Latest / Sidecar Sync / AI Agents and Association Strategies: Keynote Highlights from digitalNow 2024 (Day 1) | 63

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AI Agents and Association Strategies: Keynote Highlights from digitalNow 2024 (Day 1) | 63 · Sidecar Sync

• 0:00
  Speaker 1: AI is the worst it is ever going to be, meaning it's going to get better.
• 0:07
  Speaker 1: Better might be subjective, but better means more powerful, and a big part of what's going to happen in the coming years is a gentic system.
• 0:15
  Speaker 1: Welcome to Sidecar.
• 0:19
  Speaker 1: Sync your weekly dose of innovation.
• 0:21
  Speaker 1: If you're looking for the latest news, insights and developments in the association world, especially those driven by artificial intelligence, you're in the right place.
• 0:30
  Speaker 1: We cut through the noise to bring you the most relevant updates, with a keen focus on how AI and other emerging technologies are shaping the future.
• 0:38
  Speaker 1: No fluff, just facts and informed discussions.
• 0:42
  Speaker 1: I'm Amit Nagarajan, Chairman of Blue Cypress, and I'm your host.
• 0:47
  Speaker 2: Hello everyone and welcome back to today's episode of the Sidecar Sync Podcast.
• 0:52
  Speaker 2: My name is Mallory Mejiaz and I'm one of your hosts, along with Amit Nagarajan, and today we have a special edition Sidecar Sync episode lined up for you, where we're going to be sharing some keynote highlights from our annual event, digital.
• 1:06
  Speaker 2: Now, before we kick off today's episode, let's hear a quick word from our sponsor.
• 1:12
  Speaker 3: Introducing the newly revamped AI Learning Hub, your comprehensive library of self-paced courses designed specifically for association professionals.
• 1:21
  Speaker 3: We've just updated all our content with fresh material covering everything from AI prompting and marketing to events, education, data strategy, ai agents and more.
• 1:33
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• 1:44
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• 1:54
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• 2:00
  Speaker 3: Start your AI journey today at learnsidecarglobalcom.
• 2:08
  Speaker 2: If you have tuned in to the Sidecar Sync podcast before today, you have probably heard us talk about Digital Now.
• 2:15
  Speaker 2: Digital Now is a two and a half day conference that Sidecar puts on every year for association leaders.
• 2:20
  Speaker 2: In previous years we've covered topics like blockchain technology, web 3, and, of course, artificial intelligence and, as you can probably imagine, at Digital Now 2024, which we hosted October 27th through the 30th, we talked pretty much exclusively about artificial intelligence and the idea of building an exponential association and how AI is going to redefine what it means to be an association now and well into the future.
• 2:46
  Speaker 2: It was two and a half days.
• 2:48
  Speaker 2: We had nine fantastic keynote speakers and breakout sessions from fantastic presenters within the association space and, of course, we know many listeners and viewers of the Sidecar Sync podcast could not attend, so we wanted to share a piece of that event with you.
• 3:05
  Speaker 2: In today's episode, we'll be hearing some short excerpts from our four keynote speakers on day one of Digital Now.
• 3:11
  Speaker 2: If you want to hear the full length keynotes, they're actually currently in our AI Learning Hub right now, so if you already have access, go check them out, and if you're interested in seeing those full length keynote sessions, I highly encourage you to go to learnsidecarglobalcom Now, while you're listening to today's episode, you might feel inspired and you might decide that you would like to attend Digital Now 2025.
• 3:37
  Speaker 2: So if that's of interest to you, you can go to digitalnowsidecarglobalcom and lock in the early bird registration rate for Digital Now 2025.
• 3:48
  Speaker 2: I should also mention the event is going to be November 2nd through the 5th in Chicago 2025 at the Lowe's Hotel.
• 3:56
  Speaker 2: So right now we're running our early bird special, which is $797 for an individual registration.
• 4:02
  Speaker 2: But really where it gets good is when you want to register four or more individuals.
• 4:07
  Speaker 2: So if you register four or more individuals, you get that registration rate for $625 per person for two and a half day conference and the extra perk on top of that is you're essentially locking in that $625 rate.
• 4:21
  Speaker 2: So if you decide several months from now you know you would really like to bring a couple more people from your team you can still do that outside of the early bird period for $625.
• 4:31
  Speaker 2: So if that's of interest to you while you're listening to this episode, head to digitalnowsidecarglobalcom.
• 4:40
  Speaker 2: You might be familiar with our first keynote speaker.
• 4:44
  Speaker 2: At least if you've listened to any episode of the Sidecar Sync before today, you should be.
• 4:48
  Speaker 2: Our first keynote speaker is Amit Nagarajan, who is a host of the Sidecar Sync podcast as well.
• 4:55
  Speaker 2: We love having Amit kick off Digital Now because he really sets the tone for kind of what's happened the previous year since the prior digital now and then sets the tone for the whole theme of the event every year, so in 2024,.
• 5:10
  Speaker 2: He talks about AI, agents and agentic systems and really speaks about how powerful and essential these systems will be over the next year and well into the future.
• 5:21
  Speaker 2: He lays the groundwork for comparing models to agents.
• 5:25
  Speaker 2: So, with the basic idea being that models don't really adapt over time, he has this really great analogy that you'll hear, where he compares them to a brilliant person who's essentially lost the ability to learn anything new after college, and that's compared to agents, which are a collection of different software components that come together to make a valuable system that can take action autonomously or semi-autonomously and ultimately learn and improve over time.
• 5:51
  Speaker 2: In his keynote session, he shares examples of AI agents from within and outside of the association space in areas like customer service, knowledge and data.
• 6:01
  Speaker 2: So please enjoy this excerpt from our first keynote speaker, amit Nagarajan.
• 6:07
  Speaker 1: All righty, you guys.
• 6:09
  Speaker 1: Excited about AI, yeah, a little bit fearful of it too, I mean.
• 6:14
  Speaker 1: I put my hand up for that, sometimes scared, shitless.
• 6:17
  Speaker 1: Here's the thing AI is the worst it is ever going to be, meaning it's going to get better.
• 6:27
  Speaker 1: Better might be subjective, but better means more powerful, and a big part of what's going to happen in the coming years is agentic systems, which is the point of my talk today.
• 6:37
  Speaker 1: I feel that associations have not been able to really jump on the agent bandwagon quite yet.
• 6:46
  Speaker 1: In the broader world, agents are becoming probably the most popular topic in the world of AI, because they can do things that models themselves can't.
• 6:54
  Speaker 1: That's what I'm going to be talking about today, now.
• 6:56
  Speaker 1: What I want to give you a sense of first, though, is the pace of progress.
• 6:59
  Speaker 1: So every year at Digital Now, it's a nice touchstone.
• 7:03
  Speaker 1: It's an opportunity in our journey together as a community to say well, what's happened?
• 7:07
  Speaker 1: You know what's going on, and it's hard to keep up, right?
• 7:11
  Speaker 1: I mean, I do this stuff.
• 7:12
  Speaker 1: Most of my waking hours I'm spending thinking about artificial intelligence, and it is relentless and it's overwhelming.
• 7:20
  Speaker 1: So it's okay to admit that, I think, and it's really the only reality that exists for all of us.
• 7:24
  Speaker 1: So we's okay to admit that, I think, and it's really the only reality that exists for all of us.
• 7:27
  Speaker 1: So we're going to talk a little bit about that and then I'm going to dive into what exactly are agents.
• 7:28
  Speaker 1: I don't want it to be a mystery.
• 7:29
  Speaker 1: I want it to be clear and simple and understandable, because agents really are just that they're just systems, and we'll get into that.
• 7:36
  Speaker 1: We'll talk through some examples and then we'll talk about how to take action, how you can actually move forward and take advantage of this stuff.
• 7:48
  Speaker 1: So let's begin by taking a quick snapshot of the journey of AI's progression.
• 7:49
  Speaker 1: Remember, the AI you have today is actually really bad.
• 7:53
  Speaker 1: That's the thing that people don't realize is the systems today are kind of dumb.
• 7:57
  Speaker 1: Now, at the same time, they're unbelievable, they're amazing, they're world changing, and both things can be true at the same time.
• 8:04
  Speaker 1: Part of the reason for that is because AI has been moving so incredibly fast that the systems themselves have capabilities that we do not understand, we do not know how to use, and that includes the we being the world, not just associations.
