Creator management platform GRIN has introduced Gia, an AI assistant designed to transform how brands run influencer marketing campaigns by automating the most labor-intensive aspects of creator partnerships. This new technology aims to solve the key challenge that has prevented influencer marketing from becoming a true performance channel: operational complexity.

Ryan Debenham, CEO of GRIN, believes Gia represents a pivotal shift in creator marketing.

“We’re in a new era where we can unlock the true potential of influencer marketing at a much greater scale,” Ryan explains. “We have the data to show that influencer marketing can have a higher return on investment than other paid channels. However, we have yet to see it become as significant as paid channels for a brand, due to the effort and complexity involved in actually attributing the return on investment. And I believe all of that can be fixed through AI.”

Why GRIN Created Gia

GRIN’s development of Gia was driven by clear observations from their clients’ experiences. Despite growing interest from brands worldwide in influencer marketing, many struggle with its implementation. “You’ve got pretty much every brand or business in the world at this point asking, ‘What’s our strategy? How do we do this?'” Ryan notes.

The core issue, according to Ryan, lies not with the brands but with the industry itself: “I view it as our fault in terms of it’s too complex and we’ve not done a sufficient job in simplifying it for people.” The typical workflow involves countless hours searching for creators, vetting them, managing outreach, and monitoring content, often handled by understaffed teams.

“Even our customers that are often not small businesses—they’re upper SMB or mid-market brands—oftentimes it’s a team of one that’s running influencer marketing,” Ryan observes. “It is one person wearing many different hats, trying to manage many different influencers and campaigns, and it’s just a tremendous amount of work.”

GRIN initially attempted to tackle these challenges by expanding beyond technology to offer educational resources and community support. “We started bringing a lot of educational material, webinars, and masterclasses. We expanded our service and support offering,” Ryan says. But this approach still didn’t solve the main problem: “We are offering more support, but we have not reduced the amount of work.”

This realization led directly to the development of Gia as a solution that could actually reduce workload, not just provide guidance on how to handle it. “A tool by itself leads a lot of customers to an unsatisfying outcome,” Ryan concludes.

What Gia Is

Gia stands apart from typical “AI-powered” marketing tools that Ryan characterizes as mostly “hype.” Drawing on his 15 years of experience as a software engineer, including stints leading Data Analytics and AI at Qualtrics and serving as CTO at Route, Ryan approached AI integration with caution.

“Most of it lacks substance,” Ryan says of standard AI implementations. “Maybe it demos well, but does it really create value for the customer in terms of a better outcome or reduced time? In most cases, it falls really flat. I refused to build an AI feature that was purely for the purpose of creating hype.”

Instead of adding AI capabilities to their existing platform, GRIN created Gia as a completely new system. “We are not layering this on top of GRIN. We are building this as a brand new, from-the-ground-up capability,” Ryan emphasizes. “We started over, we have built Gia from the ground up as a purely agentic-powered operating system for influencer marketing.”

Gia’s purpose is to handle the operational aspects of influencer marketing with minimal human intervention. “She will be the operator that partners with brands to accomplish their goals and only expects the brand to do the work that is really necessary. She will do everything else on behalf of them,” Ryan explains.

How Gia Works

Gia’s creation has progressed through several stages, each representing an important step forward in capability. 

The first iteration focused on simplifying influencer discovery, a process that traditionally required substantial human effort. “Our own metrics on that—our team spends about 30 minutes per vetted influencer,” Ryan explains. “If you think about producing a list of 100 influencers, that’s 50 hours. That is a tremendous investment.”

Initially, Gia could translate natural language requests into database searches; however, the results weren’t always accurate. The breakthrough came when Gia was designed to mimic the human vetting process—examining creator profiles and analyzing content in depth.

“Once Gia has run the initial search to create a pool of candidates, she’ll open up the profile and look at the content,” Ryan explains. “She’ll look at every image, every video, and decide, ‘Is this about beauty?’ She’ll look at their bio, ‘Do they say that they’re in LA?’ She’ll look at their audience and then make a determination.”

