So we mentioned the stuff in the service, say things like this or that, write them down. And so before the hackathon starts, we actually. Ask people to raise their hands and mention what they wrote down in their notebooks as use cases They would like to work on and then very quickly we vote on those we figure out which are going to be the most impactful And then people gather in groups on the topics that are relevant to them Most of the groups are groups from the different departments of the company So hr people are working together marketing people sales operations, etc But some of the groups are not are unique where people from different departments just want to work on a small project together during the hackathon, and they get together and they do that. In this particular training, we had about 60 people in the training, so we had 12 different groups working on 12 different use cases. These are actual use cases that they are struggling with, that based on the learning in the 24 hours that came before that, they think they can solve with AI and they spend the next three hours working through these use cases where I rotate between the teams and help them figure out how to implement them with different tools and different processes based on my knowledge of information. And what happens afterwards is we get back together and each of the team presents to the rest of the company. What they worked on. And the presentation works in a way where they. Describe the problem. They describe the process that they try to follow. They describe the struggles and the limitations they found in trying to implement it in way one, way two, way three. If they solve the problem, they explain how they solve the problem. They share the outcome and they share the solution. If the outcome was successful, how much time it's going to save them based on how much time it took to do this before they solved this with AI. And again, in this particular case, since we had 12 teams, we had a huge variety of huge case of use cases, which was absolutely fantastic. And I want to share with you some of the use cases that they did in the hackathon. By the way, it was one of the first times that All most that almost all the teams were able to develop a working solution that they can start using immediately. Literally the time that the hackathon ended, they had a tool they can use. So let's talk about some of those things. They are selling through all the large retailers, meaning Amazon, Walmart, Target, et cetera. Through each and every one of them, there are several different channels they're selling in stores, they're selling online and other channels as well, including B2C and other B2B channels, they get data and reports from these distributors. in multiple shapes, sizes, forms, formats, etc. So it's a lot of work for them to understand what's actually going on when it comes to the sales side. The same thing happens A similar thing happens on the logistical side and the back office and supply chain management. They have multiple suppliers around the entire world with warehouses in different places and to understand where different pieces of the product is to put them together and when they show up in. The warehouse and when they need to be shipped in what pallets to which distribution center and so on is very complex because there's no one system that puts it all together. So they spend significant amount of time trying to do data aggregation in an effective way to actually get a real understanding of what's happening in the business right now. So we worked on multiple of these kinds of use cases, both on the backend supply side, as well as on the sales and distribution side, and all the groups that work on these problems were extremely successful. To put things in context, one of the reports they used to work on used to take them multiple days. Some people said 10, some people said eight, some people said 15, but it's a lot of work. And now they have an AI process that within seconds provides. The same kind of report. If you compare that that's nothing short of magic. And if you think about the investment in this kind of training, and it's a big investment, they actually flew people from multiple places to their main office. And so we were, like I said, 60 people training out of them, 35 flowing from other locations, some of them from out of the country, they had to Fly me, provided lunch to everybody and dinner and so on. So it's a big investment. But being able to generate a report that takes a couple of people 10 days to do once a month. And now happens in seconds is already a positive ROI on the entire process, and that was just one use cases one use case. As I mentioned, there were several similar kind of scenarios that they worked on, and all of them were able to generate these new updated fast reports that gives them exactly the data they want in exactly the format they want. Now, in seconds, the shortest thing that it replace is 15 to 20 minutes. Some of them are just a few hours. And as I mentioned, the biggest one, more than a few days to generate these reports. So this is on the data aggregation side. There are also use cases around data analysis, right? Just getting financial information and making sense in it in a faster, more effective way in the format that can help different people in the organization. faster than they can do this before. The other thing that we did is image generation. They sell apparels, so they need images of people and kids wearing their clothing. And to do that, it's always a photo shoot. So we learned how to create a photo. images of the stuff that they're selling on people with training models on the actual clothing that they make and sell. So that was another use case. They're a large company with hundreds of employees, so they're constantly Onboarding people. One of the things they're onboarding for is IT, right? People need to know how to log in, how to generate passwords, how to keep their data safe and so on and so forth. And so there's a person there that is continuously every single week doing onboarding for employees. And he was now able to create at least the first draft of an onboarding training session with an avatar of himself doing the training instead of him. So this is, makes it completely consistent. It can happen in multiple languages because there are people in several different places around the world. Not all of them are English speaking countries lots of barriers that were very time consuming and costly before. Now we're eliminated just with the ability to create these avatar based videos in seconds instead of hours Or in this case in person onboarding. They were able to map their warehouse Processes so something that they've never done before to have a very clear process on how to do different things In the warehouse as something comes in and things need to be shipped out and so on So they were And we even started diving into the next use case, which would have been how to have much better mapping of where everything else, what pallets it's on, which track it's on, and so on. That is now fragmented across multiple platforms. And we already have an idea on how to do the next step. And we're going to talk more about that, about what the next steps after the training is. Now, as I mentioned, while not all of them finished the prototype, most of them did. And even those who didn't were able to figure out what should work if they try other things. And so once the hackathon is over, you either have a working solution, of course, multiple aspects of the business. Or you have a very good start and a path forward, and in addition to the tangible successes of