• 8:19
  Speaker 1: A model at least the current architectures of models don't adapt over time.
• 8:24
  Speaker 1: Models don't really learn from the interactions with you.
• 8:27
  Speaker 1: Now that's something that's going to change in the coming years.
• 8:29
  Speaker 1: There's a lot of research happening on forms of these models that will be able to be more adaptive and learn as they go, but right now, the models you interact with themselves don't get smarter.
• 8:40
  Speaker 1: They don't learn from the interactions.
• 8:41
  Speaker 1: They don't remember anything about what you told them, they're just fixed.
• 8:45
  Speaker 1: Think of it this way Imagine as though you hired a brilliant young professional right out of university Pick a university in your mind.
• 8:52
  Speaker 1: That's amazing.
• 8:53
  Speaker 1: And they learned everything 100% perfectly that the university taught them.
• 8:57
  Speaker 1: But once they came to work for you, they were not able to retain anything.
• 9:01
  Speaker 1: You told them they knew all their base knowledge from university, but they learned nothing from their interactions with you.
• 9:07
  Speaker 1: That's what the model architectures are today.
• 9:10
  Speaker 1: So it's kind of limiting right, because it's pretty amazing that they know everything from university or whatever their training set was, but the fact that they cannot go beyond that, it's a bit of a challenge.
• 9:19
  Speaker 1: So that's where agents can come in.
• 9:22
  Speaker 1: Think of agents as a fancy term.
• 9:24
  Speaker 1: That just means system.
• 9:26
  Speaker 1: All an agent is is a collection of different software components that are composed together to make up a more valuable system.
• 9:35
  Speaker 1: So, as a business, if you want to solve problems with AI, you're thinking about these different bits and pieces.
• 9:41
  Speaker 1: Another way to think of it is you guys are all familiar with systems like AMSs or LMSs.
• 9:46
  Speaker 1: Those are systems, right, and they have lots of parts.
• 9:49
  Speaker 1: No one goes to Microsoft and says, hey, how come SQL Server as a database doesn't handle my AMS requirements or my LMS requirements by itself?
• 9:58
  Speaker 1: It's just the database, it's the raw database, brain or engine.
• 10:02
  Speaker 1: Right, and think of it that way.
• 10:04
  Speaker 1: An agent is just basically a collection of componentry.
• 10:06
  Speaker 1: So what can agents do beyond models?
• 10:09
  Speaker 1: So the first thing they can do is observe their environment.
• 10:12
  Speaker 1: They can understand where they live in the world and they can connect to other systems.
• 10:17
  Speaker 1: So let's talk about AI agents.
• 10:19
  Speaker 1: There's a company called Klarna Quick show of hands.
• 10:22
  Speaker 1: How many of you have heard of Klarna?
• 10:23
  Speaker 1: Okay, so Klarna is a buy now, pay later company, bnpl for short.
• 10:30
  Speaker 1: Essentially, in e-commerce, you might go to a store online and you'll see something that says pay over time or pay in installments, and so Klarna will let you set up a payment plan, buy a product now and receive the value from it, but pay it over four months or six months, things like that.
• 10:45
  Speaker 1: They have millions of customers all over the world.
• 10:47
  Speaker 1: They have a lot of customer inquiries.
• 10:50
  Speaker 1: People are constantly emailing them stuff like just asking what their payment schedule is, or asking them to change the payment schedule, or just asking fairly generic questions.
• 10:57
  Speaker 1: So they implemented an AI-based assistant that resolves two-thirds of their overall ticket volume Two-thirds.
• 11:06
  Speaker 1: What's interesting, though, and it's multilingual, available all the time.
• 11:08
  Speaker 1: Of course.
• 11:09
  Speaker 1: What is really interesting is this the resolution time right, the time not for someone to answer, but the time to get to the answer to the finish line went from 11 minutes on average down to two minutes.
• 11:21
  Speaker 1: Think about that Just as the most important metric to customer service.
• 11:25
  Speaker 1: I mean, you might want to talk to someone who's pleasant, but really, if they can answer your question quickly, you're really happy with them, right?
• 11:33
  Speaker 1: So, of course, as a result of that, their NPS went way up, their customer sat went way up.
• 11:38
  Speaker 1: The cost, of course, went way down.
• 11:41
  Speaker 1: The AI assistant, in the first month that it was released this is earlier this year did the work of 700 people in the first month.
• 11:48
  Speaker 1: It's pretty crazy.
• 11:49
  Speaker 1: So this is kind of cool because, for the first time, customer service tech is both saving money, which is great, but also improving the experience.
• 11:58
  Speaker 1: Improving the experience Now.
• 12:00
  Speaker 1: This, of course, is very rapidly becoming the expectation.
• 12:03
  Speaker 1: Brands are all going to be expected to do this, and that includes you.
• 12:07
  Speaker 1: So can associations reasonably do this?
• 12:11
  Speaker 1: You're not Klarna.
• 12:11
  Speaker 1: You don't have the resources of Klarna or someone like that.
• 12:15
  Speaker 1: They're a fairly large company at this point.
• 12:17
  Speaker 1: They're a tech company, right, they have access to talent that you don't have.
• 12:20
  Speaker 1: They have access to a lot more capital than you do.
• 12:23
  Speaker 1: So audio is becoming a bigger and bigger thing, and so one of our companies, betty, is rolling out a voice mode next year and we have a preview of it, and I was gonna do this live on stage by calling Betty on a phone to demo it to you guys, but I decided to record it ahead of time, so the internet's not the best in the room, so we're going to just take a listen to a conversation I had with Betty, and she was trained.
• 12:44
  Speaker 1: This particular instance of Betty was trained on digital now content.
• 12:47
  Speaker 1: So I'm just asking some questions, and this is going to become the standard of what people expect, and it's not yet perfect, but it's a starting point.
• 12:54
  Speaker 1: So we'll go ahead and listen.
• 12:55
  Speaker 1: Hey, betty, what's going on?
• 12:59
  Speaker 4: Hey there, exciting stuff in the association world.
• 13:03
  Speaker 4: Digital now is coming up and it's the place to be for top association leaders, keynotes, workshops and networking galore that's awesome conference digital now is happening from october 27 to 30 2024 at the Omni Shoreham Hotel in Washington DC.
• 13:23
  Speaker 4: Ready to dive into some game changing content?
• 13:26
  Speaker 1: Yeah, I am, and you know what?
• 13:28
  Speaker 1: Here's a surprise for you.
• 13:29
  Speaker 1: I hope you're excited because you are actually on stage right now during my opening keynote, so say hi to everyone.
• 13:37
  Speaker 4: Hello everyone, it's a thrill to be here at Digital Now sharing the stage with all of you visionary association leaders.
• 13:45
  Speaker 4: Let's dive into some cutting edge ideas and make this conference unforgettable, Ready to shape the future.
• 13:53
  Speaker 1: Hey Betty, listen, some of the folks in the room are probably wondering the best way to get started with AI.
• 13:58
  Speaker 1: They're a lot of times perhaps hesitant because their organizations don't have a ton of technical resources.
• 14:05
  Speaker 1: So let me know what you're thinking.
• 14:06
  Speaker 1: Can you speed it up a little bit, Because I'm a little bit impatient.
• 14:10
  Speaker 4: Absolutely no need for hesitation.
• 14:12
  Speaker 4: Here's a quick start Dedicate just 15 minutes a day to learning about AI, Follow AI thought leaders on LinkedIn, subscribe to AI newsletters and listen to the Sidecar Sync podcast.
• 14:26
  Speaker 1: Well, that's a great idea.
• 14:27
  Speaker 1: Mallory and I, in particular, are 100% on board with everyone listening to the Sidecar Sync podcast that we co-host every single week.
• 14:34
  Speaker 1: Well, listen, betty, we've got to go.
• 14:36
  Speaker 1: This keynote isn't super long and I'm going to get pulled off stage pretty soon.
• 14:40
  Speaker 1: Thanks so much for your help.
• 14:41
  Speaker 1: We're really excited about your voice mode and your help for all associations as their knowledge agent.
• 14:48
  Speaker 4: Thanks for having me.
• 14:49
  Speaker 4: I'm thrilled to be part of your AI journey.
