MEDIASCAPE: Insights From Digital Changemakers
Join hosts Joseph Itaya and Anika Jackson as they dive into conversations with leaders and changemakers shaping the future of digital media. Each episode explores the frontier of multimedia, artificial intelligence, marketing, branding, and communication, spotlighting how emerging digital trends and technologies are transforming industries across the globe.
MEDIASCAPE is proudly sponsored by USC Annenberg’s Master of Science in Digital Media Management (MSDMM) program. This online master’s program is designed to prepare practitioners to understand the evolving media landscape, make data-driven and ethical decisions, and build a more equitable future by leading diverse teams with the technical, artistic, analytical, and production skills needed to create engaging content and technologies for the global marketplace. Learn more or apply today at https://dmm.usc.edu.
MEDIASCAPE: Insights From Digital Changemakers
Navigating the Digital Landscape through AI and Custom Solutions with Ariana Smetana
What if your career journey could seamlessly blend the worlds of technology, corporate strategy, and interior design? Ariana Smetana, the dynamic founder and CEO of AccelIQ Digital, shares her fascinating transition from prestigious roles in London and Houston to leading digital transformation efforts. Her unique perspective on technology and AI, sparked by the digital revolution of 2020, offers invaluable insights for any business navigating the digital landscape. Arianna emphasizes how crucial a strong web presence is for overcoming the challenges and seizing the opportunities presented by the digital and AI era.
Imagine revolutionizing the way you consume media and learn through AI. Our discussion reveals how AI is not just about automation but personalizing experiences in entertainment and education. Discover how AI technology, ranging from everyday gadgets to advanced tools like ChatGPT, is being leveraged by industries to refine user content experiences. Insights from our program leader at Kellogg further illuminate how AI applications bridge the gap between theoretical concepts and practical industry solutions, enabling organizations to tackle genuine business challenges with technology as a partner.
Picture a future where AI saves you 30-40% of your work time. We explore how AI's transformative power in the workplace is not just about efficiency but about empowering the workforce with new skills to adapt and thrive. The conversation touches on emerging trends such as edge computing and the necessity of customization in AI tools. We highlight a compelling client success story, showcasing AI's role in streamlining documentation processes, and discuss the advantages of exploring multimodal AI options. By staying informed and adaptable, students, faculty, and professionals can harness AI's ever-evolving capabilities to stay ahead in the digital age.
Is Your Business Ready for Custom AI? Find out here!
This podcast is proudly sponsored by USC Annenberg’s Master of Science in Digital Media Management (MSDMM) program. An online master’s designed to prepare practitioners to understand the evolving media landscape, make data-driven and ethical decisions, and build a more equitable future by leading diverse teams with the technical, artistic, analytical, and production skills needed to create engaging content and technologies for the global marketplace. Learn more or apply today at https://dmm.usc.edu.
Welcome to Mediascape insights from digital changemakers, a speaker series and podcast brought to you by USC Annenberg's Digital Media Management Program. Join us as we unlock the secrets to success in an increasingly digital world.
Speaker 2:I am so thrilled to have somebody I've known for quite a few years, over a decade from my time in Houston. We were both doing very different things at that time in our lives, but we now both find ourselves in this AI world. So, arianna Smetana, you are the founder and CEO of Accel IQ Digital. You have a lot of experience in corporate, in startups, and now you're bringing it to help people understand how do you utilize this new technology. So thank you for being here.
Speaker 3:Well, thank you, Anika. Such a pleasure to talk to you again.
Speaker 2:I'd love to start with your background. What was your history? You know, I know you also you were doing design work and all these beautiful things on the side of all the other businesses that you had and the corporate jobs that you had. So can you talk a little bit about your background, where you started and then how your interest was piqued for each part of your career?
