Harnessing the Power of AI to Boost Your Business Strategy with Special Guest Kavita Ganesan
you're listening to stimulus Tech talk a conversation based podcast created by stimulus technologies that covers a range of topics related to business and technology hello welcome to stimulus Tech talk I'm Nathan Whitaker CEO of stimulus Technologies and we're very excited to have our guest Kavita ganasan today she is an AI advisor strategist educator and founder of openness analytics Kavita works with teams across the organizations to help them integrate AI strategically and get meaningful outcomes from any every initiative so just a little bit about more about Kavita she has over 15 years of experience and uh scale to deliver multiple successful AI initiatives for large companies such as eBay 3M GitHub and McMaster Carr as well as smaller organizations she's also helped leaders and practitioners around the world through her blog post coaching sessions and open source tools Kavita holds degrees from prestigious computer science programs specifically a master's degree from the University of Southern California and a PhD from the University of Illinois at Urbana Champaign with a specialization NLP search Technologies and machine learning Kavita has been featured by numerous media Outlets including Forbes CEO World cmsyr Verizon CD times technopedia and Ted magazine so welcome Kavita thank you for having me Linden you're welcome so AI has definitely become a big Topic in the news recently and we've had a couple of sessions on AI and I ran into your book a couple of months ago and was very excited to reach out to you find out a little bit about how businesses are using AI so it sounds like you've had a lot of experience working with companies on integrating AI into their businesses in their business models so tell me a little bit about yourself and kind of your background and what you do more than more than the traditional bio sure um so my uh history with AI goes way back to like 2005 was actually introduced to AI uh during my master's program and um there was more on the academic research side of things so I've done a lot of AI research um and then over the years uh I got my PhD and I was planning to become a research scientist or a professor but that's the time data science as a field really started to take off so if you remember 2011 to 2013 is where the big data um Revolution started to happen so instead of becoming an academic I decided to go and solve a bunch of uh industry problems so that's why I got exposed to 3M Healthcare I work for GitHub and I saw different types of AI problems put a lot of models in production and I learned a lot uh in those years and as I was doing that other companies were approaching me to help them Implement AI in the organization because it's a very it has a very New Concept at that time um so they wanted help on how to integrate AI into their business or come up with AI startups so I got more and more into Consulting roles and I really liked it and now I do a mix of um Consulting training and advisory type of work so I came from the academic side research and now I'm like purely AI for business type of person so it's interesting I mean AI is a very developing field um how is it you know working in a field that's constantly changing and evolving and you know how I mean how does that work and and you're learning because there's no like textbook you're kind of writing it as you go along right yeah so as long as you have the foundational skills building on that skills is not uh hot so um the last few years llm became a really um populating but because I have all this background in AI in NLP and I understand how things work so building on that knowledge was not difficult it just it takes me some time to read some papers um reading through blog posts and just really understanding what it is how it works and how I can use it with my clients and also like going deep and experimenting with things so so the foundation is very critical uh whether you're on the technical side or on the non-technical side so having a breadth of understanding of what AI is would be uh crucial I think okay interesting so I would imagine you know 10 years ago 15 years ago the community that was working on AI was pretty small um not a lot of organizations or researchers that were working on it has it grown quite a bit or is it still a small tight-knit community working on these these problems so I would say on the recent side it's fairly still a small community um it's a the big tech companies those universities and those well-funded AI research Labs but on the industry side I've seen significant growth on people wanting to somehow use AI for something so I even had a client who approached me for AI for storytelling so he wants to integrate it into these courses so that growth has been quite uh significant in the last six months I would say okay and do you see find you know as uh maybe 15 years ago you know it was a big marketing buzzword do you find when working with businesses it you know AI is kind of a buzzword that people want to attach and they're really not doing AI they just want to attach that label on it do you find that all the time so that happens more often than I would like to see um so a lot of people think that they are doing AI but they're just talking about AI uh they're experimenting with things like Chad GPT but they don't really have a I would say a plan on how they're going to come up with the AI product how they're going to evaluate it and how they're going to release it so the product plan is not there they just know that they want to use AI to do a demo I see that all the time especially with AI startups they don't have a product design in place so yeah I see that as a problem but clients who do succeed have a plan on where they're going to use AI so I have a client currently he knows exactly he needs AI in product recommendation systems so that's where I'm helping him develop that solution um so his approach is I have a design I have this area where I need Ai and I'm going to hire the expert to help me with that so he's set himself up for success I feel okay perfect so I yeah that's it's an interesting problem where you know people you know want to jump on the bus and then they're not you know to have some great ideas and tough to implement so I mean you know chat GPT obviously is big in the news um but what other what kind of tools are businesses using because I'm sure they're not developing an AI infrastructure from scratch