specific tools that are working, it builds an amazing excitement and momentum within the company for AI implementation, literally all the employees were energized to, oh my God, we can do this, we can do that. And you hear people starting talking to one another on different business cases and different ideas that they have where they can use AI in order to solve problems that were not addressed in the hackathon, but that by getting their hands dirty and actually trying things out and understanding how things work, they can now see a path to solve a lot more problems. So When I say it is significantly better than any other means of AI training, it's partially because of that. It gives you tangible solutions and outcomes that you can start using immediately after the training is over. And it builds an amazing level of understanding in a very short amount of time. So within two days, you have a lot of people in the company who know a lot about On multiple AI tools that are relevant to the stuff that they need to implement to help them do their jobs better, faster, cheaper. And it creates a lot of excitement and conversation around AI. And as I mentioned, this is just the starting point, which now you can build on that excitement. You can build on that knowledge and build an internal way or external. You can still keep bringing somebody from the outside, at least in the beginning. to help you build this continuous learning and education and to help you start figuring out how to put strategy around it and how to implement this in a structured way that the entire organization can build and gather around. So what does it mean to you? Well, if you are not in the leadership team in your company, it means Your leadership needs to know and understand this. They need to understand that training is critical. They need to understand that there's people like me out there and it doesn't have to be me, but there's people like me out there who has been providing this kind of training for a while and have a lot of experience. So I've trained companies as small as 20 people. My largest client has. Over 40, 000 employees worldwide and with them I've done both in person and online training because I did not fly to train their APAC sales team as an example, but I did provide training to multiple people around the world over online workshops. And I have done when they got together for specific events. I have done in person training for them as well. So I have the background of doing this in very small companies, in very large companies across multiple industries. And I have my personal background as a CEO of several different businesses that had two exits behind me that were able to scale a few businesses to significant sizes. So all of that obviously helps a lot when it comes to train an entire company on how to do different things with AI. But what I If you are in leadership, what does that mean to you? It means that you need to, first of all, define your training needs. You need to understand the gaps between what you have right now and where you want to be from an AI perspective. If you don't know even how to get started, contact me on LinkedIn or contact me through my website or set up a meeting with me on the Multiplai website and I can definitely help you out with that of how to define the training needs. Once you define the needs you can define the scope of the actual training. What kind of training do you want to provide? What topics you want to cover? How long does it need to be, et cetera? Then define the best delivery method for you. As I mentioned, this could be self based online. This could be cohort based online. This could be in person. This could be many other shapes and forms. And every company, and as I mentioned, every sector of the company. So for your board, you probably want one kind of training that might be different than your leadership team that might be different than the first one. Frontline employees. So every one of them might be a different solution that you need to tailor for their specific needs. And then you need to set up the actual training. And when I said the actual training, it's, as I mentioned, it's either the initial training, or if you started in house and you're struggling, this is an accelerator training on how to get that going, as I mentioned, that could be in person, that could be online, that could be, but there's still arrangements that needs to be made. If it's online, people need. Logins, they need a platform, they need to know how to get in and out. There needs to be some kind of a payment mechanism. All of that is something that you have to take care of. And then after all of that is said and done, you still need to figure out leadership focus around implementation and around ongoing tracking and ongoing training to keep moving as fast as AI is moving. Now I'm sharing all of this with you in December of 2024, because while in 2024, at least the beginning of 2024, it was an option. You could train on AI or you couldn't, and it would have been still fine. If you are not going to get your team trained on how to use AI and start implementing AI in your business in 2025. You'll be in trouble because it is very likely that some or many of your competitors are already doing that if they are doing that it means that their financial structure of their company, the overhead that they have across multiple tasks that are similar to yours, are going to be significantly more competitive than yours. I just gave you several examples before. Where work that used to take a few hours or in some cases a few days now takes seconds. Do that across the entire company and you understand that the level of overhead is going to be different Meaning companies who will do this will be able to have lower prices than they have today Still making more money and being a lot more competitive. So it's not an option anymore. It's an absolute must. And this, what I just shared with you literally gives you the blueprint of the most effective AI training you can do in your company. As I mentioned, you can do this in house, or you can hire me. It doesn't matter, but from something that you need to do, this is A very high priority if you want to stay competitive in this new AI era. If this is something you want to do with me, as I mentioned, easiest thing, reach out to me on LinkedIn or go to the Multiplai AI website, Multiplai is spelled M U L T I P L A I. So instead of Y A I in the end, dot A I. And over there you'll be able to learn about all the different kind of training and consulting that we provide. And also book a time with me if that's something you're interested in. But either way, as I mentioned, it is something you have to figure out how you do. Either still in December, if you're very quick or as early as possible in 2025. As I mentioned before, this is the most critical factor for success in AI implementation. So don't wait and start working on this in your company or in your organization. If you have been listening to this podcast and you've been enjoying it and getting value from it, I would really appreciate it if you rate the podcast on Apple podcasts or Spotify, you can do this very easily by putting up your phone and clicking on the app that you're listening to us right now, and then clicking on the rate or the star level button and rating us. And while you're on the app, if you And while you're on the app, click the share button and share this podcast with other people that you think that can benefit from this kind of knowledge. I would really appreciate it personally. And until next time, have an amazing day.

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