• 14:51
  Speaker 4: Enjoy the rest of digital now and remember the future of associations is bright with innovation.
• 15:01
  Speaker 1: All right.
• 15:01
  Speaker 1: So there's some really cool things about that and there's obviously some glaring opportunities.
• 15:06
  Speaker 1: Right still with voice today, remember, we are on this journey and AI models keep getting better at this crazy fast pace.
• 15:14
  Speaker 1: Voice mode right now.
• 15:15
  Speaker 1: The reason it's a preview and not yet available in the product is it's ridiculously expensive to do this.
• 15:20
  Speaker 1: Well, at the moment, but that's about to change.
• 15:22
  Speaker 1: For low latency, high resolution audio like that, it's extremely expensive at the moment, but very soon, like literally in the next three to six months, we expect that to be available and to be able to make that.
• 15:34
  Speaker 1: You know scale.
• 15:35
  Speaker 1: So why is voice mode important?
• 15:37
  Speaker 1: You know, when we think about the chat GPT moment, we say okay.
• 15:41
  Speaker 1: Well, for the first time, the broader world had access to talk to a computer.
• 15:46
  Speaker 1: Right, we were typing, but we were talking to a computer in our language.
• 15:50
  Speaker 1: That's a pretty stunning shift from all of our history with technology.
• 15:55
  Speaker 1: Up until that point in time, people had to adapt to the machine.
• 15:59
  Speaker 1: You had to learn how to click on menus and type in commands, or if you were coding, writing programming code, you had to do those things in order to get the machine to do what you wanted.
• 16:10
  Speaker 1: So you, the person had to adapt to the computer.
• 16:16
  Speaker 1: That shifted.
• 16:18
  Speaker 1: The computer under the hood was still the same, basically more powerful version, but now the computer was adapting to you.
• 16:26
  Speaker 1: That is the reason why ChatGPT had 100 million users in 30 days the fastest growing app in the history of technology so far because people were blown away by the fact that they could have meaningful conversations at scale with a computer.
• 16:40
  Speaker 1: That was the novel thing and of course, that was just text and as human beings there's a lot we can do with text.
• 16:48
  Speaker 1: Reading and writing is great, but talking to each other is kind of how we started this whole thing.
• 16:54
  Speaker 1: So being able to talk to a computer is a big deal, and I think Betty's voice mode right now it's a little bit robotic.
• 17:01
  Speaker 1: It's actually a little bit slow.
• 17:03
  Speaker 1: You could tell there was a little bit longer gap than what you might expect with a human.
• 17:06
  Speaker 1: It's actually pretty good, especially compared to what audio was even a couple years ago.
• 17:11
  Speaker 1: So the main reason I wanted to play this for you is to get this into your brains.
• 17:16
  Speaker 1: That voice is something you can do, you should be thinking about and it's going to become the expectation too.
• 17:23
  Speaker 1: If you think about the reality of the world.
• 17:25
  Speaker 1: You don't live in a bubble.
• 17:27
  Speaker 1: You may be in association with limited resources, you may not think of yourself as part of the brand experience of consumers, but you are.
• 17:35
  Speaker 1: Your members are consumers in the world, just like you and I, and they have expectations, and it's going to be voice very soon, so you have to think about how to incorporate this as a modality into your overall strategy.
• 17:48
  Speaker 1: All right, shifting gears, so we're going to talk through a couple more examples of agents.
• 17:56
  Speaker 1: This particular slide is focused on the world of data largely structured data.
• 18:00
  Speaker 1: Data is something that obviously permeates our existence, and you guys have a ton of data.
• 18:02
  Speaker 1: Largely structured data.
• 18:03
  Speaker 1: Data is something that obviously permeates our existence, and you guys have a ton of it, and you don't do that much with it for the most part.
• 18:09
  Speaker 1: So, for 23 years, I was part of an AMS company I founded, and we were really proud of the fact that our database was super flexible.
• 18:18
  Speaker 1: It allowed you to configure it so you could drop any data you want.
• 18:22
  Speaker 1: I'm still very proud of that.
• 18:23
  Speaker 1: It's awesome, and there's a lot of systems that can do that.
• 18:25
  Speaker 1: Now.
• 18:26
  Speaker 1: The thing is, though, is that it was basically a one-way street.
• 18:29
  Speaker 1: People would put data in, put data in.
• 18:31
  Speaker 1: Put data in and they'd work really, really hard to get the data right.
• 18:35
  Speaker 1: Another one here called I think it's pronounced AI Win.
• 18:38
  Speaker 1: This is a very specialized software for CPA firms.
• 18:43
  Speaker 1: It's an AI-based billing platform.
• 18:45
  Speaker 1: It not only decreases time spent, but also it increases the result.
• 18:51
  Speaker 1: So I like this case study because it's focusing on the outcome, not just the internal bits of hey, we saved time, but, like with Klarna, you had a measurable improvement in the outcome here.
• 19:02
  Speaker 1: You had a 300% increase in online payments collected, and online payments tend to move a lot faster than snail mail.
• 19:10
  Speaker 1: So that's a measurable improvement in cash flow.
• 19:12
  Speaker 1: That reduces, you know, dunning notices.
• 19:15
  Speaker 1: There's lots of downstream benefits.
• 19:16
  Speaker 1: That's something to consider too.
• 19:18
  Speaker 1: So there's association versions of this you guys can consider.
• 19:22
  Speaker 1: Really, the goal of sharing a couple of non-association examples, principally for me, is to get you guys to think about what you can follow, what you can read, what you can listen to outside of our space.
• 19:33
  Speaker 1: So that's you know.
• 19:35
  Speaker 1: As Betty mentioned, mallory and I host the Sidecar Sync podcast every week.
• 19:38
  Speaker 1: A lot of what we talk about is stuff from outside of the industry and how it's applicable to this market.
• 19:44
  Speaker 1: So that's one resource available for you guys, but I would suggest you also follow some other things that are totally unrelated to associations.
• 19:51
  Speaker 1: Don't just focus on what's going on here.
• 19:53
  Speaker 1: Think about learning from the rest of the world and then thinking about how to apply it.
• 20:00
  Speaker 1: So, coming back to the whole point of this is why are we excited about agents?
• 20:04
  Speaker 1: You know we want to talk about freeing up some of your team.
• 20:08
  Speaker 1: How many of you here work in an organization where you say, hey, we don't have enough to do, we have abundant free time and we're just kind of chill, right?
• 20:16
  Speaker 1: No one that'll admit it at least.
• 20:18
  Speaker 1: Right?
• 20:18
  Speaker 1: We're all super busy, so it'd be great if we could free up some of those cycles.
• 20:23
  Speaker 1: It's kind of like that system one and system two thinking stuff I was talking about earlier.
• 20:26
  Speaker 1: If we're so crazy busy that all we do is go from task A to task B to task C, do we really stop and breathe and think for a moment, aside from quality of life improvements and improvements to your culture that that could potentially bring?
• 20:39
  Speaker 1: Think about the better outcomes you could create if you actually stopped for a minute and thought about things.
• 20:47
  Speaker 2: The next keynote speaker for day one of Digital Now 2024 was Thomas Altman.
• 20:53
  Speaker 2: Thomas Altman is a data scientist, an association expert and an entrepreneur.
• 20:57
  Speaker 2: His first introduction to the world of associations was a decade ago, when he took a job implementing AMS solutions right out of grad school.
• 21:05
  Speaker 2: Thomas is the co-founder of Tassio Labs and, to be totally honest, he is one of my personal go-to AI experts, Aside from Amit.
• 21:14
  Speaker 2: If I have any nitty gritty AI questions that I want answers to, Thomas is the person that I always go to.
• 21:21
  Speaker 2: So his keynote centers around the idea that advancements in artificial intelligence have fundamentally shifted how humans consume, cultivate and create knowledge.
• 21:32
  Speaker 2: In this keynote, he's going to explore how these changes present both challenges and unprecedented opportunities for organizations dedicated to knowledge sharing, like associations.
• 21:49
  Speaker 5: I'm Thomas Altman.
• 21:49
  Speaker 5: I'm very excited to be here today, and one of the reasons I'm very excited to be here today is that this is not what I normally do, right?
• 21:53
  Speaker 5: I'm not normally on a stage talking to people.