To test Gia’s capabilities, the team created increasingly specific queries. “We’re looking for creators in L.A. that have gray curly hair,” Ryan recalls. “The only way you would know if they have gray curly hair is if the AI is really looking at the content. And what was amazing is we came back and there was a whole pile of creators with gray curly hair.”

Gia’s capabilities then expanded to manage the communication process. “You need to email them all, wait for their response, follow up, and determine if they’ve accepted your proposal or go through a negotiation process,” Ryan explains of the typical workflow that Gia now handles. Early customers report notable time savings, with feedback that validates GRIN’s approach: “She is saving us so much time. This is incredible.”

The next version of Gia represents the most important advancement yet. Instead of requiring brands to prompt Gia for specific tasks, the system will work with brands to establish overall goals and then independently execute to achieve them.

“The next generation of Gia is one where, rather than asking Gia to perform different tasks of influencer marketing, instead you work with Gia to establish a goal for your brand,” Ryan explains. For example, a brand might specify: “The goal is to launch a creator-powered affiliate program that can generate $5,000 a month in GMV.” Gia would then develop and implement a complete strategy to achieve this goal.

“Gia can actually look at the website and determine what their values are. What the brand’s tone and essence are all about. And Gia will go off and recruit creators herself,” Ryan explains. This approach mirrors how brands would work with a talent agency, aligning on goals rather than overseeing each step.

Ryan recently tested this value proposition with a friend who runs a brand called HuggaBuddies: “What if I could work with you to understand your brand goals, and then what if I could propose a creator-powered affiliate program and go manage that goal? Within 30 to 60 days, I’m actively generating sales for you and the only cost is a commission on those sales.” The response was enthusiastic: “If you’ve built that—that’s insane. I’m in.”

The Technology That Makes Gia Possible

The timing of Gia’s development is directly tied to recent advances in artificial intelligence. Ryan, who built AI systems 15 years ago “that were far from as capable as they are today,” was initially cautious about integrating AI into GRIN’s products.

“I viewed a lot of the AI product development that was happening as mostly hype,” Ryan admits. What changed his perspective was the improvement in large language models (LLMs) that occurred in late 2023 and early 2024.

“The actual brain, which is the LLM, has gotten sophisticated enough that it can reason and perform these tasks successfully, whereas a year ago, I would say that was not true,” Ryan explains. He describes a telling moment when upgrading to a newer AI model immediately solved reasoning problems that had stumped older versions.

“That’s a very magical thing, because what it says is the brains have gotten sophisticated enough that they can look at the data and say, ‘Yeah, they match.’ We rely on the brain being smart enough to make those types of decisions.”

This technological improvement enables Gia to understand context, make judgments, and work independently in ways that weren’t possible before. “We are in a world where that has changed. And now it’s on us to leverage that technology and bring the value of that to our customers,” he says.

Refining Creator Marketing

With Gia, GRIN aims to revamp how brands approach influencer marketing, making it accessible and effective for companies of all sizes.

“This is what really unlocks the future of influencer marketing,” Ryan explains. “If you can take what is necessary for a brand to treat influencer marketing more like a performance channel, where I have a budget and I have a goal, and the actual work in trying to achieve that goal is not the day-to-day operational tasks.”

Ryan sees influencer marketing as “word of mouth marketing at scale,” noting that “brands love this concept because at the end of the day, the best way to spread awareness and drive sales is if people recommend other people to go buy your product.” The challenge has always been executing this at scale, which is precisely what Gia aims to solve.

Even large brands with established teams see value in this approach. At a recent event, Ryan asked a customer from a global brand whether Gia would be interesting despite having a large team. Her response surprised him: “Just because I have a lot of people does not mean that we’re not stretched thin either. We’re stretched very thin. An AI technology that could automate a lot of that work is very appealing to us.”

For the influencer marketing industry as a whole, Ryan predicts a change similar to the web adoption curve: “It’d be like building web software in 1999, and most brands are not doing it. But if you fast forward to 2010, if you didn’t adopt the web, you were almost irrelevant.”

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