Writer and the Real ROI of AI at Work, Beyond Productivity Metrics

[00:00:03] Welcome to AI at Work, a podcast which is part of the Tech Talks Network. And in this podcast, we're going to venture into the transformative influence of artificial intelligence inside the workplace. And our discussions will focus on both the remarkable breakthroughs, but also the complex challenges of integrating AI into our everyday business functions and workflows.

[00:00:30] How often do we talk about AI in marketing without asking what it actually feels like for the people who have to use it every single day? This is just one of the many questions that keep circling around my mind as I sat down with someone who has lived through several waves of transformation and yet still finds new ways to make teams faster, sharper, and most importantly of all, human.

[00:00:58] So today on AI at Work, I'm joined by the CMO of Writer. And he's had one of those careers that blends analyst mindset, engineering roots, product marketing intuition, not to mention a million mile view of how teams adopt new technology. His name's Diego. He's going to bring with him today a mix of wisdom and humor that has made this conversation as enjoyable as it is grounded.

[00:01:29] And together we will go everywhere from geo cities, nostalgia to the reality of agentic marketing and why leaders have to change before their teams can. So if you want a window into how modern marketing really shifts when AI becomes part of their daily workflow, this is one of those that you should enjoy. And I suspect you will hear a few moments that feel surprisingly familiar in your own workplace.

[00:01:58] But before I get my guest on today, I want to give a quick thank you to my friends at Denodo. We're playing a big part in support in this show because one of the questions I hear more and more from listeners on this podcast is why does AI succeed or why does it fail? Because let's be honest, AI is moving fast, but success is often still elusive.

[00:02:22] Now, most projects fail not because of the AI, but because the data foundation isn't ready. This is why organizations are increasingly turning to Denodo. Denodo delivers trustworthy and AI-ready data without the need to copy it everywhere. Essentially, you can optimize your lake house, accelerate agentic AI, and build data products that finally make self-service real and achievable.

[00:02:50] And with a powerful partner ecosystem, teams get to value even faster. So if you're ready to understand why your AI projects fail and how to succeed with AI, simply visit denodo.com and take control of your data world. But enough from me. Let me introduce you to Diego right now. So a massive warm welcome to the show.

[00:03:18] Can you tell everyone listening a little about who you are and what you do? Yes. Thanks, Neil. Thanks for having me. My name is Diego Lamonto. I am the Chief Marketing Officer at Writer. If you don't know about Writer, we are a full-stack generative AI platform. We specialize in the enterprise. We're really strong in the front office, marketing, sales, or places where you engage with customers. And I've been in B2B enterprise software for over 20 years. I grew up in product marketing. I was the head of product marketing at UiPath,

[00:03:47] all through our big growth phase from Series B to going public. And across my career, I think the theme has been sort of AAA. Analytics, then automation, and then AI. And of course, AI has kind of been under the covers the whole time. It's just that now it's hot. But that's where I've been focusing. We're talking around a lot of cool new stuff here and AI. And obviously, you've been in this for a lot longer than the hype. But Writer, Cobb, how did you get that domain?

[00:04:15] Is there a story there too? There is a story there. I'm not sure how much I could share. But the reality is our founders, May Habib and Wasim Al-Sheik. May, if you know May, she's a phenomenon. She's a firestorm. And she really drives so much of our growth and our trajectory. And she's really passionate about what we were doing. Reached out to the person who was sitting on Writer.com for a long time.

[00:04:43] And inspired them to sell to us, even though he wasn't selling to anyone. He just liked our moxie, so to speak. And it wasn't cheap, obviously. But I think it was a lot of influence and a lot of passion for what we were doing that won them over to give it to us. Love it. What a great story. And of course, looking back at your career, you've spent years inside fast-growing AI companies.

[00:05:10] So I'm curious, though, looking at your origin story, what early experiences maybe shaped the way you think about marketing leadership in a world where agents and automation are now increasingly becoming part of the team? Yeah. Yeah. You know, so when I first started my career, I started as an actually, I went to school for marketing and business. But I started as an engineer.

[00:05:33] And, you know, the dot-com days, I was just making websites for fun just because I found it interesting as a thing to do for my kind of enjoyment. And I ended up getting my first job as a web developer, you know, in the late 90s during the dot-com boom. Interestingly enough, I was making, I mean, this little quick little side tangent, and then we'll get to your question. I was making websites for fun, New York City, 90s, you know, indie rock movement.