• 21:55
  Speaker 5: Although I like it, it's not what I normally do.
• 21:57
  Speaker 5: Normally, what I do is help associations implement AI strategies, understand their data, use it really effectively, which means you're more likely to find me tucked away deep in a cave, kind of hunched over a computer, typing away like Gollum with a fish or something like that.
• 22:13
  Speaker 5: So I'm very excited to be here, because when Mallory came to me and said, hey, thomas, you can come out of your cave and see people and look at the daylight, I jumped at the chance.
• 22:21
  Speaker 5: So really appreciate you all having me today.
• 22:24
  Speaker 5: Actually, where's my clicker?
• 22:26
  Speaker 5: There it is.
• 22:26
  Speaker 5: So one of the things, since that is my day-to-day.
• 22:31
  Speaker 5: One of the things I've started to notice, though, since I'm working a lot with this intersection between AI, associations and data, is I've started to notice some patterns emerge, right, I've seen some things, and in fact, I've started to notice some patterns emerge.
• 22:42
  Speaker 5: I've seen some things, and in fact, I've seen maybe the same thing kind of over and over again, regardless of the type of association, and the story is something like Thomas, we've got kind of all this great kind of content.
• 22:56
  Speaker 5: In fact, we are optimized for producing this content.
• 23:00
  Speaker 5: We've got the systems, the processes, the culture in place for creating knowledge and we produce this knowledge and put it out into the world.
• 23:06
  Speaker 5: But our sneaking suspicion is kind of this vague notion we all have is that our members aren't getting the most out of that.
• 23:14
  Speaker 5: Right, so the Royal Societies were basically groups like this.
• 23:18
  Speaker 5: Right, people coming together that tended to be around scientific endeavors.
• 23:22
  Speaker 5: Right so people coming into a room talking about their different like attempts at science that they have made since the last meeting, using their language, their words, to talk about what they plan to do, maybe writing that down, sharing it for their peers to review, somebody reading the debate happening within the room, everyone then scattering with new ideas.
• 23:43
  Speaker 5: Right, so, because I had an idea, I came and I shared it with the group.
• 23:47
  Speaker 5: Maybe you disagreed pretty vehemently with that idea, but it inspired you to go in a new direction.
• 23:53
  Speaker 5: This is how sort of these royal societies pushed the space of knowledge outward right, and it was through that process.
• 24:00
  Speaker 5: It was through this collaborative, communicative process, the use of language in a way that shared knowledge and then, also, through the interaction, created knowledge that I think associations still capture to this day.
• 24:10
  Speaker 5: The other thing, the other kind of entity that popped up around the same time, were these chartered organizations, right?
• 24:16
  Speaker 5: These chartered companies?
• 24:17
  Speaker 5: Right, these were the prototypes for what we would consider corporations today, but they're also the prototypes for trade associations, right?
• 24:23
  Speaker 5: These are people working together outside the threshold of the state.
• 24:28
  Speaker 5: Right, it's outside.
• 24:29
  Speaker 5: It's not governmental, it's a civil institution of people collaborating to push the trade forward, to make trade more possible, to make sure that, you know, the common interest for this one group is being served, even when it's in conflict with the state.
• 24:44
  Speaker 5: It is this thing that stood apart from it, that allowed people to push their own goals forward.
• 24:52
  Speaker 5: Let me dive into this.
• 24:52
  Speaker 5: When I say language is a technology, what does that mean?
• 24:54
  Speaker 5: It seems weird, it seems like a strange concept, but I think it's an important one.
• 25:00
  Speaker 5: When I started thinking this way, it actually changed the way that I engage with AI.
• 25:05
  Speaker 5: So when I say language as a technology, I mean it.
• 25:08
  Speaker 5: You can use your words tactically as a tool to create right.
• 25:12
  Speaker 5: So think about it this way.
• 25:14
  Speaker 5: You can use.
• 25:15
  Speaker 5: In the same way, you can use a hammer to kind of put pieces of board together to create something bigger than you had before.
• 25:22
  Speaker 5: Right, it's a tool that creates something larger from component pieces.
• 25:25
  Speaker 5: Language the way that we use words allows us to shape our kind of experience of reality.
• 25:32
  Speaker 5: What I mean by that is I know this is kind of woo-woo, but it's a very important way to think about using your words.
• 25:38
  Speaker 5: Right.
• 25:38
  Speaker 5: When you have ideas, right, the ideas initiate inside of your head.
• 25:41
  Speaker 5: Right, and they stay internalized to you until you put them into words.
• 25:45
  Speaker 5: And once you put them into words, it is now a tangible thing that other people can react to.
• 25:50
  Speaker 5: Right, so when I write down or I say, when I'm standing here in front of you and you can all agree or disagree.
• 25:56
  Speaker 5: The only reason you can agree or disagree is because this is now a real thing.
• 25:59
  Speaker 5: Like, I have committed this interior thought process to an external form that you can then engage with.
• 26:06
  Speaker 5: Right, and the technology that I used is my words and what that does.
• 26:10
  Speaker 5: It allows you to sort of engage with it.
• 26:12
  Speaker 5: It enables collaboration across ideas, allows ideas to be shared further abroad.
• 26:19
  Speaker 5: This is gonna be an interactive exercise, so we're gonna break out of the sitting and watching.
• 26:24
  Speaker 5: We're going to participate, right, there's going to be a call and response.
• 26:26
  Speaker 5: I'll do a demo first so we get a sense of how this is meant to go, but the idea is I'm going to turn you into a large language model.
• 26:32
  Speaker 5: This whole room is going to become the large language model for this exercise, and I'm going to ask you to predict the next word.
• 26:39
  Speaker 5: I'm going we put words on the screen, I'm going to say them and then I'm going to point and you're going to say the word back.
• 26:44
  Speaker 5: So I'll say once upon a time, and at what point?
• 26:46
  Speaker 5: You would say there Okay, are we clear?
• 26:50
  Speaker 5: Does everybody feel good to jump in?
• 26:52
  Speaker 5: All right, so this is the largest room I've done this in.
• 26:56
  Speaker 5: I have no idea how this is going to go.
• 26:57
  Speaker 5: I'm a little nervous.
• 26:58
  Speaker 5: So once upon a time there was was.
• 27:01
  Speaker 5: Oh my god, that was amazing.
• 27:03
  Speaker 5: I am so happy, I am so thrilled that that worked.
• 27:06
  Speaker 5: Yes, once upon a time, there was right.
• 27:08
  Speaker 5: And the reason, by the way, I started with once upon a time there for groups like this is that there's usually 20% of the group that are Star Wars fans, and if I just started with.
• 27:18
  Speaker 5: Once upon a time, it goes in a galaxy far, far away.
• 27:20
  Speaker 5: It's like the idea still works, but that's not what I was trying to do.
• 27:23
  Speaker 5: So once upon a time there was how did you know that, right?
• 27:27
  Speaker 5: How did you know that was came after that.
• 27:30
  Speaker 5: How did I know that you were going to know that?
• 27:32
  Speaker 5: I put it on the screen.
• 27:33
  Speaker 5: I knew this was going to happen, and the reason is you've seen the pattern, right, and that's kind of a low-level version of what's happening inside of ChatGPT is it's seeing these kind of patterns, and in this case, it's kind of a naive pattern.
• 27:47
  Speaker 5: It's a very simple one, right?
• 27:48
  Speaker 5: But scale up.
• 27:50
  Speaker 5: I saw a talk from Ilya Setskovor, right?
• 27:53
  Speaker 5: So Ilya Setskovor was one of the founders of OpenAI, one of the proponents of this scaling up, of autocomplete, right?
• 28:00
  Speaker 5: He probably is the person that got it and said, okay, we could actually throw a billion dollars at this and if we did, we would solve this problem, we'd create intelligence, and he was talking about so once upon a time there was it's pretty easy.
• 28:13
  Speaker 5: But imagine, instead of this, imagine you had read a whole book.
• 28:16
  Speaker 5: This book was a murder mystery, kind of like a knives out clue, kind of a situation, right.
• 28:22
  Speaker 5: So you've read this whole book.
• 28:23
  Speaker 5: There's a murder and there's all these different possible scenarios that could have happened, and you're at the very end of the book, you're on the last page and there's sort of one page less.