I mean what what kind of software and tools are companies integrating into their systems um I would say that's a range of products like Amazon has a lot of machine learning tools like AWS transcribe um uh other tools to understand text data so companies are using those type of prepackaged tools and some are developing from scratch because a lot of AI problems don't need chat GPT they need simple steps so all of that still needs to be integrated from scratch uh specific to the to the product needs um and it's not heavy machine learning or anything of that sort but it's still some form of NLT some form of intelligence in the product so it's it's a mix and the newer AI startups are the ones who want to use chat GPT generative AI in some capacity and if you see the blog post or LinkedIn posts that that you may see on in your feed that's typically the researchers putting out tools about uh new generative AI tools or people just curating tools but I don't think those are actually being used in production systems as widely as you think good again back to chat GPT we had a guest on a couple of weeks ago um you know talking about issues of copyright with you know things like chat GPT and I'm sure that's a you know big question is you know copyright intellectual property issues um and you know he mentioned and I think you mentioned it also that using a private stack or private you know machine learning versus you know going to a public database like chat GPT May circumvent some of those issues with intellectual property and and copyright yeah yeah and a lot of companies don't want to deal with that problem like uploading their um things that are proprietary to them to a third-party service and course for startups cost is also a big problem so each call that you make to that API costs you money so just testing and evaluating and then finding integrating and releasing to customers is the costs are going to really add up so that's not something they want to tolerate so if the problem is small enough they just want to build it themselves but perfect so I mean what if it's a business leader not a you know an I.T professional I guess but if it's a CEO or CFO that's evaluating a AI project you know in the small Deb insights business range you know what kind of things do they need to know about AI is it a quick Roi in the investment or is it a long-term investment you know what are what are some gotchas yeah so that box to this one is fine AI opportunities because there may be a hundred different opportunities in your company but some of them may have very marginal benefits from using AI so finding those high impact ones is critical because that will show you where your competitive Advantage is really going to be so let's say um a lot of their problems are in customer service so then you can think about how I can make customer service my competitive advantage and maybe enhance all the workflows in that department with different uh AI solutions that make sense so that's one area but for the long term if you want to be able to repeatedly use Ai and deploy AI systems you have this long-term planning also involved like thinking about your data infrastructure a lot of companies collect data but the data stores are sometimes in Silo sometimes you cannot access the data and all of that become problems when you're actually trying to like build models or even fine-tune existing models you need that data source some companies may not be collecting data as aggressively so they need to think about how to get that in place so then does the um cultural elements so you know a lot of people are fearful of being replaced by Ai and this even happens at the CEO level so I had a CEO approach me and say I'm afraid I'm going to lose my job I'm going to lose my company because of generative AI um so addressing those types of fear and how AI fits into the picture is important like AI is not going to take over your job but it's going to augment can augment your workflow and make you a lot more productive so having these types of conversations is going to be important because it's a mindset shift and you also need to think about how would you upskill your employees so everybody in the company needs to have a general understanding of AI some of the engineers need to get those AI skills because they are the ones who are going to be integrating these Solutions so upskilling existing employees is also a crucial piece so I would say focusing on all of this uh is for the long term but in the short term you also need to know where the opportunities are so you can plan uh you can take these data points and start creating a comprehensive planning can you I would imagine that um you know AI is as you mentioned a product productivity enhancer you know we've seen in the US that uh productivity increases have flatlined in the last few years as we've come out of covid um and that's what I've read you know the biggest advantage of AI is is increasing productivity of employees so does it embrace it can you give us an example maybe of a company that's implemented an AI strategy that has seen an increase in productivity or an increase in in you know Workforce capability yeah if you take the Cricut companies for example if you if it's a fraud detect Ive detection department so they use a lot of AI and they deal with high volumes of transaction and each transaction needs to be flagged for different uh occurrences or um fraud and that in itself just using AI in that workflow significantly uh reduces the need to hire um a lot more employees than they they are really using right now so that is a very good example of how AI can really increase uh productivity because you don't have to manually verify each and every transaction an AI system flags the transaction and maybe a human reviews the transaction and if it's a high confidence flagging then they don't even need to do that it's automatic so the customers then alerted so that's one area where I've seen good use of AI another is in manufacturing defect detection so companies like Seagate they use AI to detect defects in Silicon Vapors now it's very very tedious to detect defects um in Silicon Wafers because it's so microscopic but with the use of AI specifically computer vision it's able to detect those little defects and highlight where those are and then instead of doing this in a matter of days it does it in like an hour or so so imagine the amount of throughput that they're getting from this AI systems and also you don't have to stop the production line as