Ask Us Anything: AI In Internal Comms

Speaker A: Welcome everyone, and thank you so much for joining our first ever Ask Us Anything session. Today's session is exactly what it sounds like, a chance to ask what's on your mind about AI and internal comms. We know AI can feel like a topic that generates more heat than light right now, especially for internal comms professionals who are trying to figure out what it actually means for your work. every day. So we wanted to create a space where you could ask the things you've been wondering about and maybe hadn't had the right venue to ask. To kick things off, my name is Christina, and I'm the product marketing manager here at Contact Monkey. And I'm joined by Dan Grossi. He's our senior product manager who's been the brains behind our AI features. So I will let Dan introduce himself quickly.

Speaker B: Hi everyone. Thanks, Christina. And thank you. Big thank you to you and the rest of the marketing team for pulling this webinar together. together. It's really great to be here and look forward to the discussion over the next little bit. I mean, first off, I guess you're, you're, you're, you're too kind. I mean, this is really a team effort in terms of our development of AI features. It's really everyone across product design and engineering and even go-to-market that are contributing to AI features at this point. I just consider myself lucky that AI has become a major focus of my role. And I say that because I'm a big fan of AI. I've been a longtime AI enthusiast, active user. I spend a lot of my time experimenting with AI and new ways of working. So I'm really excited to be in this position. Maybe just a quick, like, mention of my career arc, because I think it's kind of relevant to the overall conversation. My educational background is in software development. I have a degree in computer engineering, started my career as a software engineer, quickly found that I really preferred to be in a product role. And so I transitioned and have been doing product management for a little while now, about 20 years. And I can honestly say that this last little period, you know, call it the last year or two, has really been a game changer in terms of the way I work because of AI. For me, it really has lived up to the promise of being transformative for the good. And so, you know, I'm really, I've been really reenergized in my work. It's freed up a lot of time for me to create. And so a big part of my role now is figuring out how we can bring more of those same transformative, beneficial experiences to our Contact Monkey customers.

Speaker A: Love it. And how are you using AI yourself today?

Speaker B: Yeah, there's a lot to mention on this front, so I'll just kind of bucket it basically. I think for me, it really is like it feels as though I have a team of assistants at any given point in time. And so for a lot of the more tedious work, let's call it the less energizing work. So, you know, document formatting and writing and ticket writing for engineers, slide preparation, turning those notes and thoughts into something much more polished. It really has been a lot more efficient. I can really concentrate on just like having a master document and then from there kind of spinning off different formats as needed. And I think there's a really big parallel there actually for internal comms where, you know, maybe moving to a model of having a master document and then being able to similarly like spin off those summaries or, you know, a short blurb, you know, a Teams post, etc.

Speaker A: Mm-hmm.

Speaker B: Research has been a huge unlock. You know, there's a lot of scientific research that's available for a lot of the features that I'm working on now. And so to be able to have a project where I can attach those research papers and have AI surface the insights that are relevant to my feature without having for me to read through 40 pages of like really dense, complex scientific findings, that's really been a big level up. And lastly, I mean, having a sounding board, a thought partner. So the same way that I feel like I have a team of assistants. I feel like I have a copy of my boss who's there on demand that I could bounce ideas off of, get ideas, get feedback, mitigation strategies, talk about technical feasibility. So that's been really valuable to have that kind of back and forth. And lastly, maybe just quickly because there's so much here, but like a big one that's been really energizing for me is to be able to create more. So via vibe coding to be able to spin up a prototype really quickly so that I can come to a first meeting, not just with a requirements document, but like an actual functioning prototype. And that really jumpstarts the conversation. And I feel has really cut down the time to development pretty considerably. I could go on, but I think I've been talking already a lot on this. So, yeah, how about yourself though? I know you're a big AI user. So, Uh, what have you been using it for?

Speaker A: Yeah, so I kind of do an element of internal comms through enablement work. So I use the ContactMonkey platform to send newsletters. And because we don't have a lot of stakeholder review embedded in our workflow, Confidence Check is my pal. And I use Claude to help me research and consolidate a bunch of different sources of information. So I don't have to search from search in Notion and Slack and multiple sources.