[00:06:03] And I, like, before we were blogs, I used to have, like, a music page. And there was no blog software. There was no WordPress. So I just made this blog myself. And I was interning in an advertising agency during this time. And they were starting their internet division because back then it was like, what do we do with the web? Well, let's just go to our advertising agency and make a brochure site. And so I was sitting next to the guy who was starting the internet division, and I showed him what I was doing. He was like, oh, cool.

[00:06:32] We just got a big contract to buildcountry.com for CBS. We need people. You want to work for $10 an hour over the summer and do HTML for us. And I was like, I can't believe that that's what I – you're going to pay me to make websites. And so I actually finished school in the evening, and I was building websites. But I knew – I went through the whole engineering and building sites and being a developer, and I knew that wasn't, like, my strong suit. It was a hobby.

[00:07:00] So I wanted to get back to the business side, and I found product marketing, which seemed to be the perfect entry point for me into the business side of things, where I could blend my technical hands-on understanding of the technology with business and marketing and strategy and narrative and positioning. And I just fell in love with marketing, and product marketing specifically and marketing in general.

[00:07:24] And so to get to your question, what I learned early on is that people are – new technology is exciting to, like, 5% of us and to the rest of us. It's scary. And it is – for some, it's scary. For others, it's like a bother. It's like something I just – like, I got enough to do. I don't need to learn new technology.

[00:07:51] And so what I learned is that, you know, we have to understand the human psyche here. We have to make people comfortable with the technology, and you have to get them engaged and using the technology more and more. So I made my principles show people the art of the possible, tell stories. Don't just talk about the features and the capabilities because most of us don't care about that.

[00:08:15] They just want to know how will I survive with this thing becoming part of the work that we do. And the other part was make it easy for them to get started. Just as much hands-on. So we, you know, even today at Writer, we do a lot of hands-on workshops and, you know, hackathons and get people using things. And you just have to get people understanding it.

[00:08:36] So I had an early mentor during that first product marketing job who, when I was making all my slides and, you know, all my campaigns and everything that I was putting together, he really called out that I had a lack of customer stories and that the customer story was the most important thing. And let's start there. And he was right. And that just really, my marketing started to work a lot better when I made it more human and more about the story. So, yeah. What a great story.

[00:09:06] And listening to you today, I was getting flashbacks of my own and GeoCities days. Yeah, exactly. I used to have the blinking text, right? So it was Diego's music page, awful background. Like, basically, think about your background. You know, like, you know, the awful backgrounds, repeating patterns, right? And then linking text and just, but you know what? I loved it. It was very GeoCities branded type of experience. Love it. And fast forward to present day.

[00:09:36] Last week, I was at AWS. Everyone was talking around agentic AI and building the tools or providing businesses with the tools and the partners to create these agents that will do things on everybody's behalf. And you describe a new playbook for agentic marketing, which is why I was so excited to get you on after going to that conference, especially where trust and quality matter more than volume.

[00:10:01] So what does that look like in practice and how it changed the day-to-day work of modern marketing team? Because we hear all these stories coming out of a conference and many people are sat on that plane ride home thinking, well, what does it mean to me? So what does it mean to a modern marketing team? Yeah. How do I take all this buzz and turn it into a practical playbook? We think a lot about that.

[00:10:22] And, you know, I'm happy to say my team, you know, even to work with my team to get us agentified or having an agentic playbook because I have amazingly tenured people who know what they're doing. They've been doing this for years. And that overcoming that inertia is definitely a bit of work. But we put a playbook together that I think helps us understand when and where and how to use agents effectively.

[00:10:49] So there's, I think, five key pillars to it. But the overarching theme is that what you want to do is you want to take AI and point it at the things that AI can do just as good or maybe even better than humans.

[00:11:11] It means that humans don't have a domain advantage on or drive a differentiation for your company in. So what I mean by that is AI can help you be faster, right? You can take a single input like a research report and turn it into dozens of derivative assets at once. You know, it could create social posts. It could create sales deck updates. It can create email sequences.

[00:11:41] The speed at which you can do that is that AI can help your team go faster with the grunt work is amazing. The scale that AI can help you with is also another key motion here. So you want to use AI for adopting to more personas, new regions. Take a playbook and move it across more markets, more products, more audiences.