Speaker 3:Sure, well, definitely I don't have a traditional background of career progression that you go through the career progression in one company. I started my career in London with PwC and have economics degree from training and from there when I got to Houston and US, was with the Continental Airlines a couple of years with them, then kind of pivoted into the energy being in Houston. You end up one way or the other working with energy company. I was with Shell Oil for eight years and I was in a different, you know corporate roles that range from, you know, financial to kind of operational and development of their network of gasoline retail stations and then in chemicals business at last.
Speaker 3:And after that I kind of had completely shift in my priorities and focus and went back to school, decided to kind of explore my creative side, went to study interior design and started my first business in very different role and that's kind of when we intersected, working in that field and being definitely more creative and engaged in various organizations in Houston and being, you know, part of the I don't know different world of people who are interested in design. And it's funny, you know, towards the probably 17, 18, I started really exploring technology as was coming into my purview what technology can help companies, and I would start working with the startups who are developing their technology and fast development of the organizations, work with their office spaces, and then I start thinking about my own and I was wondering whether I should venture into developing something that can solve my business problems. And that led me into studying digital transformation, and that was kind of in the opportune time of 2020, when everything became digital.
Speaker 2:Truly, you couldn't have timed it more impeccably.
Speaker 3:It was pretty much, you know, digital experience and learning about digital transformation and from there that really piqued my interest learn from all kinds of aspects. Technology can help businesses. I was really attracted to AI and what it can do. Related to my past experiences. You know business analyst and data analyst as much you know, having a background in economics and statistical analysis. So that was kind of, you know, my pivot and aha moment to get me involved in that and I start my next business and after, you know, probably kind of settled down in 2022, when we all kind of came out back into the kind of office spaces I started working with customers on, you know, digital transformation strategy, ai aspects and from there on, just building it up as I am today.
Speaker 2:Wonderful and I also appreciate that you're a lifelong learner. So you had this great career, you had this amazing skill set, but then you went back to school for creative pursuits and then you wanted to learn more about digital and that ecosystem. And 2020 is really where we saw the digital divide, where we had businesses who were already. They had websites, they understood at least a little bit about technology, and then we had a lot of mom and pop businesses who didn't have websites, or maybe they had one page with no calls to action, no links in no real information, no way to sell their products online and move swiftly. And we still are seeing that now, where maybe more people have, you know, breached that divide.
Speaker 2:But we still have, of course, the AI divide and how to transform your business using new technology, new tools that we all have access to.
Speaker 3:Yep, yep. You know that's certainly being on internet and having your web presence is almost like a crucial thing for any business, and to be more sophisticated would be not only then you have one page documents you know on your website, but needs to be something more engaging, interactive, and I look kind of you know this new generation of software which, like AI and, you know, machine learning, to the extent it's mixed over the same, it's going to take us to a completely different way of working and thinking and I think every person and every business should be really learning about it to the extent they're you know that can apply it and be part of about it, to the extent that can apply it and be part of this big wave of change that is coming. Part of my kind of initiative to work with businesses and bring them that knowledge and move them forward.
Speaker 2:Fantastic, and what types of interactions do you usually have? Do you go in and help a company figure out what they need to do strategically, what systems and processing and operational aspects they need to add in to be prepared and to learn AI? Are you going in and teaching them how to use different tools based on an analysis of what tools they really need? There's a little bit of both, yeah everything.
Speaker 3:Really I'm very tailored towards the need of the customer. So one layer that fundamentally it's good to have is strategic view of you know what this new technology can bring and assessing actually how much of that you need and understanding you know people, how you know your people and resources you have, your processes are, you know, currently stack up and then also you know how this new layer of technology can help you with all of these aspects. And then you know the assessment needs to be where in the whole process between all of these resources, you really need help, where the gaps are, where this technology can maybe provide automation, optimization, some efficiencies in time and way the people work. And then isolating that into the next roadmap to develop those projects and initiative in the organization is what I help them with.
Speaker 2:Yeah, and you actually have your own product, that's a trademark process, excel Insight. So can you talk to us a little bit about that? And then, what are the industries that you primarily focus on?