• 28:32
  Speaker 5: You get to the last page and the detective standing in front of the group, he says I know who the murderer is.
• 28:39
  Speaker 5: The murderer is how do you predict the next word?
• 28:43
  Speaker 5: What does it take for you to predict that next word?
• 28:48
  Speaker 5: Really well, it takes some intelligence, it takes some knowledge, right.
• 28:53
  Speaker 5: What you're doing is you're connecting the dots.
• 28:56
  Speaker 5: There are ideas floating around that whole novel, that whole maybe, you whole, maybe movie that you watched, that are going to inform what would be a good next word prediction versus a bad one, right?
• 29:08
  Speaker 5: And what I would say is I would think of artificial intelligence as a prosthetic for human intelligence.
• 29:14
  Speaker 5: So what do I mean by that?
• 29:16
  Speaker 5: So, in the same way that I can sort of walk around and if I'm holding a cane, I can actually extend my field of contact beyond my physical body, like I can actually touch further out than where my arm can actually reach, because I'm holding a cane, my sense of touch is actually extended further than my physical body.
• 29:35
  Speaker 5: Same thing if I've got binoculars on, I can see further away.
• 29:38
  Speaker 5: I would argue that artificial intelligence is that for ideas.
• 29:45
  Speaker 5: So if you engage artificial intelligence in a smart way, you can actually extend the ideas that you can have beyond what was possible without it, and I think there's a couple ways that we can do that.
• 29:56
  Speaker 5: We'll talk first around how to do that at the individual level, and then how you can capture that information as an organization.
• 30:01
  Speaker 5: So the first way I want to talk about this is that, as an individual, you can actually expand your access to knowledge by intentionally doing this.
• 30:17
  Speaker 5: So what I mean by that is and my workshop later is going to be tactically how to do this using chat, gpt.
• 30:21
  Speaker 5: So if you're curious around like techniques to do this, feel free to join that.
• 30:25
  Speaker 5: But as a theme, what you can do here, I like to think of this as intentionally engaging with those ideas.
• 30:31
  Speaker 5: So if an LLM is a network of ideas, right, we can intentionally poke at that, using our language to extract those ideas.
• 30:40
  Speaker 5: So how do we get back down?
• 30:42
  Speaker 5: Right?
• 30:42
  Speaker 5: So we've kind of we've covered a lot of heavy topics, right, admittedly so I think, though, if you can really take this to heart.
• 30:49
  Speaker 5: If you can kind of see the threads right, the way that associations have evolved to be knowledge creators right, the way that AI has come to be by using language, the way that associations intersect with that knowledge, then I think what you can start to do is put together strategic plans to implement AI in a way that gets you back down to your roots right.
• 31:13
  Speaker 5: So if our roots as association people are around helping people associate, bringing people together, exchanging ideas, collaborating ideas sort of I think of it, as you know, almost like open source code when people write a white paper, a journal article or a policy statement or a rule or a standard, right.
• 31:31
  Speaker 5: What this is is we're putting out into the world a bunch of language that other people can take and use it how they want to debug it, add more ideas on top of it, sort of submit the pull request.
• 33:31
  Speaker 5: If you will back to the knowledge base itself, and when you have AI kind of working behind the scenes through this agentic process by putting people into touch with this larger language model system, I think what you can do is invest less time in sort of the grind of the day-to-day and more time into connecting people with each other, because, at the end of the day, that's the purpose right.
• 33:54
  Speaker 5: That's where we want to get to is making sure that our groups, our constituencies, are being served by us.
• 34:00
  Speaker 5: They're feeling the connection to the work that we're doing, they're being participatory in the creation, either passively, by searching for it and consuming it, or actively, by creating the next wave of it.
• 34:10
  Speaker 5: By being able to intentionally get people back in touch with that, by letting AI handle all these things behind the scenes, you can actually put that power back into your members' hands.
• 34:20
  Speaker 5: And by putting that power back into your members' hands, you are delivering that value that I imagine most of us suspect that we're missing right now, and I've seen this happen.
• 34:30
  Speaker 5: People, once they feel in control of the knowledge and feel participatory in that knowledge process, they feel more engaged with your association and they come back and they spend more time with you and they provide more ideas, and it's a kind of a virtuous cycle that we can build up.
• 34:46
  Speaker 5: So I will end on this.
• 34:48
  Speaker 5: My challenge is to you is probably the same one as a myth go out and use AI, but now use it with this knowledge that you have today that the key technology is not the AI.
• 34:58
  Speaker 5: The key technology is our language.
• 35:02
  Speaker 2: Our next Digital Now keynote speaker from day one is a name that you might recognize Sharon Guy, because we interviewed Sharon on an earlier episode of the Sidecar Sync podcast.
• 35:12
  Speaker 2: Because we interviewed Sharon on an earlier episode of the Sidecar Sync podcast.
• 35:15
  Speaker 2: If you don't know who she is, she is a culture fluid expert in e-commerce, digital transformation and AI.
• 35:20
  Speaker 2: She helps organizations become agile disruptors in their industry so they can increase revenue and retain users.
• 35:25
  Speaker 2: In her tenure at Alibaba, she advised brands and heads of state in crafting their digital strategy with programmatic marketing and artificial intelligence.
• 35:34
  Speaker 2: She is also the author of the book E-commerce Reimagined what we Can Learn in Retail and E-commerce from China.
• 35:41
  Speaker 2: Drawing on Sharon's decade-long experience with the e-commerce system, her keynote shares actionable insights on how associations can adopt AI-driven strategies for their own success, from creating new member engagement opportunities with live streaming to building stronger communities of advocates.
• 35:59
  Speaker 2: Enjoy this excerpt from Sharon Guy's keynote session.
• 36:02
  Speaker 6: I'm going to start off this keynote with an imagination exercise.
• 36:07
  Speaker 6: So if we can all close our eyes for a minute and imagine that we are one day way out in the future, we're also a Monday and you're at home and you're holding a hot cup of coffee, like maybe you are doing now.
• 36:24
  Speaker 6: And you're holding a hot cup of coffee, like maybe you are doing now, and you want to open the door to feel that ray of Washington DC fall-autumn sunshine.
• 36:32
  Speaker 6: So you open your door and you look up and there's a friendly neighborhood drone here to deliver off a package to you.
• 36:41
  Speaker 6: Here to deliver off a package to you.
• 36:43
  Speaker 6: It's from the Shop, your favorite e-commerce store.
• 36:46
  Speaker 6: In this futuristic world, the Shop is akin to a company like Amazon, a company that knows your needs and wants so well that you never actually need to go to theshopcom to order anything or visit its mobile app.
• 37:04
  Speaker 6: The shop will simply hire drones to deliver off products and packages right to your doorstep.
• 37:11
  Speaker 6: And I shouldn't forget to mention that in this futuristic world, there is no return policy, because the shop's algorithm never fails.
• 37:24
  Speaker 6: Because the shop's algorithm never fails.
• 37:26
  Speaker 6: And you can open your eyes now and you might be saying, ooh, sharon, I don't know if I want to live in that world.
• 37:33
  Speaker 6: That world's kind of creepy.
• 37:35
  Speaker 6: What if I get something that I don't intend to order or even get?
• 37:39
  Speaker 6: Well, that's exactly what happened to the protagonist of this story, and that scene is borrowed from this book, a sci-fi novel called Quality Land.
• 37:51
  Speaker 6: That turns a lot of these AI concepts on its head.
• 37:55
  Speaker 6: But when I first had alien contact I mean when I first worked with AI was when I was in China in 2017.
• 38:07
  Speaker 6: So I used to work at this company called Alibaba.
• 38:11
  Speaker 6: Within it there's this business unit called Tmall, which was the Amazon of China, and the thing with retail systems in China is it's a lot more complicated, or the digital ecosystem in China is a lot more complicated than what it is in the US.
• 38:27
  Speaker 6: So we used to have this thing called Double 11, or November 11th.
• 38:34
  Speaker 6: It's actually coming right up.
• 38:35
  Speaker 6: It's the biggest sale of the year.
• 38:37
  Speaker 6: It's very similar to Black Friday.
• 38:39
  Speaker 6: It's at the end of the year, it's also in November and Alibaba works with about 300,000 brands from around the world and everyone wants to sell to China because it's also the world's largest consumer group of consumers and during Double Eleven season, everyone gets really busy in organizing brands, figuring out what they should sell, what their strategies are, what their pricing should be.
