Why Mastering AI Tools Matters with Zapier’s Emily Mabie

Hey everyone. Welcome back here to Techstrong tv. I want to introduce you all to Emily May be, no, not Emily, may be Emily May.

Um, that's definitely her name, not maybe, um, Emily, welcome to Tech Trunk tv. It's great to have you here. Thank you, Alan.

I'm so excited to be here with you today. Thank you. So Emily, you have what for today's Times may be a dream job and dream title.

You are an AI automation engineer over at Zapier. Yeah. Congratulations on that.

How, how does one become an ai? I'm sure there are people out here who are gonna ask this. How do they become an AI automation engineer?

I think that I get asked this question more than almost any other, uh, and I can answer it for you with a little story about me. So, uh, my background is not in engineering. It's not in building computers or coding or anything that might sound like it's really strongly aligned.

My background is actually, uh, teaching kindergarten. I taught really, uh, I taught kindergarten and public school and special education for 10 years. And, um, when I made the leap into the world of tech, it was actually to do learning design for adults.

And that was sort of the niche I first found myself in. Um, and after about five years of designing, learning for adults in the tech space, designing trainings and workshops, I just so happened to be at an offsite with our chief people officer at Zapier. His name is Brandon, and he was eating breakfast.

Brandon was watching a video of a brand new piece of technology that Zapier, where I work, had just premiered. And it was AI agents. It was the day it premiered, and if you're watching, it was 18 months ago, I really was walking by him at breakfast and he ushered me over and said, I want you to see this.

And I'm, I'm not exaggerating when I say I watched this four minute video with him, grabbed my cell phone. I said, I can't eat breakfast right now. I have to go.

I ran up to my hotel room, called my partner and said, I just saw the future of tech, and when I get home, I'm going to push everything I can to the side of my desk for two weeks and learn how to use it. And I had the benefit of working at a company that prioritized innovation and technology, automation, ai, but I was able to fully invest in learning AI agents for my job. So for learning design, for HR use, right?

I was designing checklists, I was designing, you know, uh, sorts of AI automations that kind of helped me run the tedium of my day to day. But through learning that one tool, just AI agents learning it deeply, I ended up having to learn all sorts of other things, prompting, setting up databases, just within the pain points that I experienced every day on the job. And 18 months later, I am so trusted at work with our AI tools that I was offered a new job, which is AI automation engineer for hr.

Uh, so the, the really like, fine point on it is how do you get that job? You learn the pain points of your own role, whatever it is at work, if you're a nurse, if you are, uh, an IT practitioner and then you start automating it, you learn a tool for that job, and then you can become the trusted resource for AI automation in that role. I love it.

I like, I hope everyone out here paid attention to this, Emily. 'cause what a great story. Thank you.

What a great, great, great, great, great story. And I do agree with you. I, I, you know, I had a similar thing about 28 years ago, almost 30 years ago when I first saw it, like Netscape browser on the internet mm-hmm.

And realized what the web was going to do. Yes, Yes, yes. And, uh, I, I went to law school, I was practicing law, and, but I was, you know, computers were my passion, and I saw that, and I did a similar thing.

I, I, I wasn't as I think as, I wasn't as forward as you, I wasn't as focused as you. It took me a little time to really bring it together. Sure.

But it, it, it's an amazing thing, you know, and as we sit here today, I wonder if in five to 10 years, a person down, a guy sitting out here Yeah. Is still gonna be able to just say, Hey, I'm just gonna clear off my desk and take a few weeks and become an expert here. Yeah.

Or is it going to advance where, you know, it's gonna take years for someone to really master everything it becomes, or perhaps even worse, don't bother, it'll take care of itself. Right. And, and, um, you know, that, that's certainly a possibility we have to think of too.

But kudos to you for, for making that connection, right. And seeing the future, the future of rock and roll, as they said about Bruce Springsteen one time. And, um, you know, and, and here you are.

You mentioned a little bit about Zapier, as I mentioned to you off, off camera, full disclosure. Look, we're a big Zapier customer here at Textron. Yeah.

A lot of our automations and integrations are zaps, as we call them. And, uh, it, it's a great product and great tool. But Emily, for those people who maybe aren't familiar with Zapier, how would you describe it to 'em?

Oh, wow. I've only been with Zapier for a little over three years, and so my experience with Zapier and yours, Alan, is probably a little different, right? Zapier, as you mentioned with your use case, helps companies of all different sizes automate workflows and connect their tools.

That looks like a library of more than 8,000 apps that we can connect so that they can talk to each other. Everything from Salesforce to Slack, to open ai. And for enterprises, those big, big companies.