[00:12:06] We have a large Fortune 500 CPG customer that when they launch a product, they take the core product briefing and use Rider to create over 500 individual product detail pages that they then post to all of the different vendors that they're using across the world. And that just gives them this bigger scale than they could get to before.

[00:12:33] You know, you can't, it was hard to launch to so many markets at one time. And AI can help you do that because it's great at just taking stuff and turning it into more of that stuff with a different flavor. But you want to take the speed and scale and you want to drive the humanity. You want to use that to embed and imbue more humanity into the work that your people are doing.

[00:12:58] So let AI take the grunt work and then the savings that you have from the productivity savings that you have from that advantage, use it to give your team more time to do creative work, more creative thinking, more brainstorming.

[00:13:17] And for, depending on your business, how this gets executed, but you want to use it to invest more in customer relationships and high touch customer engagements. So I'll give you an example. For my team, we, we spend, we're really great digitally. The team covering all bases, our metrics are awesome. We deliver all the pipeline and everything that we are supposed to be doing digitally.

[00:13:45] And we have a great presence digitally, but we're very productive in terms of how we get there. Our cost to produce is much less than my peers. And so I'm able to invest in digital advertising with less production costs than the typical B2B software company. I take those savings and I put that, I don't bank it. I don't, I talked to my CFO and, you know, we talk about how to, you know, what does our model, what does our economic model look like?

[00:14:13] And I say to him, let's, I can do this cheaper. And what we're going to do is we're going to take those savings and we're going to move that to more live in-person events because that's what moves the needle for writer. Like we have, we've deconstructed our funnel. We've deconstructed how we acquire customers. We see what works for us and it's dinners with customers. We have an AI leaders forum that we run every, every quarter or so where we bring in AI leaders for intimate chats and talks and networking events.

[00:14:43] And we do more, we have a higher percentage spend on field marketing than the typical B2B organization. But that's because we figured out how to do the digital side of the equation much more effectively. So what you want to do is take, take AI, drive speed and scale. You want to use those savings. You want to make humans do the creative work. So that asset that I talked about earlier on a research report that you can turn into dozens of completed derivative assets.

[00:15:11] Well, that is originated by a human and that's where the human ingenuity comes from. And that's where your brand will have a differentiation. So you reuse the investments to give people more time to do the creative work and then supplement that with something that drives deeper customer relationships. In our case, it's more field marketing events, but it could be other types of engagements for different types of business.

[00:15:36] In a former life, I used to work in IT and over the years, I've seen many companies rush to deploy the latest shiny technology, but without adjusting how their leaders operate at the top. And I don't think AI is any different. So can you tell me a little bit more about why you believe C-level executives need to evolve first if they truly want their organization to succeed with AI too? Yeah, AI is like no other. And like I said, I've been through a lot of waves.

[00:16:05] The whole analytics wave in the 2000s, the automation wave in the 2010s. Those were incremental improvements on the way we did things before. They're great. They captured a lot of value in better operational acuity. But AI is completely different. It is a first principles ground up. It will deliver the possibility of first principles ground up transformation of workflows.

[00:16:35] And if you don't get hands on and understand how it works and how to actually get it to do great stuff as a leader, you will fall behind. And your team will fall behind because it's so easy to just not really drive a radical transformation with it. But the leaders that I'm seeing that are having the most success are the ones that are rolling their sleeves up.

[00:17:05] They're working with it every day. And they're really driving. You know, they're treating it as a revolution, not an IT project. It is something that they're rethinking the core workflows of how their department runs. And for that, the CMO really has to think of like, okay, how am I going to, how's my organization going to function from here? Like, do I need more relationship managers and less content creators? Right?

[00:17:33] How does the structure of my org change? How does a workflow actually get done? If it used to be, we make stuff, then we send it to another group of people who make derivative stuff from it. Well, if we're going to make stuff and then we're going to send it to AI to do the derivative stuff, like that's a different workflow. So if you don't understand how that work really works, what the roles are that need to be reassigned, how your teams need to be upskilled, you're not going to make it in the next wave.

[00:18:02] Because the teams that are doing that will. And you have to, you know, you have to show your team and model AI adoption yourself. Because like I said earlier, it's, especially in large enterprises, and that's where Ryder lives. We, Fortune 500, Global 2000 is really our sweet spot. And because the people there tend to be tenured and experienced, they're pretty comfortable with the way they're doing things.