• 39:04
  Speaker 6: Brands figuring out what they should sell, what their strategies are, what their pricing should be.
• 39:06
  Speaker 6: And I was about to go home at 11 pm from a meeting when I get called back into the office and I'll remember this day forever because it was a blistering cold night in the city of Shanghai and I got called back into the office and they're like we need to show you this new tool.
• 39:28
  Speaker 6: So this is the homepage and it's very similar to if you have amazoncom in your phones and you open up the homepage.
• 39:35
  Speaker 6: There's a lot of personalization that runs behind these apps, in that whatever you see in these banners or these products are personalized to you.
• 39:44
  Speaker 6: It's the same in Amazon.
• 39:46
  Speaker 6: So the page that I open looks entirely different from what you would see when you open it versus anybody else.
• 39:51
  Speaker 6: And so all of that runs with this algorithm that both Amazon has proprietarily and Alibaba has proprietarily.
• 40:01
  Speaker 6: But all of these so for, for instance, this banner that you see, we used to hire about 10,000 designers in During the season of double oven because there's just so many products that we have to work with.
• 40:16
  Speaker 6: I, when I was going through this at the topic and then presentation, I was thinking, actually, you know what?
• 40:21
  Speaker 6: I think I there's actually a lot of similarities between the association space and the e-commerce space.
• 40:28
  Speaker 6: Or if you managed an e-commerce website of some sort, because, well, we both have a customer.
• 40:35
  Speaker 6: Associations have members, e-commerce websites have online customers, and then associations and e-commerce owners we're both trying to earn some sort of money so that we continue to run.
• 40:50
  Speaker 6: So on the association side, the goal is to renew members' annual membership and e-commerce websites we're trying to get our customers to buy things again and again.
• 40:59
  Speaker 6: In the association world, you have to keep your members engaged through events, through webinars, through different types of content reports, seminars, ceo or leadership summits.
• 41:13
  Speaker 6: On the e-commerce side, we have the same thing.
• 41:15
  Speaker 6: There's campaigns that we host.
• 41:18
  Speaker 6: There's special SKUs or items that we highlight to attract.
• 41:22
  Speaker 6: We call them a hook SKU.
• 41:24
  Speaker 6: It's something that you show in the front page or the first thing that a customer sees so that they don't scroll away, so that they keep on scrolling on your website.
• 41:34
  Speaker 6: And then associations are also matchmakers, because when you host these large events, you're bringing together a lot of suppliers, a lot of planners together and you're enabling them to create that connection On an e-commerce website.
• 41:49
  Speaker 6: We're doing the same thing.
• 41:51
  Speaker 6: So a year ago, we asked AI to give us a video of Will Smith eating spaghetti, and this is the type of video that we got from AI.
• 42:01
  Speaker 6: This is from the Model Scope Text-to-Video Generator and this is dated March 28, 2023.
• 42:08
  Speaker 6: And you might say it's a little demonic, to say the least.
• 42:11
  Speaker 6: No spaghetti brand or restaurant brand would ever use this type of footage.
• 42:16
  Speaker 6: But a year after that, exactly a year after, we were able to get something like this and this is produced by Sora, which is OpenAI's text-to-video product.
• 42:28
  Speaker 6: And now this is a video that is not shot with a model, not shot in Tokyo, japan.
• 42:35
  Speaker 6: There were no directors or cinematographers, and now this is a type of footage that is kind of usable.
• 42:42
  Speaker 6: And then, just a few months ago, openai started to collaborate with actual music artists.
• 43:08
  Speaker 5: So now we have whole music videos that is made with AI.
• 43:13
  Speaker 6: There was one scene in there, actually, where this girl stood by a door in a denim jacket and she had no arm, but you probably didn't notice that.
• 43:22
  Speaker 6: And so that's the thing with AI, too, is it's definitely still imperfect, but sometimes those imperfections aren't even that, it's not even that noticeable to the human eye.
• 43:33
  Speaker 6: Their generative AI is definitely stretching its arms as far as into live streaming as well, and this is something that you'll also see popularized in 2025, 2026, where because, as I said before, the online space is noisy Everyone is trying to get an eyeball eyeballs to go on their app to for views, impressions.
• 43:54
  Speaker 6: Something that is going to change very soon A lot of e-commerce companies, brands, retailers are looking at is change in this search space, and I think this is what's going to affect a lot of us too.
• 44:06
  Speaker 6: So where are you starting your searches?
• 44:08
  Speaker 6: I polled my LinkedIn community and 30% I was very alarmed to see that it was 30% that is starting their search through an LLM, which was a lot higher than I had originally anticipated.
• 44:23
  Speaker 6: By now it's even a larger number, and so there's this new term that's emerging called AEO or answer engine optimization.
• 44:32
  Speaker 6: So we're moving from a world where we kept on interacting with a context window like this, to a context window that looks like this, which means that instead of writing just a simple search term and then you breezing through every single web page and sort of getting to your own conclusion of what that answer is, we're going into a world where we're writing about a whole situation or context and then for the answer engine or the LLM to give us that answer directly.
• 45:02
  Speaker 6: So very recently I was trying to buy small business insurance and I went through this process.
• 45:08
  Speaker 6: Normally I would go to Google type small business insurance, look through the options, pick one.
• 45:14
  Speaker 6: But I went to ChatGPT for this search and in the end I actually purchased off of it or from a link that ChatGPT gave me.
• 45:23
  Speaker 6: So a lot of these buying patterns are starting to change.
• 45:27
  Speaker 6: A lot of buyers are directly going to that situational, descriptive context window to find the actual vendor or solution.
• 45:37
  Speaker 6: So for a lot of your members also, that might be happening to their businesses and that's something that they have to realize is this huge change in that search world.
• 45:46
  Speaker 6: So we all know about SEO, which is search engine optimization.
• 45:51
  Speaker 6: We all run websites, right.
• 45:53
  Speaker 6: You, every single Association has a website.
• 45:55
  Speaker 6: Sidecar has one, and I have one as well, and so we all invested a lot of time in optimizing our home pages, or every single page, for it to rank higher.
• 46:08
  Speaker 6: A lot of your members also might compete with each other.
• 46:12
  Speaker 6: They're also optimizing, spending a lot of money in SEO to rank their websites higher.
• 46:17
  Speaker 6: So now, with this change in search, we're going to see a new type of investment in what we call AEO, or Answer Engine Optimization, where we're trying to get our new type of investment in what we call AEO, or answer engine optimization, where we're trying to get our website more relevant for an answer engine to pick up.
• 46:30
  Speaker 6: I think this is a very crucial moment in internet history also, and it's also really good for the smaller guys, because if you can AEO your website well enough and that if a buyer is trying to search for a question, maybe you didn't have tons of thousands of dollars or some of the other big guys, millions of dollars to spend in Google ads and Instagram ads, and I think what's important to remember is there's a lot of change.
• 46:59
  Speaker 6: I call it sense making.
• 47:00
  Speaker 6: So, in this AI stage that we're in, a lot of people are trying to wrap their heads around what's happening because, as humans, we don't like change.
• 47:10
  Speaker 6: It's so much easier for us when we have set routines and things that we are.
• 47:17
  Speaker 6: You know, there's a certain email that has to be answered in a certain way and we answer that.
• 47:21
  Speaker 6: There are certain people that we meet on a weekly basis and we meet with them.
• 47:31
  Speaker 6: We like routine and we like schedules, but right now, a lot of the things that are happening in AI it's disrupting the entire world and a lot of businesses and a lot of executives in your members probably also are going through that exact same sense-making phase.
• 47:47
  Speaker 2: Our last keynote speaker on day one of Digital Now was Dr Denise Turley, who is a dynamic leader, visionary educator and influential voice in the world of artificial intelligence and leadership.
• 47:59
  Speaker 2: As vice president of corporate systems at the US Chamber of Commerce, denise spearheads the strategic development of enterprise-wide technology solutions.
• 48:07
  Speaker 2: Her leadership transcends the corporate world, extending into academia, where she serves as an assistant professor, guiding the next generation of leaders through inclusive and technology-driven educational practices.