Speaker B: So.

Speaker A: Yeah, that's how I use AI in a nutshell.

Speaker B: Awesome. Yeah, glad to hear the confidence check usage there. Always, always happy to hear it. Obviously.

Speaker A: Well, yeah, so since this session is all about learning from each other, we have a first question for the audience, and that is, what would an IC-specific AI tool need to do for you to actually adopt it? So if you can all just leave your comments in the chat, that'll help us kick off the conversation. And in the meantime, a few housekeeping notes before we officially get started. So the session is being recorded and you'll receive it in your inbox by tomorrow. And at the bottom of your screen, you'll see both the chat box and the Q&A box. So please use the Q&A box separately for your questions and the chat box to write to us throughout the event. We only have about 45 minutes today, so in case we don't have a chance to answer your questions live, we'll do our best to follow up with responses, or feel free to email us at marketing@contactmonkey.com. And at the end of this session, you'll see a survey pop up on your screen, and we'd appreciate if you took a few minutes to respond. So let's get started. We'll first tell you a bit about how we see the future in internal comms with AI. But before we get to that, we'll flip the script for a second. We're gonna launch a poll, a quick poll to get your feedback. And of course, because the conversation goes both ways, we'd rather spend the next 45 minutes talking with you instead of at you. So you'll see a poll pop up in the next few seconds here. Go ahead and take a few minutes to leave your responses. And in the meantime, Dan's gonna walk us through the results of the previous poll that we launched in our original confidence check session. Yep.

Speaker B: Thank you very much. I'm gonna fire up my screen share.

Speaker A: All right.

Speaker B: Great. So yeah, let's take, let's take a quick look at the same questions. These are the same questions that we asked in the confidence check webinar back in November. And these are the results that we saw then. Not to bias any of the responses now, but so was pretty good back in November, already seeing quite a bit of of usage at that time. So pretty even split here, you can see, between regular use for content creation, curation, and QA. And really kind of strong results here as well in terms of it being approved and org-wide adoption. And then kind of tapers off quite a bit into, you know, the piloting, more cautious approach. So really curious to see if there's, you know, a trend line that shows up in our results here now that we're asking the questions again. Definitely anecdotally, we've, we've seen, you know, through all of our conversations, definitely an uptick in increased interest and adoption in AI. The next question. So how does your organization perceive the value of AI? So again, you know, here the leading response, high strategic value. So organizations really coming on around to understanding the big boost that AI can provide for them. Useful for select tasks, and then still a very solid cohort in the, you know, cautious approach. And then kind of in the air bars for kind of the more neutral and skeptical stances there. Which of the following are formally approved for your work use at your org? So definitely the standout here was Copilot. Not very surprising, but actually surprising to see that there was pretty solid usage even amongst other tools. So ChatGPT, Gemini, Was another one. That's a very strong contender, something that we use heavily here at Contact Monkey. Great results, and it's actually the thing that's powering our confidence check at the moment. So yeah, definitely wanna see what the trend is now, how the results look. And lastly, which parts of your internal comms workflow would you want the most help with? And here, you know, an even split more or less across the board, you know, maybe a slight edge here to understanding analytics and drafting content. And, you know, we'll definitely see that kind of bubble up in the next portion of the webinar as we dig into Contact Monkey and look at some of our features that we've already shipped on the drafting content side. But yeah, again, curious to see what the trend is here.

Speaker A: Alright, we have our results. Alright, let's take a look.