[00:18:29] And if they don't see their leaders taking risk and being hands-on, they're just not going to do it. And then the last thing is you have to just change how you measure success. You know, traditional KPIs, they don't measure, they don't capture the value of AI. You have to actually measure the impact of the AI as well, separately, so that you can understand is adoption happening or not happening. Because it is a leading indicator to future KPI success.

[00:18:59] So you have to be tracking that separately. And when you look at the reality inside of enterprises, I'm curious, what are some of the most common mistakes that you will see in teams making when adopting AI? And what are some of the simple steps that just help them get past those early friction points? Yeah, a couple things. First thing is deploying AI without a clear use case or a success metric.

[00:19:24] The big challenge I see right now is that a lot of teams are deploying the, you know, co-pilots or ChatGPT and handing that to the quote-unquote line workers and checking a box that they've deployed AI inside the department.

[00:19:48] And the reality is that when you just deploy a general productivity tool, what you get is capped by the imagination and the local workflow of the person. And that's not, that's actually been a lot of friction. You know, you read the, you know, everyone saw the report of MIT, 95% are not getting value.

[00:20:16] That's because they're not really driving a clear use case, a clear success metric, finding a specific problem and a specific workflow to transform and apply AI to that and then measure it all the way through. That's the fix. That's the way, that's the way to get, that's the first mistake. The second is really ignoring the change management aspect of this and ignoring AI literacy for the organization.

[00:20:45] You know, a lot of the companies focus all their energy on the technology and forget that, as we've been talking about in this conversation, the human factor is so important. And unless they're spending time upskilling their teams, investing in AI literacy, finding the evangelists, celebrating the ones, the people who are leveraging it and using it well, and giving people, you know, the room to experiment safely.

[00:21:14] It's, it's, it's, the human side of the equation will limit the technology side from being robustly successful. And so that, those are the, I think those are the big mistakes, not having the, like, not having a specific use case in mind, just giving productivity tools and really ignoring change management and not doing enough to get the people up and running. You got to give people time to work on this. You got to give them room to fail. You have to show them how to do it, and you have to make it important for them to do it.

[00:21:42] And I also wanted to highlight that at writer.com, you work with brands like American Eagle and Qualcomm, so some massive names here. So what stands out from some of these collaborations about how teams can use agents to empower people rather than push them aside? Because this is a side of the narrative that we don't hear enough, I think. Yeah, I like American Eagle. Obviously, they've had a hot year.

[00:22:07] They've had a big year, and their CMO, Craig Roberts, is fantastic, and he's so AI-forward. So you see the results in their creative. Regardless of where you stand on it, I think they've done an amazing job. They got a lot of side noise, which is interesting, but that's a different story. But they're creatively excellent, right? They're great storytellers. They have fun, interesting, creative.

[00:22:33] And Craig came to writer, too. He's not eliminating copywriters. He's not eliminating people doing creative. They're using AI to handle repetitive time-consuming content creation, generating product descriptions, personalizing email, adapting messaging for different channels. So it goes all the way back to write what we said earlier about using AI in the right way,

[00:22:59] using it for the things that it's really good at, and then freeing the people up to do more creative. Another good example of this is New American Funding. So I just did a webinar with them. You can, not trying to be promotional, but you can find it at writer.com. And Andrew Stuckman is their CMO. He's so thoughtful and so forward-thinking. New American Funding is a, they do mortgage loans for people. They're a mortgage loan company.

[00:23:28] But they focus on getting people, like their mission is to, everyone should be a homeowner, right? And so they use writer to handle all of the really complex compliance checks that they need to do with their marketing content. Because they're in a regulated industry, they're a financial services company. So, and he talks about this in the webinar.

[00:23:53] So much of the work involved is not marketing work at all. It's compliance checks, regulatory checks, you know, making sure that it passes all the bars that it needs to pass in order to actually go to market. And so writer is helping them do that. They built a compliance agent that looks at everything that they're going to put out and checks it against all of their compliance regulations.

