[Music] hello everyone welcome to another episode of tech unhinged today we are joined by Ryan Scott he is the head of product Ai and Innovation at DNA Behavior Ryan is not just any Tech leader he’s the guy who took the unprecedented world of human behavior and thought and threw in a mix of AI and made a sense of it all so with a strong background in software development and a talent for turning data into meaningful insights Ryan is shaping the future of personalization in the workspace and Beyond we are truly excited to dive into his unique perspective on this show today and I also had a chance to meet him personally in Atlanta last year so hello again Ryan Welcome to our show so thank you for having me so how about Ryan you just quickly start off by telling us us and explaining to us basically explaining to our viewers the implications of Behavioral Science in customer and employee experiences and how AI intersects with it and why this combination is so powerful for businesses today we are in the business of helping people understand how people are different and help them understand how best to work together so what motivates people to make specific decisions how they work in the workplace and then from a customer lens how they approach decision- making and the buying process so that we can remove that friction um so if you imagine we’re dealing with massive sets of data because we’re describing people and humans are naturally just very complex um so there’s about 4,000 different behavioral insights that we have in our database so um how do you see uh behavioral insights paired with AI reshaping uh employee and customer experiences in modern organizations yeah so we’ll start with the customer side first because our approaches are very different but on the customer side there was a recent Harvard study that was done and 95% of the decisions that consumers make when they’re in the buy process of a service or a good is all subconscious so that means that people don’t necessarily know their own thought processes and decisions that are actually going on behind the scenes whenever they buy something so a sales and marketing uh expert at at any kind of firm they’re trying to tack this problem is trying to hyper personalize the whole buying experience for somebody and that’s a challenge for them because we’re all expect to do to do stuff more faster better with AI and Technology but if a lot of these insights are HID to them or some subconscious uh for the consumer that’s a difficult challenge to to Really tackle so that’s the key problem that we’re solving with uh on the consumer side the buyer side is revealing these buying decisions that people are having whenever they are in buying a product or service uh revealing those to a sales or marketing team putting those inside of their CRM so that they can see these insights on people um so that they can customize that buying experience so what that looks like is you would use you know a tool like HubSpot um or you know a modern digital marketing platform and we use HubSpot internally so the way it works for us is we have all of our data inside our CRM and when we send people email Mark uh marketing emails we can swap the content out dynamically so so someone that’s more introverted is going to see completely different content in our system versus someone that’s extroverted and we know that we can speed up the process of learning a new solution and uh help ultimately help our sales and marketing process by customizing the way that people absorb information and receive marketing for us so that’s how it works for the customer side now thinking about this from the employee side if you think about all of the interactions that happen for an employee whenever they’re working for a company so the first touch point would be in the hiring process so we can Benchmark specific uh job openings at a company so we know exactly what type of person would fit that role perfectly we use AI in order to automate the process of choosing the right candidate that should fit that role so we have a web app um piece of technology that you can use AI in order to filter out the full list of candidates so let’s say you have 200 people that apply to a job our AI could filter out 180 of those leaving you just 20 and we know that all 20 of those are Behavior we have a whole AI platform that has 10,000 pages of research and text um that have been indexed into it and that system will generate behavioral interview questions um the next you know point of contact for someone is in the hiring process the hiring letter we have a whole AI module that will actually generate all kinds of emails and letters for HR teams to speed up that process um and then whenever they’re on boarding to the team um they can really meet their future co-workers and then imagine if someone’s in the sales or marketing team we then could match up consumers that we know would be suited for working with that salesperson we then can work on the process of of merging the clients and employees together and do rep matching as we call it so we would match up reps with ideal customers so that they’re all working together and that all works more seamlessly so it’s kind of a rundown of how it would work um and there’s just a lot of data that goes behind the scenes just because humans are so complex right right so this is how in organizations you guys on the organization level uh these Solutions are being leveraged so how can leaders themselves being individuals and persons themselves leverage these Technologies to make uh like you know for example you sent uh uh talked about one example where you can match reps with uh specific consumers who are customers who are have a certain personality type so how can other than this use case how can leaders uh leverage this within organizations to um you know uh help team Dynamics and performance yeah that’s a great question so one way that we we’ve really helped firms with is that if you have anybody that’s kind of struggling in a specific area helping the leader understand that not everybody naturally excels at every one specific thing um so a problem that we just helped a particular firm with based in Atlanta is they had someone that was routinely not following procedures as far as entering in notes into their CRM tool now seems rudimentary and the old school way of doing it would be you know the the leader would just thump the table and you know tell them you need to do better you’re not following the instructions um but with the insights that our platform has there’s some people that just naturally are terrible at following procedures and