Speaker B: Let's take a look indeed. Okay, let me skip back here real quick. Great. And I mean, it's fair to say this sample is also different. So you know, there's some variation expected just by, by that very nature. But nonetheless, in our very non-scientific approach here, I think an interesting exercise. And so, yeah, 50% on the regular use. So let's call that a statistically significant bump up from the 36% that we saw last time around. Exploring only down in the 5% range. And so that was previously up at 12%. So, yeah, I mean, you know, naturally, at least that fits with our hypothesis, fits with what we're hearing on the ground and in our conversations. I mean, naturally, you all are here because you're interested in AI, but that's kind of a level playing field because last time that we were talking about confidence check and AI. So. Very similar audience on that side of things. Let me skip ahead now again to question 2. How does your organization perceive the value? So high strategic value and promising but cautious. Okay, I mean, interesting to see that, you know, maybe a bit of a bump up, let's say, on the promising but cautious side of things. But suffice it to say, you know, the skepticism is very low. in both the results from last fall and now. So obviously, naturally, a huge cohort of folks that are actively using it in their day-to-day or otherwise exploring it and using it for select tasks. All right, skipping ahead. Okay, yeah, our bigger cohort for Microsoft Copilot, 73%. So Definitely that, that's seen a lot of increased adoption. It's, it's the natural choice for organizations that are in the Microsoft ecosystem. But let's take a look at maybe the other adoption on other tools. So seeing quite a bump up on ChatGPT adoption, and this is like a multiple, multiple choice selection. So a lot of folks using ChatGPT, you know, good cohort of folks that are using Gemini. As well. So a good assortment of tools here. And naturally, Copilot stands out as, as a unique use case and a unique opportunity that, that we're aware of. And let's see. All right, internal, would you want the most help with? So drafting content, 82%. Definitely a huge cohort there. And as we saw last time, kind of tied, let's say, as a front runner with understanding analytics. So that is great to see. And so that trends pretty well as we saw it before. But I think a lot of kind of strong demand and desire, you know, more or less across the board. And I mean, we're really trying to take a breadth-first approach as well on our side. But understanding that there are a couple leaders that we want to pay a little bit more attention to and kind of, you know, push out sooner than later and prioritize those efforts. Great. So yeah, I appreciate everyone weighing in on the survey, on the poll there. If you have any questions about that or comments, again, the chat is open, the Q&A panel is open. Don't be shy. Let's get our questions in. We really want to, you know, be able to, to address anything that we can in this, in this session. But otherwise, with that, I will kind of jump ahead in the slides and really speak to kind of the overarching, you know, set the stage. Now that we know a little bit more about each other, kind of calibrate on your usage of AI. Really wanna set the stage in terms of what our vision is, the direction that we're generally committed to on the AI front within Contact Monkey. And I mean, this is really born out of a very acute need. And so this is what we're looking here. This is information that comes out of our annual survey that marketing runs. And this is a great body of work. I definitely plug the survey results that you can have access to via a link that maybe we'll pop that into the chat. But the theme that we really saw is that organizations are asked to be doing more with less, right? So the mandate is growing, but the headcount isn't. If you find yourself in this boat, then I guess as a consolation, you're not alone. And, you know, how can we help you? The same kind of way that I, I'm feeling the transformation and I'm feeling kind of superpowered and superhuman with AI tools. How can we equip you with those similar tools so that you can do more with the existing, you know, headcount that you have on your team? And, you know, interesting that 2/3 of the organizations that we've surveyed have 5 or fewer people on their team. 82% of leaders are saying that comms is valuable, but the budgets and headcount haven't quite grown to kind of meet that same demand. And so this again is, you know, kind of what we're looking to, you know, really address with the functions that we're bringing to Contact Monkey. In terms of, you know, how we, you know, view the user journey. as you create a piece of communications. You know, this is a divide and conquer approach, so to speak. Look, so how can we distill down the user journey and then approach each of these kind of like segments in the journey appropriately? So, you know, if this sounds familiar, kind of this workflow from starting at the collection phase where you're having to chase down information, Via multiple sources of truth and multiple people trying to keep up with your timeline and what you had, you know, roughed out in terms of your comm strategy. Once you've then chased all of that down, now comes the time to, you know, put proverbial pen to paper, rewriting updates that you might have gotten from different stakeholders and different groups. Digging through old copies of your campaigns for inspiration or seeing how much you can reuse from that and kind of going through a few edit cycles. And that's just on