[00:24:20] And what used to take weeks now takes a day for them to get this out the door. And he talks about how that gives the team much more time and bandwidth to focus on the creative. And I love his campaign that he's running right now. And they won an award for it. Hell yeah, you're buying a home. Capture that moment of like first-time homeowners. Because that's who their market is, like young people and first-time homeowners. And that moment of like, yeah, we're going to buy a home.

[00:24:47] I remember when I bought my first home, like that feeling. And he captured that and he credits a lot of that to, hey, we just have a lot more creative bandwidth to do interesting things. And writer was helping us do the, you know, the boring stuff. I talked about the CPG company. They actually, they estimated they're saving 5,500 human hours a year in product descriptions and product detail content using writer. A lot of B2B software companies are using writer in their sales enablement process.

[00:25:17] We work with a leading cybersecurity platform and they transform their whole RFP process. So when, you know, a request proposal comes in from a prospect, writer agents pull all the data from Salesforce, from Microsoft, Teams, Channels, creates the responses and then gives it to the account teams for review. So much time saved from, for the sales team.

[00:25:39] And, and another fun example that a lot of our B2B customers are using originated with, with my team as the actual first for people to create this agent. And then we, we productized it and a lot of our customers are using it. My head of demand gen found that we had a bottleneck in our outbound motion where we, you know, we reach out and position the stuff that we're doing. Like, Hey, Diego is going to be on this webinar.

[00:26:09] We'd love to have you join. Please join us. Or, Hey, we just wrote this white paper. Would love to, you know, walk you through it. Right. Traditional sort of B2B tech outreach. And Andrew, who's my head of demand gen. He saw that we created this amazing stuff and then sales wasn't picking it up and using it. And so he created his own pipeline.

[00:26:28] He calls it the PG kit agent, pipeline generation agent, which every time we create an asset, a new asset, it automatically creates all the outbound materials for our sellers to go and then do the outreach. So emails, call scripts, LinkedIn posts automatically puts it in our notion and you have to do a thing that agent just handles all and then informs them that this is available.

[00:26:55] So that those are some examples of how some of our customers are using it. And even my own team is using it to be more productive. So incredibly cool. And before you join me on the podcast, I was doing a little research on you. One of the things that stood out to me was how you often talk about freeing marketers from some of that repetitive work so they can focus on some of the ideas that require more human judgment. And again, it's something we don't hear enough about.

[00:27:20] So what type of tasks are the best candidates for automation and where should teams keep a firm human hand in place? Again, quite a tricky balance, but I'd love to hear what you're saying here. Yeah, I think it's a lot of the tasks I was sharing. Automate the repeatable. Like if you need a general framework, it's automate the repeatable. Content optimization and formatting. Data analysis and reporting. Personalization at scale, right? Taking something and creating multiple segments for it.

[00:27:49] Routine customer communications, right? FAQ responses, standard onboarding emails, transactional messages. Research and summarization, right? What are the top trends in our industry this quarter? Where can AI, you know, AI can aggregate into those eyes and summarize that faster than any human. In fact, I was just at with a customer, a large hedge fund, and we were showing them the new writer agent, which is our newest release or our core agent interface.

[00:28:17] And they asked us right on the spot. Can you take our research report or research and write a report, but do it in the voice of our lead analyst? Who has a lot of self-deprecating humor and references his Australian background.

[00:28:41] And so what we did was we took and they said, and we'll show you what a good report looks like. So we pointed them at all the research. We pointed them at here's what a good report looks like. And then we said, here's the person. Please look up how he talks, what he talks about, and how he references his Australian heritage. And it created an amazing first draft for them to work off of, right?

[00:29:07] And so that's an example for research, you know, creating those initial draft reports. And then templated content, right? Product descriptions, job postings, just standard documentation, things that, you know, AI can create the first draft. So anything that's sort of repeatable or comes from a source doc that needs to be summarized, just streamlined. And then keep humans in charge of brand strategy and positioning. Once again, you know, the idea here is let AI do the grunt work.

[00:29:37] When your brand, your brand needs to derive its differentiation from the people in charge. Because otherwise, if you don't do that and you hand off the core narrative to AI, that's where you're going to sound and people are going to call you AI slump. That's where the real opportunity is.

[00:30:04] Because so many people have all of these tools that the medium level is really easy to get to. And it's all going to sound the same. So you have to inject strong narrative and positioning. And that's what you got to keep humans in charge of. Keep them in charge of creative direction and innovation. Humans keep them in charge of relationship building, strategic decision making, nuanced communication, things that are hard to communicate.