instructions because they get they get bored um so people that are highly creative uh and I’m one of them um we like to do things differently every single time uh that we do it um we don’t like to follow this proven path we get bored with that we like to do things that are new and different kind of explore and learn that way so our system will identify these behaviors um recognize Tas that that someone would be good at and would excel at and other ones that aren’t uh their natural strong suits and then to bridge that Gap um a there’s some things that you can just not assign to one specific person if they’re just not suited for it um entering a notes into a ser M though is something that everybody should be doing um in a firm um so recognizing that that’s that’s actually a modification that we need to have in training uh our AI can actually come up with training notes and coaching notes for the leader so that they can teach the person why it needs to be done a specific way so that they would learn be knowing that they’re highly creative or whatever their trade is um our system will use those insights in order to create a custom coaching path for the leader where working with that person so using that same sort of technique I mean it could be used in any any process in a business just anything that someone is lagging at you know helping the leader identify that um there’s reasonings behind that it’s not just that they’re just not following instructions and are being a you know a rebel so to speak uh there could be more of a behavioral issue that that needs to be explored and uh you know it could be retraining or coaching but if you’re done if it’s done on a behavioral perspective you’re going to get a better output so you know um all that said you know AI is on the rise these days everybody is talking about AI this conversation is also about how uh behavioral data it uh meet matches with the AI and how we can Implement AI in it so there must be some expectations on the customer end as well regarding uh the rise of AI and how it’s going to get implemented in your system especially Behavioral Science what role does it have to play in it and what is it that DNA behavior is doing to meet those expectations in the short run as well as in the long run yeah it’s a great question so going back I think that we don’t always know where technology is going to take us um and I think that that’s where I’ve kind of learned along in my career um one thing that I’ve drawn from that that was a really big inspiration in the way that we built our technology is recently in Atlanta we built a new stadium uh and that stadium was built for a number of purposes we have a um a football team or as we call it soccer here uh an NFL team the Falcons and then we have a lot of concerts that come through um but then also Atlanta is one of the host cities for the 2026 World Cup so this stadium is also going to be um the the the main one of the main uh stadiums that the World Cup is in so when they designed this Stadium they built in a lot of Technology into it but they didn’t 100% know exactly what that technology was going to be used for um they essentially opened up the doors and the protocols inside of the stadium so that future things could be bolted on or added on and that’s really been an inspiration for the design of our own technology is we don’t always know where it’s going to take us uh but I’ve tried to design everything inside of our system so that it’s as flexible as possible um so that ultimately we can add on uh bolt-on upgrades or new modules um to meet the needs of the customer um and that’s just we we can’t really predict what what AI is going to bring us and what technology so being as flexible as possible something that I think every it or a product designer needs to do um but it’s really helped us out at DNA because um you know we we already already you know two years into this build we’re already bolting on uh new elements inside of our system so that sounds all really great Ryan and really promising in terms of what AI can do for us in this field in the future so what do you think would be the biggest challenges in that especially in terms of hyper personalization Solutions uh when you’re scaling it for large scale Enterprises or diverse markets yeah so one of the challenges that we’re constantly having and in this this is I think one that we will always have is that people are bad at adapting to technology they don’t know how to use it some people are good at it but then most people aren’t uh that’s actually a behavioral Insight that we measure at DNA is knowing how well someone will adapt to technology and you know it’s only a third of the population that are really good at it um so if you put a piece of new technology in front of somebody it’s only a third of your users that will actually know how to intuitively use it so building out that change management process so that people understand what’s the intention of this how does it work um a lot of people have a distrust for AI just because they don’t understand it they don’t know how it’s used um you know there’s other elements that are in the media that that influence that that are out of our control so being transparent in how something is developed um showing that it’s reliable the system is fair um you know those are all things that we really try to build into our process um and I think that that’s the only way to go um so we’ve I’ve gone through a whole certification process with Microsoft um and that with AI and that AI certification is almost you know I would say like 40 40% of it is all about the human element um so they have this whole process about um documenting how something transparently works demonstrating that it’s reliable and fair um and all of these elements that really help bridge that Gap and that trust with people um and I think that that’s one of the biggest challenges and something that we’ll always be working on it’s uh really intriguing for me what you just said that you know in organizations people did not know uh much how to use the different technology or different elements of technology so is that sort of a generational thing because I would expect gen Z to have a lot more uh you know grasp into technology rather than you know maybe Millennials or especially Gen X you know we see it we see it across all generations but but the problem is is slightly different so I’ll give you an example um when you’re when you’re building an AI bot um an element of that is really predicting what people are going to ask the AI bot and training the bot so that can give better answers um and a lot of times