the copy side of things. Then there's naturally like, how do you lay that out? How do you make that visually interesting and easy to follow? And so fitting that content to your templates, resizing things, reformatting it, reformatting as content changes. So there's an entire kind of portion that's spent here in the design phase of this piece of comms. And then once you have things in a place where you're happy with, then it's over to make sure that it has kind of the requisite number of eyes that get on it to make sure that there's no mistakes. making sure that you're on message, making sure that the right people who are, who need to approve are approving. Those people aren't always available to review, to proofread. You're having to track down approvers. And, you know, this is where we hear a lot of the pre-send anxiety, right? Because one error could potentially cause a lot of confusion. If there was an incorrect link, something that was missed. And now you're sending this out to 10,000 or more people, that there's a lot of work that goes into kind of remedying that. Once you have the reviews, you've sent things off, even just the send process of, you know, managing distribution lists and identifying the right audience, who you should be sending it to, and when should you be sending it, like when is optimal. I mean, those are all on you. I mean, again, this is in the abstract. This is assuming that you don't have Contact Monkey available and all the goodies that we have for you, but just kind of in the abstract, as you know, as for the workflow itself. Then once you've sent it, the reporting. So pulling data out of whatever tools you have available, tracking things in spreadsheets, analyzing and trying to find insights by hand. No benchmarks to really improve against or look at for a kind of a reference point. And so this, you know, this is everything that goes into a single piece of comms, and this is what, you know, you all on the call are being tasked with. And, you know, if this resonates or, you know, curious if there's anything that we may be missing here, or maybe that you bucket differently. I think that's another maybe great topic for the chat or the Q&A that we could get into. But this is kind of our mental model of the process. Now, the transformation that we're really looking to make, and this is kind of how we actually look at it with respect to Contact Monkey and our, you know, agentic future. It's less this linear workflow where it's kind of this, you know, one and done for a piece of comms. Everything feeding into each other, being able to talk to one another and really leveraging AI as your, your, your overall copilot, your overall assistant. You're always in the driver's seat. But again, how can we unlock that team of assistants that have your back? that thought partner, that sounding board at your disposal to make the process easier, more efficient, and ultimately create a better quality product. And so taking that same linear workflow, mapping it here, and how we're dividing and conquering and layering in AI where it really makes sense, it can help, starting at the curation process. So really, rather than having to chase down source information yourself from all these multiple sources of truth, sources of information, what can be done to help you curate? And, you know, something that's already connected to your systems of record, your intranet, et cetera, that can already create an initial draft for you. And that initial draft in Contact Monkey, how can you then, you know, fit that content With the assistance of a design agent, something that we already have in a live beta. Co-author is, is the name. So being able to fit that content to a professional layout, you can interact with it using conversational prompts, natural language. And it has accessibility in mind. It has your branding guidelines in mind. to really assist on that formatting and fitting and sometimes finicky process. And we'll see more of that in a second. Next up, Confidence Check. So this is something that we've now rolled out for a few months now. I've seen a lot of good results, have had a lot of great testimonials. And Confidence Check is the thing that has your back. This is the thing that's meant to address the pre-send anxiety. So how can we leverage AI to review content for errors, compliance, accessibility, and, you know, make sure that it's overall effective and error-free before sending? So that's another thing that we're gonna take a quick peek at in the demo phase in just a sec. Then over to delivery, and maybe this gets overlooked quite a bit because, you know, we know that it's not as simple as just hitting the send button. How can we equip you with an AI agent, a delivery agent that delivers content through the right channels to the right audiences at the best time and take a lot of that, you know, decision-making or not decision-making, but inform you and then equip you such that you can make a decision and help you here so that you're not kind of juggling distribution lists and kind of creating things on the fly here. An insights agent. So as we saw from the polls and as we've been hearing, how can I draw better insights from my analytics, from my metrics data? And this is the thing that's monitoring all of that, surfacing the trends to you, answering your questions. So that kind of natural language querying process that you can have. And this is really kind of at the heart of what would drive a lot of the improvement. So all of these insights that are drawn both for you, both for the other agents, this is really what feeds back into the entire process here.