Speaker 3:Okay, well, after we work with so many different clients, what we see? That often clients have a lot of data and they have them in many different systems, but something really to have a meaningful analysis done. A lot of companies, no matter what system they have, they come and extract the data from the system and then put it into Excel and spreadsheets. There are certain insights or reports from it and in that point that data manipulation and cleaning of the data and collection becomes kind of bottleneck for people who are in data analysis, financial reporting or those kinds of roles, and we thought this will be something that we can easily give them, a tool that can exponentially help them with that process.
Speaker 3:Yes, there are many different tools that you can use using Excel, spreadsheets, using the lookup and many different techniques to collect this data and clean it. Of course, if you're very advanced in code writing, you can do some of that yourself, but not many people are and certainly companies get often subpar analysis done because they spend so much time on the data collection and cleaning versus really producing the insights from it, from the data. So we saw that as a great deal of need and we're building a product which can help them, especially with these data management issues, a product which can help them, especially with these data management issues and then, further down, ability to actually communicate with this data. As we all now know, with the Gen AI and ChatGPT, we want to talk to data. We don't want to be reading and searching and spending hours on that kind of task. So now you can do that, so we enable them to have far sophisticated and faster way of dealing with this type of task.
Speaker 2:Fantastic. And what are the industries that you're working with? Because I know in Houston, obviously we have oil and gas, energy, healthcare, there are some major industries there, but I imagine that a lot of people in those industries can use your service and in Houston, but I'm sure that you also want to work with people outside of that region.
Speaker 3:Yeah, interestingly. Yes, certainly, and of course Houston is pretty much dominant in those industry and we work with those industry as well. But we are a global company, so you know where people are, where the customers are. It's not a barrier Because, again, we are dealing pretty much, you know, remotely with all our projects. Rarely these days we need to be traveling to the premises of the customers. So it's becoming a quite different paradigm when we work with the companies than it was done in the past. Could be industrial, could be actually even technology company. They have hardware and they want to deal with their data on the software side and we can help them develop those components. So really depends, not so much industry specific, more of problem specific.
Speaker 2:That's what we focus on yeah fantastic, specific, more of problem specific that's what we focus on. Yeah fantastic. I've been reading a lot of articles recently about that. Consumers on that side are still wary of AI. If you have an ad for a TV and one says AI powered TV, the other one says new tech TV right, we all know what that means on this side of the equation. But the new tech is going to, you know, it just does something where people are more likely to purchase, and I think there's probably some of that mistrust still within some business sectors as well. So what are some things that we need to do to help businesses understand and overcome or demystify AI?
Speaker 3:Yeah, there is a lot of conversation and there's, unfortunately, a lot of misinformation how the AI is built, how it's used. Certainly, you know, we have the major technology company from Microsoft, google and the like, and OpenAI building the fundamental building blocks of AI and they've been training on this very this type of data, and certainly, you know, we don't know all the insides and outs. How will this develop when we know how we can use that? So this becomes a foundational building block for companies like mine to utilize that and then build something for specific problems and specific companies to use. So now the company needs to really understand how their systems operate, what type of data they work with, and sometimes that can be also a problem because there are a multitude of systems they work with. They're typically data recording systems. Then sometimes they don't even have analytics arm fully developed. So it really depends how they want to utilize that data.
Speaker 3:Data is the kind of you know main ingredients in AI. There is really nothing where that you know it's important in this equation to have the really good data and then to get really good output, and human and you know resources need to be in the chain of this process because they are the main experts so they know what data is valuable and valid for the certain problem. And then I often need to validate the output that is correct and it can be used. We are not at the point that something will be automatically and kind of without supervision done. Yes, of course we are heading that way. Many systems are already in place, but I still think that humans need to be in the loop and validate what we're doing with AI. That will really, the minute you start doing that hands-on experience, that will demystify how AI works.