that works by you know there’s like a exceptions report that’s generated by these AI bots so we developed a weekly meeting internally where we review this exception report and and that essentially is reviewing the questions that people were asking our AI bot uh for which are primarily like support or product related um you see these exceptions where the AI bot had a low confidence level on how well it was able to respond um that and also there is a there’s a voting tool that we have built into the AI bot so if the bot gives a poor answer that someone can give it a thumbs up or thumbs down so they would give a thumbs down in that case if they if they were weren’t happy with the response and we look at all of these um and we also generally know who’s asking the questions because we can see some account data as well aside from it we can’t see the people’s names you know from privacy perspective but we can see some of their um ID codes and things associated with their account so we have an idea of their age um and their background and we see that older people have no idea how to do prompt engineer engineering so they don’t know how to ask the the AI bot um the questions and I think that that that just goes down to like experience of doing like Google searching and and really understanding how to develop a query um older people don’t know how to do that so that’s one of the biggest uh challenges that we have that way but then on the younger gener ations they rely on technology too much so they expected to do stuff that’s completely out of scope and uh outside of the domain that we’re even allow you know or even interested in or even uh confident in our AI bot being being helpful in so they may question ask questions that are more about Behavioral Health rather than Behavioral Science and there’s a huge different difference with that and for a bunch of legal reasons our uh AI bot just avoids any question that’s around Behavioral Health we just can’t go there um but we’re constantly getting challenged by the younger generation of trying to push the barrier on what what the AI bot can do almost trying to expect it to be like a therapist and we’re not going there uh so that kind of goes we see it in both ways you know it’s like people are over relying on it and challenging it in one way and then the other part is like a user uh training element where where they don’t even know how to use it and we’re trying to bridge that Gap so we really have to train the bot uh to be able to adapt to both um and one way that we’ve done that is that if somebody gives a really poor uh engineered prompt so that that would be someone that doesn’t have any skills or experience in using AI um we actually taught our AI to recognize that and then teach the person in their response how to ask the question better um so that’s something that we’ve we’ve built into it we’ve seen some good results um and then also on the other side if someone asked an inappropriate question we just have a very good response that explains what the scope of what the AI bot does um and what it’s intended for uh and that seems to help it on the other side so it’s it’s really all it all comes down to human behavior at the end of the day so it’s a very interesting uh business that we’re in and having all these AI insights as well yeah so you can never get bored exactly there’s plent plenty of work to be done yeah so uh Ryan before uh we wind this up uh I have one last question that I would like you to shed some light on for our viewers so which industry do you think is most right for uh Behavioral Science technology uh use case implementations and what do you think is the impact on Society at large for advancement particularly in this field yeah it’s a great question I see that as like a short-term and a long-term uh type Horizon so shortterm uh the industries that we are best suited for are ones where there’s a heavy High touch between two different people or humans so think about it Financial Services Insurance um you know real estate um anything where you have people that are working with other people a lot of trust needs to be created and a lot a lot of times these people are very busy uh they live a very uh stressful busy life and there’s a lot of regulations in these industries so being able to speed up processes being able to speed up the relationship building um time between those individuals that always helps so I see that as short term and those are the industries that we’re working in right now long term I see this as going you know helping even robots helping them communicate better with people um so we’ve all seen you know how there’s robots that are being developed now and I think that you know 10 20 years down the road we’ll all have a robot in our house and those robots need to have insights on how to communicate to people um you know I think that you know the future long-term care you know uh element that we’ll be dealing with is that rather than having a nurse come and take care of us and um you know clean up after us or feed us or you know whatever kinds of issues that we run into and with our health health as we age I think a robot will be trying to do it um but robots need to be able to pick up on our emotions um communicate to us effectively recognize when we need space train us on how to do new specific things um you know if someone has dementia or some sort of health issue going on um you know that’s it’s all behavior and how you deal with some of these issues so I think that robots actually need to be trained on these insights as well so I think that you know as long as humans are on earth there’s a there’s a element of Behavioral Sciences um and uh it’s going to be really interesting as this uh as this all shapes uh shapes our uh future yeah and this doesn’t seem very far off and trust me the first uh household robot that’s going to come in I’m going to buy that because I really need a robot M 100% I can’t wait I can’t wait to not have to clean a toilet in the future and I’m already looking at robot robotic vacuums um the future is bright it’s very interesting yeah so uh thank you so much Ryan uh for joining us today uh this has been a really informative session for us and um I look forward to connecting with you uh for new insights in the near future as uh you know AI is going to have you build more use cases and uh go into diverse Industries where you’ll have new experiences we would love to hear about them again so thank you absolutely thank you for having me this has been really interesting and I’m happy to share uh so thanks Zara 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