[00:30:32] Things that are not, are different than, you know, what everyone else in your market is doing. If it's a differentiator, keep humans in charge of that communication and quality control and brand governance. Keep making sure there's a human that checks things before they go. So that's how we split it out. You know, it's really like what's repeatable, what's automatable. I think the ship has sailed. You've got, if you don't, if you don't figure out how to hand that stuff over to AI, you're just not going to be able to compete with those who are. Right. Right.

[00:31:01] And so then you want, you're not going to be able to compete like the middle tier. Yeah. Here's, here's how I think about it. The middle tier is going to be those who figure out automation with AI really well and just kind of like trudge along. The top tier are going to be the people who figure out how to automate with AI and differentiate with humans. The bottom tier are going to be the people who don't even, who don't even figure out how to use AI to automate because that's just going to be table stakes. So you got to figure that out first just to get to the middle tier.

[00:31:30] But then the top tier of performance in marketing is going to come from people who figure out how to keep humans as the differentiation. So many great points there. And I love how you, what you've built and the reasons that you built it and how people are using it. But I'd love to take a sneak peek behind the curtain, so to speak. And how's it used inside your own organization? How are your own marketing using writer's agents day to day? And is there anything that surprised you about the impact that the tools had when fully embedded?

[00:31:59] Yeah, we call it a writer on writer. So the wow program marketing, right? We got to make it fun for everyone. As I said earlier, even inside writer, and this is not a knock on anyone at writer, even inside writer, we had some initial inertia of really being AI. Like in my team, I'm just going to speak for my team. I hired these people who, we're a fast growing company.

[00:32:26] We don't have, you know, we're not, we're not, we're not full of a bunch of junior people just coming out of school. You know, we don't have like, you know, we're, we're a VC backed high growth company. And I've hired really smart, experienced people that know how to do their jobs. Like plug them in. I orchestrate. We have a real machine here.

[00:32:50] For even for those people, they're actually the ones that have the initial biggest challenge of using new AI tools because they're so good at what they do every day. They're so good. They know how to do it that we're asking them to change their, their approach, make career, right? So we had to put a lot of energy around the change management and a lot of energy around showing what we wanted. What does good look like?

[00:33:17] Who are the people that are really embracing it and are just the, the vanguards of an AI first motion. And so we found those champions. We celebrated them. We enabled them. We gave them the sort of, we gave them, let them drive writer on writer. And so they became the forward thinkers. That was sort of how we positioned the energy around it. But what we did was we went team by team.

[00:33:46] And we looked at it by different departments. And then we looked at it by the different stages of the funnel. And that was really illuminating for the team. Because what we were able to say was like, because when you go to someone and say, what are you going to make AI in your, in your workflow? And it's just like, well, I don't know. What do you mean? Like, you know, like it's a hard, hard question. Right. But instead, what the way our approach was, hey, let's break down what a process looks like across the org. Right.

[00:34:13] So we went top of the funnel, middle of the funnel, bottom of the funnel. Then we went product marketing, demand gen, comms, brand operations. And then we mapped out all of the different workflows that the teams have at each one of those stages. And then we prioritized based on how much value does that workflow have for us? Like, is that a mission critical workflow? You know, from zero to five, right?

[00:34:41] Mission critical workflow or is it a one is a mission critical workflow. Five is like, yeah, it's just like something we do once in a while. How much value does that bring to the organization? Like, is there, does ROI, is ROI driven? Like, does revenue and pipeline come from that, that, that operation? How hard is it to do, right? Is this something easy for humans? How repeatable is it? So we created this whole like rubric of each of the workflows that we identified. And we gave them a score on AI identifying potential.

[00:35:09] And then we basically took the ones that had the highest scores. And we just started going workflow by workflow. And then figuring out where does the agent, how can we apply an agent to that workflow? And one of those examples was my head of demand gen, you know, identified that pipeline, outbound pipeline kit agent as one example. But we do other things like we've turned our, you know, long repeatable, all our repeatable workflows, we turn into playbooks.

[00:35:37] A long form blog post automatically gets adopted for LinkedIn posts. It's now like it just, as soon as we, we finish a post, we put it in the agent and the agent turns all the LinkedIn posts, Twitter threads, email snippets. We have automated routines that run automatically, weekly competitive intelligence reports, daily social media reports, monthly performance summaries. They're all just running on autopilot.