Speaker 2:Oh, nice, yeah, and are there things that we can do to help businesses change the consumer perception as well? So, because you're working with the strategy, the insights, the data, all the things that we need to build storytelling upon, and then I'm just I know this is a question that I told you, I was going to ask you, but I'm just wondering you know, how then do we get consumers to not be afraid of it, even if they're not touching AI, even just to buy a TV that says AI enabled, or to know that their car has things built in that? Because they actually have been using different recommendation engines, right, different parts of LLMs, and they just don't realize it.
Speaker 3:Correct. We've been using it. You know one example that probably most people know, it's Netflix. You know other one would be LinkedIn as well, but you know maybe not everybody's using LinkedIn but Netflix is probably very prevalent. Everybody's been flicking through the channels and they ask you three questions select you know type of genre you like. You know maybe a couple of movies and based on these kind of data points and you're using of their, you know software and you know, in channels and movies and programming, you actually telling the machine what you like and start learning about your preferences and giving you feedback. Maybe you should watch this, maybe this is something that you would be interested. So those are some tools that are already on, based on AI preferences and it's really providing kind of insights to them, the preferences of people, so they can provide the programming to their customer base and customer have ability to get really customized. You know either marketing or you know products they really want to watch.
Speaker 3:I don't want to be flicking through 2000,. You know names of the movies, thinking which one is for me. If I get you know three to five choices, I'm more happier to know. Oh yes, this movie relates to me because this, this and that topic that I know I appreciate. So I think the value is there. Something is maybe not communicated quite well and you know things are enabled with AI on many different levels. You know cars and TVs, I'm sure soon and many things. You know. The iPhone is coming on with AI. Our laptops in the future will have chips which will process AI applications. So we are there. It's just a matter of jumping in, playing with what you have, even if it's charged GPT, and tested out, and then you're going to really know the power of this amazing tool.
Speaker 2:Thank you for that. I also want to talk about because you went back to school, right? You went to Kellogg at Northwestern to learn more about AI. Once you said, oh, this is something I really want to dig into, and now you are still working with the university. What does that work look like for you?
Speaker 3:Yeah, this was, you know, this year. I started working with them because to me, you know, the professor who was teaching the AI course was phenomenal and I really learned a great deal and also I wanted to give back to the university and so basically they have executive education program, which the program is about AI for growth and working with many different companies around the world and I'm working with them in a role of program leader. Different companies around the world and I'm working with them in a role of program leader, so, as kind of an outside expert, I come in and offer office hours and also my perspective of how I see that this technology is used in the real world and you know how companies are using in different level than what maybe academia is looking at. It's really great combination of you, combination of theoretical applications that are done in a very structured way and then something that you can see in industry that's been using this application.
Speaker 2:Yeah, I appreciate that you bring the two worlds together. Yeah, yeah, because I think that's so important. It's something that a lot of people forget about. Yeah, I want to ask what is one of the biggest aha moments or transformations that you've seen with an organization that you've worked with, either through Accel IQ or through Kellogg, or both?
Speaker 3:What I like about, you know, kellogg approach is, you know, really good foundational thinking that gives you ideas how to approach the problem, especially in the AI realm, and gives you ideas how to approach the problem, especially the AI realm, and gives you good examples. And certainly, like program leader like myself, I can bring real life example to kind of meet theory and practice together. And in my company, you know, the aha moment is actually when you see that whatever we're building and solving in the company works right. And you, of course, you have to keep open mind because it is development process that needs to be fine-tuned and at this point there is a lot of changes happening. But as long as you do that and start that journey of learning and implying and developing and using your own kind of resources to test those things, the results are so much more richer because you have domain knowledge with technology and then solving the real business problems, kind of marrying all of these aspects together.
Speaker 2:Yeah thank you, and is there an average number of hours companies can save by implementing these systems?
Speaker 3:Absolutely, we've seen, you know, definitely. It depends, of course, on the problem and the scale they're going to deploy this solution at. You know, between 30 to 40% time saving.
