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We Are Now the AI in Business Podcast - An Update From Dan

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We Are Now the AI in Business Podcast - An Update From Dan

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I'm going to be breaking down why we're changing the name. What's been new with us here at emerge and what's coming up to give you a little bit of a preview of where we're headed wanted to be able to serve do justice to our longtime listeners and give a sense of where we're going and how their feedback has played into Where we're design a focus. Things moving forward so I'll be quick here over the course of the last two to three years. We've seen a lot of growth in the show we went from somewhat middling downloads with Ai. Not being nearly as popular to over the course of the last three years growing upwards of sixty thousand downloads in a given month which for a business show is quite a lot. We don't really attract engineers attract kind of techies. We attract functional business leaders. And it's tough to actually get that critical mass so we're really grateful to have the listeners. We have but we're changing things up a bit. Who served decided so in terms of what you're GONNA learn in this little short session here with me. I'm going to be covering three main topics I serve. Why the Name Change? What's new? What's coming up etc? What's new at emerge so in other words? Serve what we've recently focused on as well as where we're headed in the future. And then lastly we kind of wrap up with getting a little bit of your feedback at the end if you'd like to send some along to me We happened here from our folks where longtime listeners. So we'll talk first about the name change of the program so the show for years now has been called. Ai Industry that's been intended to be a broad name. For sort of any given industry could be banking. It could be manufacturing. It could be whatever the case may be but we find that the term a industry has connotations that time more to heavy industry time more heavy equipment etc now we have plenty of listeners from financial services that's our main sector banking insurance investing wealth management. The these are the folks that listened to a lot but the connotation would be a look at the show from the outside is that we're GONNA be talking every episode about oil and gas and about trucking and about manufacturing because industry often implies those kind of terms so really. The show is a in business. This is a program for business leaders who do not know how to Code but they need to marshal artificial intelligence to leverage artificial intelligence to drive results in the bottom line. They're not here to learn. Coding they're not here. Learn theory the her to learn about the real precedence of USA and how they can leverage that in their own businesses meant so a in business. We just felt as a more apt name for the show. Some of our listeners agreed and so we decided. Okay we're going to actually do the name change so this is now the AI in business podcast in terms of the actual focus. We're going to keep things the way they've always been in other words. We're going to appeal to business leaders. That could be. Vp's executives managers could even be consultants that are working within the enterprise or mid sized companies. Folks who are leaders of digital transformation leaders of change who need to marshal ai to make a difference in their business so when we talk about topics that's going to mean it's going to be use cases diving into different individual sectors. It's going to be best practices for adopting a I for finding R. Y. OF AI. And it's going to be real stories of actually leveraging the technology within a company and figuring out what's hard what's easy. What are the trends that matter? So if you're interested in use cases discovering basically what's possible and what's working with a across businesses in addition to the best practices for making it work. This is going to be the show tune into. That's been our value prop for a while and I think we're GONNA be doing a better job of at this year's we bring on a really strong cadre of guests in Twenty Twenty. I'm very excited about our guest lineup. In the next two to three months we've got some big names in the in the hopper as well which. I'm sure you'll be hearing about once. There live on the program rather than doing month long themes for I am business. We're going to be doing shorter. Individual episodes about different topics keeping things. Different keeping the variety up. So if we have a bunch of episodes within let's say banking fraud or compliance and we do a lot in financial services here instead of having them all in a row for a month. We'll kind of sprinkle them intermittently amongst other sectors looking at other best practices other trends are other aspects of AI. So we want every week to be a little different a little interesting a different kind of guests different kind of topic. Sue people really get a good S- play of what's happening with artificial intelligence across sectors and how they can leverage themselves so that's another change will be doing moving forward. I think people really liked the variety. That's been the feedback we've gotten and so we're GONNA be doing it better than ever and in fact I think for some of this year we're going to be doing two episodes a week because some of you had asked for that as well in terms of what's new here at emerge so little quick update on what's happened recently and then where we're headed here just as a company just updating you our loyal listeners last year was pretty exciting year for us so a couple of big things happen there. We've increasingly become more involved with the large intergovernmental organizations last year. We presented our research on deep fakes. Some of you familiar with fakes. Basically taking somebody's face making them say or do something that they never did using artificial intelligence to programmatic generate. Someone's face moving or someone's voice. We presented our research on deep fakes at the headquarters of the United Nations last year presented some of their counterterrorism events as well and presented our research on a in the life sciences sector for the OECD down in Mexico City. In addition to presenting an Interpol World Interpol world is the largest police in law enforcement. Serve event for the international community. It's run by Interpol which is the intergovernmental policing organization. We presented our works on deep fakes. They are as well. In addition to that we've continued to focus on our research work with enterprise so last year was year of really seeing kick up. A lot of that work has been with big banks with multibillion dollar insurance companies with players and financial services but some of it has been in other sectors in professional services in life sciences and other sectors as well the commonality is working with businesses. Who essentially are aiming to make better fruitful use of artificial intelligence in their company and they need to know the current precedence of. Roi Within the field. And that's essentially where our research comes in so this year were served doubling down on what we've been called upon not only speaking at presentations but for our client work in the past. Let's say eighteen months and really focusing their so. We've titled Our what was previously called our AI capability map research. We've we've titled our AI. Opportunity Landscape Research. We've improved the process. We've broadened out what we look at and really the focus is three things so when you think to yourself what has emerged do ultimately what we do is three things we help. Companies develop or validate a winning strategy. We help companies pick the right high. Roi Projects of finding low hanging fruit. That's going to be a win. And we help. Companies pick the right vendor for their particular needs. This is essentially where our work comes in and some of you have already seen the video. You can actually go to E. M. E. R. J. DOT COM Slash A. O. L. That's a opportunity landscape so emerged. Dot Com slash. Ai Aol you can watch a two minute video on what? Our research process is with this sort of updated process. Actually looks like in terms of the research deliverable you can see that emerged. Dot Com slash. Aol But the basic gist here is. We're taking really what our strengths are in. Our strengths are mapping the vendor use cases of AI within a given sector of the total vendor use case could be companies in Europe and the United States etc and looking at their various capabilities. And then doing the same thing with the enterprise. Let's say we're talking about insurance looking at Geiko looking at all state looking at the global top. Fifty insurance providers. Asa and mapping where they're a investments are mapping they're known use cases these level of traction of their various use cases and being able to use both of those sets of data that is to say the startup landscape and the enterprise landscape to find. Where is the evidence of our? Why where are the ease of deployment in terms of AI? Applications with our own proprietary scores? Here it emerged. That's exactly what we do. We look across both landscapes. Look at all the vendor providers. All the enterprise folks and get a sense of where is their current adoption now. Where's the evidence opportunity for us to drive our whereas at Roi already happening by really layering data on those key questions of where the Roi is? We can present a visual map to clients and essentially allow them to make smarter decisions. Moving forward advise them in recommend where to go. What COMPANIES TO PICK? What initiatives are going to be quick winds on informing that strategy moving forward? And so. That's the crux of our work against the bulk of last year's work that's why we were called upon by the bigger organizations and that's why we did our work in the private sector this year. Were only doubling down there so many of you already read the content at emerge dot com. Because you wanNA understand what's possible and what's working the Iowa services essentially the very high level version of that it's the version of that that allows companies to truly inform their strategy to back their suppositions with data and to be able to move forward with data back confidence when it comes to where they're investing their dollars and how they're going to compete in the market when it comes to leveraging artificial intelligence