• 48:18
  Speaker 2: In this keynote, dr Denise Turley provides an overview of her journey and implementing generative AI solutions at the US Chamber of Commerce.
• 48:27
  Speaker 2: She shares some key lessons learned from their experiences, including successes and challenges, and she provides a framework for adopting AI within your organization.
• 48:36
  Speaker 2: Here is Dr Denise Turley.
• 48:39
  Speaker 7: So I'm going to get started in my presentation today.
• 48:42
  Speaker 7: I have a few minutes with you where I want to share with you a little bit about what does a day in the future look like where we're assisted with AI, kind of just taking a little bit one step further what Sharon was just talking about right, with that drone during the deliveries.
• 48:56
  Speaker 7: What are some other areas where maybe AI can have an impact in our lives?
• 49:02
  Speaker 7: So, in the morning, imagine that there's this concept of personalized education.
• 49:08
  Speaker 7: And then we just heard about that.
• 49:09
  Speaker 7: Right, it's really hyper-focused personalization.
• 49:13
  Speaker 7: And so in education, we think about when we send our children to school, most of the time we've got a very cookie cutter education experience, and so if you are a student that learns like everyone else, then hey, maybe you're fine, but maybe you don't, and many of us actually don't.
• 49:32
  Speaker 7: And so imagine in the future we could have an AI-assisted learning experience for our students, for our children, for our grandchildren, for our nieces, for our nephews.
• 49:42
  Speaker 7: You get it right.
• 49:43
  Speaker 7: And so in this era, what might happen is when somebody's going to school and they're in class, they've got AI that's assisting their learning and it understands exactly how you learn and it can present content to you in a way that's going to make it stick right.
• 50:00
  Speaker 7: So maybe, if you prefer to learn using interactivity maybe you like virtual spaces the system is going to adapt and present the learning module to you in that way Also, it's going to dynamically adjust right.
• 50:17
  Speaker 7: So if you're really grasping that content and you're answering those assessment questions accurately, maybe it speeds up, but if you're struggling a little bit with some of the content, it knows that it needs to slow down and maybe present that content to you in a slightly different way.
• 50:34
  Speaker 7: We can do that now with technology in a way that is scalable.
• 50:39
  Speaker 7: It's almost impossible to do it right now.
• 50:41
  Speaker 7: Teachers have so much on their plate that it's a struggle.
• 50:47
  Speaker 7: Another idea might be advances that we can do within health, so there's an opportunity for early health intervention.
• 50:55
  Speaker 7: So, in this scenario, we're going to imagine that Mr Hernandez has gone to his doctors and he's having an annual checkup, that Mr Hernandez has gone to his doctors and he's having an annual checkup.
• 51:04
  Speaker 7: So the doctor, though, is able to review information from his AI-integrated smartwatch and is watching for signs in biomarkers.
• 51:10
  Speaker 7: They can take that and then marry that data with, maybe, some recent blood work and uncover the fact that maybe Mr Hernandez now has some signs of early stages of pancreatic cancer, which is actually very, very hard to detect early.
• 51:27
  Speaker 7: Now we might be able to not only to detect this cancer, but then put him onto a regime that helps to improve his outcome.
• 51:36
  Speaker 7: So maybe in the afternoon across town there's somebody else.
• 51:40
  Speaker 7: They are visually impaired.
• 51:42
  Speaker 7: So Sarah is visually impaired.
• 51:44
  Speaker 7: She's unable to see without the use of now what is AI-assisted glasses and for the first time in years, sarah is able to go out and navigate because these glasses are feeding to her real time what's going on in the environment around her.
• 52:02
  Speaker 7: So let me talk you a little bit through our roadmap what happened, some of our successes and also some of the places where we stumbled.
• 52:10
  Speaker 7: I don't call them failures because I believe that st technology, you're going to have mistakes right, because we haven't figured it out yet.
• 52:28
  Speaker 7: There aren't truly any experts in this space right now, despite what you might read or see or see self-promoting.
• 52:35
  Speaker 7: We're all learning how this stuff works.
• 52:37
  Speaker 7: So we started out, as I mentioned, back in November 2022 with ChatGPT.
• 52:42
  Speaker 7: It was really fun.
• 52:44
  Speaker 7: It did some really cool stuff.
• 52:45
  Speaker 7: We were able to do some really cool demos, but there was no data privacy and it was inaccurate.
• 52:54
  Speaker 7: It made stuff up.
• 52:55
  Speaker 7: I would go far to say it flat out lied, and so for us it wasn't something that we could implement and we certainly could not scale that within our organization.
• 53:05
  Speaker 7: We had absolutely no faith in it, but we were still pulled in and drawn into the potential of what it could do.
• 53:13
  Speaker 7: So, a few months later, attempt number two because we abandoned ChatGPT, it was like a no-go, can't do it.
• 53:20
  Speaker 7: Well, now we had OpenAI was within Microsoft right, so it was in our Azure environment, so we were able to check that box for safeguarding our data and our privacy.
• 53:32
  Speaker 7: That's huge for us, right?
• 53:34
  Speaker 7: We're a member organization.
• 53:36
  Speaker 7: That's one of the things that we hold as gold to us is our proprietary data.
• 53:42
  Speaker 7: One of the tools that I'm really proud of is called Chamber Chat.
• 53:45
  Speaker 7: So Chamber Chat is our own internal tool.
• 53:49
  Speaker 7: That's like a chamber expert, and so we have given every one of our employees has access to this.
• 53:56
  Speaker 7: We want to make sure, of course, that our team feels empowered, and so they use Chamber Chat to create content.
• 54:03
  Speaker 7: Chamber Chat is an expert at producing content in our own voice, in our own tone.
• 54:08
  Speaker 7: They produce content in the voice of our CEO as an expert.
• 54:14
  Speaker 7: When we demoed it to her she was like oh my gosh, she's blown away.
• 54:17
  Speaker 7: It's fantastic.
• 54:17
  Speaker 7: It knows about the areas where we have expertise in.
• 54:20
  Speaker 7: It knows about our policy wins.
• 54:20
  Speaker 7: It knows fantastic.
• 54:21
  Speaker 7: It knows about the areas where we have expertise in.
• 54:22
  Speaker 7: It knows about our policy wins.
• 54:24
  Speaker 7: It just knows everything.
• 54:25
  Speaker 7: So Chamber Chat we keep Chamber Chat relevant because we put out a lot of white papers, we have a lot of articles and blogs and things that we write and that we produce content on our website much like all of you, I'm quite sure and so we go out and we scrape our website every night to bring in that content so that Chamber Chat is always relevant.
• 54:44
  Speaker 7: It always knows what we're doing, where we're winning, so that we can create that content.
• 54:52
  Speaker 7: The other thing that we're doing we have a tool that's called Eva.
• 54:54
  Speaker 7: Eva is just our employee virtual agent, so different than chamber chat, because Eva is really more for onboarding new employees.
• 55:04
  Speaker 7: Questions about how do I put in a contract, how do I do a help desk thing?
• 55:09
  Speaker 7: I've lost my phone, what do I do?
• 55:10
  Speaker 7: That's what Eva does.
• 55:12
  Speaker 7: We have a new tool I just mentioned.
• 55:16
  Speaker 7: What if you could not only create member insights.
• 55:20
  Speaker 7: But you could also create new products because you've just uncovered information about where there are gaps in your organization.
• 55:28
  Speaker 7: That will increase member value.
• 55:30
  Speaker 7: So we have a legal risk alert tool now.
• 55:34
  Speaker 7: So what that does is it's going out and we're scanning a bunch of different points across globally actually, and then we're scanning a bunch of different points across globally actually, and then we're marrying that with internal data and we're surfacing what's the likelihood of pending litigation.
• 55:50
  Speaker 7: So imagine something like airbags.
• 55:54
  Speaker 7: If, all of a sudden, there are more commercials about airbags, there are more accidents, there are more fatalities.
• 56:01
  Speaker 7: There are all these things going on about airbags.
• 56:02
  Speaker 7: There are more accidents, there are more fatalities.
• 56:02
  Speaker 7: There are all these things going on with airbags.
• 56:04
  Speaker 7: There are advertisements that are happening on websites.
• 56:06
  Speaker 7: We've got TV commercials.
• 56:08
  Speaker 7: We've got advertisements on LinkedIn, stuff like that.