Speaker A: All right.

Speaker B: And yeah, okay. Lots to talk about. And yeah, we gotta definitely leave time for Q&A. So the Contact Monkey pilot, that's what's at the heart of all of this and really orchestrating the entire process. So that's the interface layer that really allows the different agents to surface relevant data to one another so that we can continuously improve the entire process. All right, time flies when you're having fun. Okay. So I just want to go ahead and maybe skip ahead to, let's say, the, the quick demo portion right now. I do want to splash up our co-author. I have a quick demo vid that I'm gonna show here. So this is our design agent again. So looking at how we can take a quick prompt and go from a blank canvas to having a nice solid first draft that we can then build on and tweak very, very quickly. So we see here we're creating an email reminding employees about benefits enrollment. We have a quick callout as to the sections that we wanna see in there. And we can see it being built before our eyes. And this is something that's always, you know, I find pretty cool. You can kinda take a sip of, of coffee or 2 as you watch co-author go ahead and, you know, really create a, a pretty solid first draft of an email that you can then go and kinda tweak the content. And you can do that via the, the co-author. A lot of use cases here, but kind of, I'll, I'll leave it at that for, you know, in the interest of time. All right, so that's co-author in a nutshell. I did just want to touch on confidence check. I know a lot of folks that are on the call have already seen this and are using this in their daily workflow. So I won't spend a whole bunch of time here. For those of you who haven't seen it, the eyeglasses up here in the top toolbar— got logged out naturally. All right. Maybe that's a, that's a good sign that we can circle back to that demo. But one thing that I did want to call out that is on the newer side with respect to confidence check. And that is new functionality that we added in terms of a custom check. A little shout out in our help file here. We have a number of, you know, essentially little mini prompts and rules that via custom check you can tweak to your own circumstances, to your own style guidelines, to your own tone of voice, custom dictionary banned terms. Feed these into the settings, and which then feeds them into the confidence check, which then goes ahead and surfaces those violations. And there's a lot of goodies in here. So again, custom dictionary for anything where we might have spelled product names incorrectly. Invalid URL keywords is another really great one to make sure that you're not sending things from a preview server, for example. Style with respect to your date formatting or, you know, number naming conventions, titles, etc. Make sure you're spelling the CEO's name correctly. This is another favorite of mine, missing time zones. So for, you know, if you're operating across multiple time zones, Making sure that a time zone is specified anytime that you're mentioning a time and your tone of voice. And this is a big one. And this is like on the AI front, you know, if I could pass along a tip, it really is about getting your— nailing your tone of voice for different audiences. Maybe that's your executive tone of voice. Maybe that's your general comms tone of voice and having those available in your own little database, your own little spreadsheet so that you could call on those anytime that you're running a prompt. And then following this type of structure as a kind of little general AI tip when you are drafting. A little mention of the topic, the audience that you're targeting to, the voice that you're writing from, the type of structure, and any constraints. So how long do you want this to be? Do you have any conventions or branding that you'd like to pass along? So that's kind of just like a handy general AI tip. And this is the prompt that we use in the example for, for co-author. Okay. And another one that we're, we're digging into now. So not only knowing your own voice in terms of how you, you're presenting information. To your readers. But really, you know, AI gets much more useful, not just knowing about, you know, who is speaking and the voice that you're using, but who you're actually speaking to. And so we're digging into audience segmentation and how can we segment, you know, the audience users today. And really curious as kind of another conversation point. Are you using audience segments today? Are you doing that segmentation? And which segments are you using and applying? Is it tenure or function, mode of usage or level? And so kind of, you know, the little tip to pass on here that we've really dug into and found along with the kind of scientific research in this area is that it's really much more about reading modes and constraints. So how does someone consume communication? Rather than just the blind demographics of it all. And that really tends to produce much better actionable guidance. So a skimmer versus a cascader versus an executive versus a disconnected frontline worker. Those are the main kind of areas of differentiation in terms of how your reader is going to really kind of take away and process the piece of comms that you're sending. I'll go ahead and stop there, make sure that we leave room for questions. So yeah, let me turn it over to you, Christina. I've been trying to keep an eye on the chat and the Q&A, but yeah, hit me.

Speaker A: We have one more poll to launch.