[00:36:01] I had to mention the sales enablement, not just, not just the, the, the pipeline kit that I talked about, but we also generate customer and prospect synopsis for our sellers. So we go through all of our systems from Salesforce to our gong recordings. And whenever we're a sales, a salesperson is going to meet with a customer or prospect, we give them a report that, that helps them do that.

[00:36:28] It helps them understand where we are with the customer and what they care about. And so those are some examples. Love it. And of course, 2025 was all about exploring the art of the possible with agentic AI. And for many businesses, it will be 2026. It's all about action going into production.

[00:36:46] And how do you see AI driven workflows reshaping that relationship between marketing sales and product teams as enterprises further adopt AI enabled operations? Because things are getting pretty real now, aren't they? Yeah. I think what we're going to see in 2026 is much more cross departmental workflows and much more fluid collaboration than we've had before.

[00:37:14] As I mentioned earlier, I think we've had a lot of personal productivity. And so individual contributor work has been transformed over the last two years, three years. I think next, I don't think we're going to get super cross. I think the next frontier is interdepartmental work from inside the marketing org.

[00:37:42] So from product marketing, generating persona and messaging docs that automatically create initial posts and content for the content team that automatically create campaign briefs for the campaign team. I think this year is going to be a lot.

[00:38:08] 2026 is going to be a lot around going from I'm sitting at my desk and I am going to create, use AI to do, to create a blog post to AI is going to help my marketing department function much more fluidly across the different teams in an orchestrated manner.

[00:38:26] I think the frontier beyond that will be more of a 2027 and beyond where then the departments within the organization are operating more fluidly across each other. Marketing, marketing, marketing, marketing, marketing, using AI to uncover moments of truth in the customer journey that then move on to the product team. I think we still have to get through departmental fluidity.

[00:38:54] Then we go into interdepartmental fluidity and that's the next frontier. But I think this year will be all about orchestration across the entire team, whether that's a marketing team or a internal team, whatever team that may be that you're using AI for. So exciting times ahead. Indeed, I'd love to get you back on later in the year, see how things are continuously evolving.

[00:39:17] But for anyone listening wants to continue that conversation or just find out more information about anything we talked about today, I'll include a link to the webinar that you mentioned. But anywhere else you'd like to point everyone listening? Yeah, mostly LinkedIn. I'm on LinkedIn. I post a lot. I'm active there, sharing thoughts on AI, marketing, leadership, industry trends. So just search for Diego Lomanto. Diego like San Diego.

[00:39:43] And no one ever gets my last name right, so I'll spell it L-O-M-A-N-T-O. So that's the best place. I also write regularly at our blog, writer.com slash blog. And you can always also come to writer.com and check us out. You should check out our podcast, Humans of AI. We host our own podcast. We find people who are making a difference, build their careers around AI or driving the humanity of AI. And a lot of great guests there.

[00:40:11] And I think that's probably the best places. Awesome. Well, I'll include links to everything, the webinar, the podcast, your LinkedIn website. So I want to encourage people to click on the show notes and check you guys out. So much we covered in a short amount of time there. I'd love for people listening to reach out and let us know what you thought. But more than anything, just thank you for sitting down with me today. As I said, we'll get you back on later in the year, see how things are progressing. Thanks for joining me today. Thank you, Neil. A pleasure. Thanks for having me.

[00:40:40] I always enjoy conversations where the guest brings clarity to a topic that often feels overwhelming for many people. And Diego did that today with practical honesty and a real appreciation for the people behind the work. And I genuinely hope that it left you thinking about where AI should take that heavy load, where humans should own the story and what it means for leadership in the coming year.

[00:41:08] And if anything stood out or sparked a question from you, I'd love to hear from you. Please tell me how AI is changing your own workflow, where you are still experimenting. And if you enjoyed today's guest, please go and say hello to Diego on LinkedIn or check out the blog and podcast and webinar. I'll leave links to everything. But that is it for today. So thank you for joining me here at AI at Work.

[00:41:32] Remember, at Tech Talks Network, you will find nine tech podcasts and three and a half thousand interviews. That should be enough to get you through the holidays. Thank you for listening as always. And I'll speak with you all again very soon. Bye for now.