• 56:10
  Speaker 7: Right, we're monitoring all of those bringing everything in, creating an algorithm to see this is a high likelihood of pending litigation.
• 56:21
  Speaker 7: And now, who wants to know about that?
• 56:23
  Speaker 7: Who cares?
• 56:23
  Speaker 7: There's a number of our members who care about that.
• 56:26
  Speaker 7: They want to know what's coming around the corner and then what we might do, because you know we do a lot of really cool stuff at the chambers.
• 56:32
  Speaker 7: We might say well, we also know what's going on with some of the in the courts.
• 56:37
  Speaker 7: We know what judges this might go to.
• 56:40
  Speaker 7: We can also help you to prepare to defend against a certain litigation.
• 56:44
  Speaker 7: We have our customer insights tool right.
• 56:49
  Speaker 7: So, even though we were listen, we've all been able to do some type of analysis on our customers in the past.
• 56:54
  Speaker 7: The thing is that it took so long.
• 56:57
  Speaker 7: Right, we have a grant writing tool that our foundation is very excited about.
• 57:02
  Speaker 7: We we work with a lot of grants.
• 57:05
  Speaker 7: Some of you may, some of you may not.
• 57:07
  Speaker 7: We were about to augment our staff by hiring two people to get started on responding to a bunch of grants that were about to come in late 2024, 2025.
• 57:18
  Speaker 7: Instead, we said, no, we'll just build right.
• 57:21
  Speaker 7: We've got the grants that we've won in the past.
• 57:23
  Speaker 7: We've got the grants that we didn't win in the past.
• 57:26
  Speaker 7: We know all about our organization.
• 57:28
  Speaker 7: We know all about ourselves.
• 57:29
  Speaker 7: Let's build a tool.
• 57:30
  Speaker 7: So we did that.
• 57:32
  Speaker 7: We built a tool, so we now have a grant writer.
• 57:36
  Speaker 7: Being able to fully respond and prepare a grant response often took us upwards of 40 hours.
• 57:42
  Speaker 7: Some of that was also just built into the handoff time.
• 57:45
  Speaker 7: I see some people nodding because I've got I do my piece right, and then I send it over here and then somebody else does their piece, and then maybe somebody hasn't gotten to it yet, so maybe there's a little bit of a delay and I've got to wait for them to do their piece and then somebody ultimately has to review it right.
• 58:00
  Speaker 7: It takes, it takes up to a week, which before.
• 58:05
  Speaker 7: How were we going to solve for that?
• 58:06
  Speaker 7: Well, the same way we always did, we'll add new people.
• 58:08
  Speaker 7: But adding new people you can't always do that Because, as I mentioned before, we don't have unlimited resources where we can just keep adding headcount to a problem.
• 58:18
  Speaker 7: So now our grant writer gives us our first draft of our grant in under one minute, and all the team does now afterwards is they go and review it.
• 58:27
  Speaker 7: They review it for accuracy, they customize it, they just make sure it's accurate, and then we're done.
• 58:31
  Speaker 7: So I wanted to walk you through some of our lessons learned, because my hope is that you'll be able to take at least some of these and incorporate them into your journey.
• 58:43
  Speaker 7: I think you're all at different places in your journey and so some of these might stick with you a little bit.
• 58:51
  Speaker 7: Remain agile.
• 58:51
  Speaker 7: This technology, as you guys all know.
• 58:56
  Speaker 7: It just keeps changing.
• 58:58
  Speaker 7: Every time I do a presentation and then next month I have another one scheduled, I've got to redo it.
• 59:02
  Speaker 7: It's so much work.
• 59:03
  Speaker 7: I've got to redo it because it's changing so quickly.
• 59:07
  Speaker 7: The second one is get executive buy-in, because it's going to have a big impact to your budget if you want to do this right.
• 59:15
  Speaker 7: It's not just tech right.
• 59:19
  Speaker 7: Technology is the driver, technology is the disruptor, if you will.
• 59:25
  Speaker 7: But this really is not just about technology.
• 59:27
  Speaker 7: This is a cultural shift.
• 59:30
  Speaker 7: This is something that is going to come in and potentially disrupt your business.
• 59:36
  Speaker 7: You need to be asking yourselves how is this technology going to impact my core competencies?
• 59:43
  Speaker 7: If you're not asking that, chances are somebody else is already thinking about it and maybe building a thing.
• 59:50
  Speaker 7: So be ready.
• 59:53
  Speaker 7: Address the fear.
• 59:54
  Speaker 7: A lot of employees are scared.
• 59:56
  Speaker 7: They keep hearing tech is AI is going to take my job?
• 59:59
  Speaker 7: It might.
• 1:00:00
  Speaker 7: It might not, but it's definitely going to impact it.
• 1:00:02
  Speaker 7: And so there's fear, and when there's fear, you might not necessarily see the levels of adoption that you'd like to see.
• 1:00:08
  Speaker 7: So sticking with what works today is probably the most riskiest thing that you can ever do.
• 1:00:17
  Speaker 7: I promise you that I'm usually not that great at like giving bets or placing bets.
• 1:00:23
  Speaker 7: This one I will place money on right.
• 1:00:25
  Speaker 7: If you just keep doing what you're doing in your association and you think that that's enough and you're going to be good and your members are still going to be happy and engaged, I can tell you they probably aren't.
• 1:00:37
  Speaker 7: They just aren't.
• 1:00:38
  Speaker 7: So really, you have to start thinking about what is the next thing that I might need to do to keep my members engaged, because they're already thinking about it and if you're not solving for that, somebody else will.
• 1:00:52
  Speaker 7: So if we keep doing what we've always done, it's inevitable that you will get left behind.
• 1:00:57
  Speaker 7: We all want to stick with the cash cow that we know today.
• 1:01:00
  Speaker 7: It's probably not going to be the thing that moves you forward in the future.
• 1:01:04
  Speaker 7: So I'm going to highlight this Klana case study because I think it's really very relevant.
• 1:01:09
  Speaker 7: So Klana is a payment organization.
• 1:01:14
  Speaker 7: They're a large organization.
• 1:01:16
  Speaker 7: Well, they mentioned about a month ago that they are not going to renew their contracts with Salesforce or Workday Anybody.
• 1:01:25
  Speaker 7: You guys know who.
• 1:01:26
  Speaker 7: Salesforce is right, anybody use Salesforce.
• 1:01:28
  Speaker 7: Salesforce is yeah, salesforce is a big deal.
• 1:01:32
  Speaker 7: Workday that's big of a deal.
• 1:01:35
  Speaker 7: But they said no, we don't need you anymore.
• 1:01:37
  Speaker 7: We've got this thing called generative AI and we're trying to cut costs within our budget and you guys take up a big chunk of our budget so we're not renewing.
• 1:01:45
  Speaker 7: So imagine Salesforce now or Workday, as huge as they are now facing the fact that, wow, some of our customers may decide that they don't actually need us anymore.
• 1:02:02
  Speaker 7: Right, because now they've got all of their data in their databases that they can now use AI to make those connections and to surface the insights that Salesforce was able to do for us.
• 1:02:15
  Speaker 7: That's a major disruption, guys.
• 1:02:18
  Speaker 2: Everyone.
• 1:02:19
  Speaker 2: Thank you so much for tuning in to today's special edition episode with the day one keynote highlights from Digital Now 2024.
• 1:02:26
  Speaker 2: Reminder, if this event sounds of interest to you, that you can capitalize on our early bird special right now by going to digitalnowsidecarglobalcom.
• 1:02:36
  Speaker 2: Thanks everybody, we will see you next week.
• 1:02:41
  Speaker 1: Thanks for tuning in to Sidecar Sync this week.
• 1:02:43
  Speaker 1: Looking to dive deeper?
• 1:02:45
  Speaker 1: Download your free copy of our new book Ascend Unlocking the Power of AI for Associations at ascendbookorg.
• 1:02:53
  Speaker 1: It's packed with insights to power your association's journey with AI.
• 1:02:57
  Speaker 1: And remember Sidecar is here with more resources, from webinars to boot camps, to help you stay ahead in the association world.
• 1:03:05
  Speaker 1: We'll catch you in the next episode.
• 1:03:07
  Speaker 1: Until then, keep learning, keep growing and keep disrupting.