Speaker B: Oh yes, of course.

Speaker A: So let's see what our audience thinks. This is just a follow-up from what Dan shared so that we can understand, um, how often these use cases come up for you. So take a few minutes and then we will get into Q&As. And just another reminder that there's 2 separate, uh, boxes at the bottom of your screen. One is for chat, one is for Q&A. Please use the Q&A one to ask your questions. We'll leave it up for a few more seconds here. All right. Can you see the results, Dan?

Speaker B: Yes, I can. All right, great. All right, so poll question number 1, do you have defined tone and style guidance? So yes, The leader is yes, loosely defined, but inconsistent in practice. So combining that with the other yes, documented and actively used, so about 8% on that actively used. So yeah, I mean, solid representation on it, you know, having that tone and style guidance, that's definitely the first, the first step. So, you know, great to see kind of that representation. And again, that's kind of one of the bigger tips that I can pass along. The voice of sender is really important. That's the thing that's gonna elevate it beyond like, this sounds AI generated. And that is one of the questions that we got ahead of time. So really dialing in what your, what your voice is, and it doesn't have to be something really elaborate. We've seen really great results with, you know, just a sentence or 2 really distilling you know, kind of the main adjectives that describe the tone of voice that, that you want to represent. So, yeah, an important piece of the broader how do I leverage AI effectively conversation is really kind of dialing in your voice of sender. And then also distilling those like very long lengthy branding guidelines, style books that you might have in your corporation that might be 60, 70 pages long. AI is great here to even try to just distill that down to like, what are the things that you really care about? What are the things that you're gonna check or that you would wanna check before an email goes out? Those are the types of things that you can even translate into custom checks for a Confidence Monkey— confidence check rather, for example. All right, what else? So we got reader segments. Yes, basic segments only. Is by far and away the largest segment here. So not quite seeing it on the documented and actively used side. So this is, I think, an area of real opportunity, untapped potential here. There's a great deal of scientific research going into this with virtual focus groups. And so, you know, more to come on this front from ContactMonkey. But, you know, having that base foundation at least about having those basic segments is important. And I think this is an area that AI can really leverage to help you get ahead of confusion and questions that might be asked from your readers before you actually hit the send button. How often do you tailor content for different employee audiences? Yeah, so I mean, you know, it's great to see that there is regular segmentation and tailoring that's done here. That does echo a lot of what we've been hearing in our kind of one-on-one conversations with customers. And again, this is another— this is the next generation. The next evolution of audience segmentation is, okay, let's apply that information and how can we better tailor and personalize, you know, a few different streams of communications for these particular segments. So overall, we get the best engagement, the best alignment, and the best action.

Speaker A: Thank you, Dan. So just so the audience knows, we received quite a few questions in advance, so we'll get started with those. and anything new that comes through, please again, chat us in the Q&A box. So the first question was, how can AI help a small, under-resourced comms team shift time from production to more strategic work?

Speaker B: Yes, that's a great question. And that's kind of the overarching thesis of this chat. So like, hopefully, we've already touched on that quite a bit as I've we kind of dove down the rabbit holes of the different features and functions that we already have in Contact Monkey, the things that we're looking to kind of phase out in the future as well. But yes, have your voice of sender down, understand who your audience is, have your spreadsheet of tone and voices ready to go, fire up Co-author, have— take your little prompt essentially from your brief, from your planning spreadsheet or document, paste that into Co-author. You could really get a very solid, you know, first draft of something. And then on the other end, this is kind of our pairing. You know, how can you go to a first draft very quickly? How can you go to a finished piece of comms very quickly with Co-author? And then having that safety measure of confidence check to double-check, you know, your email, make sure that there's no errors in there, and really drastically reduce that time that a lot of people are getting bogged down in the content creation side. So that unlocks you to do, you know, frankly, the more fun part, maybe the more energizing part of strategy and direction.

Speaker A: Great. Thank you. The other question we received is how do you or we, I believe it's referred to Contact Monkey, referring to Contact Monkey, how do we protect internal data?