We also currently help orchestrate AI across systems so that leaders can unify their data and automate outcomes without needing to write code. But in its infancy, when it was first born, 13 some years ago, Zapier's only product was the workflow, connecting apps to talk to each other. Now, Zapier has not only this AI orchestration layer layer, but we do that through all these individual tools that we've created.

Zapier tables, which are, uh, tables, databases that have AI baked right in chatbots, AI agents, like I mentioned before, interfaces, which let you build forms or websites in like 30 seconds. Um, canvas, we've got all of these products now and, and AI co-pilot that, uh, threads across all of them to help you build very quickly and build these connected systems. Um, but in, in like the shortest answer, Zapier is a tool that helps you automate and often AI automate across your tech stack.

So everything talks to each other. Love it. That's a great description, by the way, Emily.

Thanks. Good for you. I appreciate that.

Yeah. So let us turn to this recent survey that Zapier did. It was the, uh, enterprise AI benefits survey.

Yeah. And it had some interesting findings, some surprising ones. Yeah.

Emily, why don't you let, let's kick it off with this. What do you think are the key findings that people need to take out of this? Hmm.

Okay. Okay. Key findings.

I would say one of the big, uh, takeaways is the way that AI is influencing day-to-day workflows and the individual functions in a company that are seeing the biggest gains. So we are actually seeing the biggest gains, according to the survey in marketing and sales, followed closely by operations. And those teams are using AI to accelerate everything from content creation to lead routing, to customer engagement.

And what I found really exciting, uh, about the survey data was the impact is expanding. So what we're seeing is as more teams experiment, uh, HR teams that I represent, finance it, they're discovering totally new ways to remove manual steps and reclaim time for the strategic work. And we're seeing that when AI and automation are working together, we're not seeing a result where just one workflow is working faster.

They're making entire systems smarter, which is where we see the real productivity unlock. But the flip side, the other big takeaway was the barriers, right? The, the survey was all about highlighting these barriers that are preventing enterprises from expanding their AI use.

And the number one barrier was measurement itself. Now, if anybody listening is a learning designer, like I have my background, uh, this will not surprise you because we've got that old adage of we value what we, me, we measure what we value, but mm-hmm. Many organizations don't have formal systems in place to track the return on investment for ai.

So they might be doing ai, but they can't prove that AI out. And another big challenge, another big barrier that popped up in the survey is this concept of AI sprawl companies have so many tools, so many disconnected tools, different models, different teams using them, and there is not enough orchestration between them Without that connective layer, it is so hard to scale the benefits of ai. And so to sort of wrap that up in a bow, that's where automation platforms like Zapier come in because they can help connect those AI tools to the rest of the tech stack, so that data flows automatically and benefits become enterprise wide.

But right now we're seeing that as a huge barrier. What, what, was there anything that really leapt out at you as a surprise? Kind of like, wow, I didn't see that coming.

Yeah, I, I have to say the headline itself really did surprise me how stark the gap was. For me, the most surprising insight was that huge space between adoption and actual impact. So for anyone who hasn't excitedly torn open the survey yet, nearly every enterprise we surveyed, it was like 97%, uh, said that they had begun adopting ai, but only half said that those benefits were felt organization wide, which tells us that AI has crossed something very important, the experimentation phase, but all of these companies are still struggling to operationalize it in a consistent and scalable way, which for us, we call the AI orchestration gap.

And that surprised me. Um, you know, it's not that enterprises don't have the tools. They do have the tools, they've got so many tools, it's how siloed the benefits of each of those tools remain.

One, one department has a great faster workflow. Another one is saving costs, but they don't have a unified strategy. So, couple of thoughts on that.

It's not just the tools that are siloed, it's the departments themselves that are siloed. Yeah. And so the benefits accruing to one department, perhaps for using ai, well, doesn't necessarily bleed over to the next department because of those silos.

But secondly, look, the, you know, we all look at this. There's a study out of MIT you probably saw 95% of organizations using AI are saying that it's not Yes. Hasn't had a big effect on the bottom line.

Yeah. I, I, you know, but then there is a, a competing, not a competing, but another survey that comes outta the Wharton School Yeah. That, that says, look, 40 to 60% of the ones who are using are saying it has absolutely a positive effect.

Yes. I, I think, you know, I think they're both right and both wrong in a quantum sort of way. Right.

Um, but it, it depends, I think what your expectations of success are, what, how much you're really putting into it, and what you're, you know, what you want to get out of it. I, I do think we're all in the experimental phase. I'm not sure we've passed through that.