Speaker 2:Wow.
Speaker 3:Because it's really interesting. You know how much tedious type of work certain roles have and can be eliminated with this type of tool. I don't know if you use yourself. Even just charge a 15-year-old. So creating a marketing content sometimes can be hours of editing, talking, researching. Now you can do that greatly much faster, even if it's just the first draft, with a simple thing accessing ChartGPT or Perplexity or any of the tools which give you this instant in-depth kind of assessment of your topic and then you as an expert, adding your knowledge and layers towards that and I see that in companies as well.
Speaker 3:You know if somebody would do some task that you know. Let's say, you know cleaning up the data for me and then I need to just produce the analysis of it. That saves me hours on end Usually. You know analysts. We've been seeing like six to eight hours can be spent producing a report and you know they. Really you know in time crunch because now you know the management wants to report and takes them three days to produce. Now it can be a day to produce, which is a great deal of saving.
Speaker 2:Which is a great deal of savings. And that takes me to the next question, which is there are still people who are afraid that their jobs are going to go away because of the efficiencies of AI tools. What do you say to a company or to employees at a company who are worried about that?
Speaker 3:So, yes, certainly, you know that is a scary thought because that's kind of been published in media and it's an you know aspect of how this tool could be replacing certain tasks, and there is no question that we'll be changing how the work is done. But now it's the question for the leadership and for the person who is in that role to be proactive and learn the new skills using this AI tool and kind of learning on their own or asking the management. I want to be trained. I want to. There's so many courses, including, you know, like I mentioned with Kellogg, I actually produced my own course on Maven, which is specifically targeting middle management that can learn these tools and see how this is applicable to their role. And to me, if you learn it, you can demonstrate that you're more valuable to your company than not. And then you know that you're more valuable to your company than not, and then you know you're not going to be replaced. You will be promoted when you see that you are the one who is actually solving the problems. It's beautiful.
Speaker 2:You talked a little bit about some things that are going to start having AI integrations, the new iPhone. Our computers will be fully integrated, so we don't have to keep adding different apps here and there. Where else do you see AI going in the future, based on the work that you're doing, right?
Speaker 3:now it's going many different directions. I think that one of the things that of course, the processing often is you collect the data and it needs to be done in data centers, and all of that. Now there will be ability to process this data on edge computing. Like I said, laptops will have the sufficient chips and bandwidth to process something like that, and there will be more and more smaller models coming out that may be applicable to certain use cases to give you enough responsiveness, the way you need it, and maybe accuracy, that you're looking for specific tasks. So it's going to be a variety of things that will be benefiting, I think, industry, benefiting different roles, and then you will have kind of, you know, customizations on top of that. We'll be able to build. That's what we do as well. There are many fundamental models which are coming large, but I think there will be many small ones coming and we will be building applications on top of that.
Speaker 2:Yeah, fantastic and there are so many AI models, and then we see some that are one product, one exact niche. We see some that are built a few and that's what you're talking about is that you have your proprietary system and then you also help build out custom AI tools based on what the company needs.
Speaker 3:Yep, I think you know definitely customization is important and at this point you know there is not one AI that will satisfy every answer, even though you know it's like it. It is Chai. Gpt probably wants to plan that, but I think it's still not going to be serving everybody and anybody because, especially you know that when you serve everybody you're really serving nobody, because never really precise or accurate or really becomes a generic answer size or accurate or you know, really becomes a generic answer.
Speaker 2:Do you have a favorite client story that you would want to share with us Of somebody who got in there and you were able to transform them even more than they ever thought possible and just help further business?
Speaker 3:So you know, yeah, currently working with the you know client who see an internal you know documentation problem. That is very common. That you know there is a an internal you know documentation problem. That is very common. That you know there is a lot of documentation and going through updating all of this documentation, whether you know, disseminating internally or they may even, you know, work with external parties who are working with them in some capacity. So documentation is one phenomenal thing that you can create agents and chatbots and some new interfaces to access this information much more efficiently and accurately as well.