Speaker B: Yeah. You know, security is, is a huge consideration on this front, right? And so your organizations take this very seriously and so do we. So, you know, a number of principles here, transparency being front and center. So we want to be very clear about where we're using AI and how we're using it. We have a public AI policy document that really outlines all of that information, all of the commitments that we make and kind of the tenets that we adhere to. You know, obviously no training, there's no retention at third parties based model providers based on your, your data. You know, that doesn't happen. We are leveraging state-of-the-art models as well that, you know, they— there's a great deal of, of time and energy and investment that's spent there on governance and controls and bias mitigation and evaluation. So there's kind of a number of layers here. The biggest one on our side, on the application side, is really constraining the scope and minimizing the data that's even sent to a model, to an LLM. So, you know, in the case of confidence check, in the case of co-author, we're only sending over the email contents itself. There's no information there about the recipients, you know, PII, et cetera. And we're also constraining what the LLM, the AI, has the ability to do. Right? So they're offering you feedback. It doesn't have the ability, you know, right now with our existing, you know, tools to send an email. So there isn't that risk that's even a possibility. And there's always the human in the loop. So you're always at the controls. You're the decision maker. We're presenting you with feedback and with information. But, you know, you are the one that makes the call. This isn't, you know, an autonomous layer that's just kind of running all over the place doing things without your knowledge. It doesn't even have that ability.

Speaker A: We got a question live here about analytics. So right now in Contact Monkey, we have to pull reports from each team, then combine them to get a big picture for all teams, and then analyze the reports. Are there plans in AI or with AI to make this easier?

Speaker B: Yes. Yes would be the short answer. That is definitely on our radar, on our, you know, short-term roadmap. You know, of the agents, I can say that the Insights Agent is, you know, one of the shortlisted in terms of kind of in the development process. And so they're actually, you know, a shout out here as well for the Analytics API. That is something that's available today that would allow you as one approach, you know, programmatically to be able to ingest all of the Contact Monkey metric data across teams. But, you know, yes, we— the making it easier to get more access to your data. and more access to the insights from that data is really the driving force behind the Insights Agent. So this is something that for sure is well and truly, you know, on our minds and actively being, you know, discussed and explored and researched and, you know, implemented, being implemented as well.

Speaker A: And I think we have time for one more before we follow up in writing with the rest. Question is, what evidence have you seen that AI improves efficiency or outcomes? And does AI-written content perform well with internal audiences?

Speaker B: Right. Yeah. So, I mean, I think, you know, the proof is in the pudding. And, you know, that's definitely one of our principles here is that this isn't AI for AIs. sake either. And so I think really, you know, when I talk about the proof, it's seeing the results of Confidence Check and seeing the results of the early results of Co-author in the discussions with our users and the testimonials that are coming back. You know, a number of organizations have really adopted Confidence Check as part of their, you know, daily workflow. And so we've heard it firsthand. And so we're gonna continue to kind of build down that path of having, you know, real results. You know, I think there was a portion of that question, I guess, that speaks to it not just being, you know, generic AI. And so that's again, that kind of element of voice of sender, you know, getting that nailed down so that it isn't that generic AI voice that comes across. And there's, you know, there's certain KPIs that you can even adopt within your organization, you know, start to maybe more closely follow and measure the time to initial draft and the time to completion for a piece of communications.

Speaker A: Mm-hmm.

Speaker B: Maybe even track the number of revision cycles that something goes through and even track your error rate. you know, post-send? Are you catching, you know, more errors? And we have been seeing that to be the case with, with our, you know, first agents in these areas. And we're gonna continue that pattern, you know, over to the other agents with, with insights delivery, etc.

Speaker A: Awesome. All right. Well, we are at time, so we'd love to continue the conversation. After the webinar ends, there will be a survey that pops up letting us know if you're interested in working with us to enhance our products and, and the features that become available to you. So please take some time to respond. And again, we'll follow up with a webinar recording and the questions, the remaining answers that we've received. So thank you everyone so much for joining. Thank you, Dan.

Speaker B: Thank you.

Speaker A: Yeah, we'll see you soon.

Speaker B: Yep, look forward to continuing the conversation.