often because things are just it just keeps going on you don't have to stop inspect and then um proceed with the manufacturing process interesting so if a company wanted to start investing in AI what kind of team or you know how to how do you get started because that's I mean that's the scary part for a business is where to invest and how to invest in it so I think the strategy will look different for small businesses versus larger Enterprises uh small business you'll have to look into where you're doing a lot of manual work where your processes can be enhanced so look for opportunities like that and look for tools to augment your workflow it may or may not be AI it could be just software automation but it helps you then why not uh look into using it and evaluate it for a period of time so look for those inefficiencies but for larger Enterprises uh there's a lot more planning involved because the stakes are high so once you deploy an AI system it has to create value for the business otherwise you're losing money in the long run so finding those opportunities is very critical so you want to look for problems complex problems that require human-like decision making and it's also high volume so you want to find really high volume problems where the use of software automation can produce some sort of tangible benefit maybe reduction in time to perform a task or reduction in errors so something tangible something tangible and measurable and also the planning so the this AI type planning is not just um you should not just try to approach it because of AI but it's needed because at some point you may find an AI opportunity and you may want to start looking into using AI systems so that planning has to start now especially on the data side and the cultural side we have to come to terms with AI is going to be within businesses so let's get started perfect um so you have a book I want to talk about your book a little bit sure yeah so what uh you know why would somebody want to read your book what you know how does it help a an executive or a business owner understand it yeah yeah so it starts so my book comes from a place where I'm trying to bridge the gap between the technical world and the non-technical world the CEOs the directors who may not have um much coding experience and I've seen that when there's mismatch expectation on the leadership side AI systems tend to fail not because the models are failing it's because the initiative that's a there's a misunderstanding of what AI system is supposed to do and what is actually doing so I've seen many AI initiatives going sideways because of that so what my book does it starts with the basics it talks about what is AI from a business perspective provides use cases that where you could use Ai and why that makes sense for AI and then it goes into more deeper Concepts like um so how do you plan for AI how do you prepare your organization what are the five preparation pillars so I talk about that in my book and I also talk about how do you find these opportunities so what I spoke about earlier these complex decision-making problems that are high volume so I provide a step-by-step framework on how do you find those opportunities how do you rank and how do you prioritize so I wanted to create something that's uh repeatable um approach so that everyone in the organization can use the same approach and they have a way to collaborate using that approach and finally I talk about uh buildup by considerate considerations and also how to measure AI success and what does that even mean so does it mean model success does it mean just measuring Roi so getting that clear in an executive mindset will help them have better expectations of what AI systems are supposed to do for them so that's so that's what it covers perfect and how I just uh wrote a book my book's coming out in a couple of months and yeah tell me about your process how was it how was it writing the book it's it's interesting writing a technical book for non-technical people I did the same thing so for you yeah what was that like um I would say I spent a lot of time taking the knowledge that was already inside of me and then trying to codify and then running through those uh steps and making sure it works in different cases so kind of like um a test case for programming so you run it through different test cases so I I spent a lot of time developing those uh Frameworks and making sure that they actually uh is something that these are things that I do intuitively without thinking but for somebody else to repeat it I need to make sure it makes sense so the the draft took me around six months the first draft but editing was um took me about a year to do yeah there's a lot of um back and forth and back and forth yeah I had about the same experience I thought oh I'd have it done in about three months and yeah a year and a half later we were you're ready for for publishing so it's it's an interesting process but certainly fun it makes it challenges you it challenges you it clarifies your thinking uh it helps you think about others and how they may be perceiving your message yeah well excellent uh and we'll be sure to include a link to your book uh for those that are listening to the podcast that might be interested in picking up a copy from Amazon or another reseller um so excellent and if somebody you know is interested in Ai and wanted to get a hold of you what's the best way to get in touch yeah uh you can visit my home page kavita-gameason.com or my company website openoffice-analytics.com so these are the two places where you can get a hold of me and you'll also have some three chapters to my book um on those websites okay so what we we really appreciate your time and um hopefully you know those that are listening are looking for strategies to improve their businesses um and I think AI is a great way to increase productivity even if it's solving small issues like I love your example of you know from a customer service aspect or you know analyzing data as they're coming in and be able to you know produce those results so that's I mean businesses need that today especially with it you know trying to find good employees and increasing um you know their productivity without having to increase their workflow Force so that's definitely a great great strategy to move forward with this so again thank you so much for your time I appreciate it and we'll make sure we include those links in the podcast so they can find you thanks yeah excellent [Music]
2023-08-21 06:12