Yeah. And I, I, you know, I don't think we're going to get through that. I think we, you can't look at AI as a monolith.

Right, right. I think we had a, the last three years or so with generative ai mm-hmm. And we've learned about chatbots and generative AI and all the great things it could do.

I think we're just embarking on this agentic ai. Yes, Yes. Which is a different animal, I think, than generative.

Yes. And so it's gonna have its own use cases, its own, you know, machinations that it goes through. Yes.

So I think it's gonna take us a year or two to really see that, how that plays out. Yes. I mean, you know, we recorded this before Thanksgiving, so people will Paul watch it after Thanksgiving, but I was doing the Textron gang for our Thanksgiving show.

And look, it's a great time to be alive. It's a great time to be involved in tech during this period where there's so much promise and so much, you know, there's so much possibilities out there. There's so many, so many things are possible.

Yes. How many of them will come to fruition? How many of them are going to be truly doable, is really gonna be the measure of us as a species, as humans.

Yes. Right. Because as much as we think AI's gonna replace us or do things, no, it's still the, it could be one of the greatest tools, the greatest tool we ever have, but it's up to us to make it beneficial.

It's up to us to make it profitable. It's up to us to operationalize it. Yes.

We can't sit back and say, oh, we're all using it and it doesn't do anything. Well, good look in the mirror. Anyway, Emily, I'll get off my soapbox now.

Go ahead. I Wanna, I wanna connect with what you said though, because you brought up, you brought up sort of this, um, trajectory. We went from generative AI really taking off in the last few years, and now we're seeing agentic AI really taking off.

And, um, I, I think it relates to the data that we were talking about, because for me, generative ai, uh, it helps me with efficiency gains, but it doesn't necessarily save me a ton of time or cost. But when you look at things like agentic ai, where AI is taking on tasks with tools at its disposal, and I'm just a human in the loop helping my, my robot coworker, that's where we see things like time savings coming through as the loudest and clearest top measurable benefit. In the survey where I think it was 30% of respondents said AI has reclaimed them time, or, uh, the other two big wins were efficiency gains and cost savings.

Um, and something I think is really important, what you said at the end there about like, we have this tool, but humans are going to determine the impact that it has. The survey found that companies that had formal return on investment or metrics tracking were six times more likely to see a measurable benefit from ai. And for me, again, I know I just said it, but like that's the takeaway.

What gets measured gets valued and multiplied. If we want to, uh, value what we measure, we have to measure what we value and that helps us direct AI in the right direction. Absolutely.

Emily, for people who want to maybe take a deeper dive into the survey results and report, where can they go? Oh, I love this question. Zapier's got a blog.

com/blog and then if you slash again enterprise dash ai dash benefits, I'll give you a deep dive. But I'm gonna hold them hostage, Alan, because I wanna tell them some key takeaways. Is that okay?

Sure. Okay. Alright.

We've been hearing a lot of questions from people about what enterprise leaders should focus on next year. And when you dive into that survey on Zapier's blog, you will see five practical recommendations. But I wanna walk you through 'em real quick.

Let's knock 'em down. Okay. The first one, connect your ecosystem.

So we want you as enterprise leaders to ensure that AI tools integrate seamlessly across your teams. That's number one. Number two, measure what matters.

You heard me say it now for the third time, sorry, everybody establish a formal return on investment metrics tracking process. Track that it correlates with stronger outcomes. Number three, empower all the employees.

I told that story at the beginning, Alan, 'cause you asked me about how does someone even become an AI automation engineer? And the answer is, democratize your tools. Let your employees use no code and low code tools like Zapier so that business users are safely building AI workflows.

That's number three. Number four, standardized AI use enterprise wide. You've gotta move from these isolated projects to fully orchestrated automation.

And the last one, reinvest your time savings. So you're gonna notice that all of a sudden you're saving time and your process put that reclaimed time towards innovation. Alan, you asked at the beginning like, are we moving to a place where people can't push stuff to the side of the desk for two weeks?

Well, when you get those two weeks back, push stuff to the side and innovate. Maybe use that reclaimed time to improve your customer's experiences. But in general, the headline is, enterprises don't need more ai, they need smarter AI that's connected through automation.

Alright, there's spiel. All righty, Emily, thank you so much. Congratulations on your role.

Keep us posted. And best of luck. Did you go check out the survey on Zapier at the Zapier blog as Emily told you, we're gonna take a break here on Text Trunk tv.

We'll be back in just a bit.