Speaker 3:Because sometimes you know if you have documentation which is pages and pages, people will not read that right, it's not a fun task to do, and then you know they may miss it. It's not a fun task to do and then you know they may miss it. So if you have this interface which can help them do that faster, and you know, with a simple, you know language, that you can ask the machine you know, tell me where's this? Can you explain to me? You know how this relates to. You know this. You know specific case I'm working on. Can you give me a code that is you know? Can you give me a code that is, you know, responding to this problem.
Speaker 3:I have, you know, lots of kind of you know, support functions can be also, you know, automated through these kinds of tools, whether internally or when you have, you know, customer support functions being automated in some way. But you know, again, it's really applicable to specific company and specific needs. So this one is exciting because everybody tries to do that on their own and then they realize they need deeper expertise and then working collaboratively with external experts like ourselves helps them to reach that far better and more accurately than otherwise. Yeah, fantastic.
Speaker 2:Hi, I understand that you have a form people can fill out to see if they're ready for a custom AI tool in their business, so I'll definitely put that link in the show notes. But I also want to know do you want people if we have students who are interested in learning more about what you do should they reach out to you via your website, via your LinkedIn?
Speaker 3:Certainly both LinkedIn. You know I'm very active on the LinkedIn. They can certainly reach out. I'm very closely, you know, affiliated with the Houston Community College and their AI program. They have amazing program now. They even have a four-year degree, also University of Houston. They invited me a couple of times to speak on their, you know, engagements. I'd love to support students and help them anyway and, you know, internships or, you know, just ask questions. That's perfect way to do engage, oh, fantastic.
Speaker 2:Thank you, Ariana. Is there one last piece of wisdom that you'd like to leave with the audience today?
Speaker 3:Well, you know, you and I were kind of talking about that and I was thinking you know what is the piece of advice? And I don't know there are many. Sometimes it's more about thinking about yourself and paying attention that how we're treating ourselves first and you know giving ourselves the oxygen, the food and all of the ingredients we need, and then we are fully able to spread that benefits through our work. Or you know how we approach our, you know friendships and all of that, the relationships to others, right Almost like you know giving oxygen in the case of emergency in the other, the plane. Give yourself first and then help others. So that's kind of one philosophy that it's good to you know. Start with that and spread the joy and help others as well. Fantastic.
Speaker 2:And is there one AI tool? I mean, we talked a lot about ChatGPT. Is there another tool perhaps that you think anybody as a consumer, as a student, as somebody who's just diving into AI, should start trying?
Speaker 3:Well, there are many and these days you know whether it's, you know meta, you know a llama product, whether you know you have Mistral, whether you know you have Plod Grovok, you name it. They all you know kind of specialize in certain things. You know, perplexity is almost like a search engine type of output gives you references, give you kind of deep type of analysis. Chartgpt has many multimodal options. All of them have certain angle they like to kind of serve and develop further than others. Maybe some are more encoding, some are more picture processing, maybe video. Of course there is a lot of media processing which are kind of specialized image processing platforms to work with. I kind of test them all different use cases and different problems I want to solve. I would not stop with any specific one because they all advance and serve different purposes.
Speaker 2:Fantastic. Well, I always love seeing you and I really appreciate your time today telling us a little bit about your journey and a lot about what people need to consider for best use cases in their businesses for AI tools.
Speaker 3:Yes, likewise Annika.
Speaker 2:It was always a pleasure connecting and seeing you and doing a wonderful job, Thank you, and thank you to all of our students and faculty staff and friends of USC who are listening to or watching this episode. I am Annika Jackson. I'm here with Arias Medana for Mediascape Insights from Digital Changemakers.
Speaker 1:To learn more about the Master of Science in Digital Media Management program, visit us on the web at dmmuscedu.
.jpg)
