AI has officially crossed the line from novelty to necessity. In Branch’s recent State of App Growth survey, 100% of marketers said they’re already using AI in their workflows for everything from predictive analytics to creative optimization.
But using AI and using it well are two different things. Most teams have plugged AI into their stack, but far fewer have figured out how to turn that technology into real business impact.
In a recent Marketing Dive webinar, Branch VP of Product Irina Bukatik and Movable Ink Associate Director of Product Marketing Erica Dingman unpacked what effective AI adoption really looks like.
Here are five takeaways from the conversation.
1. Start with the problem, not the tool
Marketers are experimenting with AI in meaningful ways: generating and testing creative at scale, personalizing content for millions of users, and optimizing budgets and bids in real time. But while AI can automate most things, that doesn’t mean it should. The most effective strategies begin with a clear business challenge: What problem are you trying to solve? What does success look like? And what data or processes already exist that could make that outcome easier to reach?
Once those questions are clear, the role of AI becomes obvious. Instead of chasing new features or vendors, you can focus on how the technology amplifies what’s already working.
“Like every new technology, there’s a risk of over-focusing on the tools rather than the problem we’re trying to solve.” — Irina Bukatik
Key takeaway: Lead with intent. Tools follow strategy, not the other way around.
2. Your AI is only is as good as your data
Data is AI’s fuel, and the cleaner and fresher it is, the farther you’ll go. When models rely on outdated or fragmented data, they make bad predictions and reinforce weak assumptions. That’s why smart teams obsess over quality and recency.
Take mobile attribution data as an example. Every customer interaction, or inaction, tells your system something valuable. The more data your models have, and the more signals they collect from real user behavior, the better they become at spotting what works. When those signals span mobile, web, connected TV, and beyond, AI starts to see the full picture of how users move between devices and channels. Over time, those learnings compound to help marketers anticipate needs instead of reacting to them.
“Any AI product is going to get better the more you use it. But you need to make sure it gets exposed to the right data.” — Erica Dingman
Key takeaway: Keep your data connected, accurate, and current. It’s the single biggest driver of AI performance.
3. Good UX drives adoption
Marketers will only adopt AI tools that feel natural to use. The most successful platforms fit into existing workflows.
Bukatik compared today’s AI moment to the early days of mobile: the technology existed, but intuitive design eventually made it accessible to everyone. The same principle applies here. If your AI tools feel clunky or opaque, teams will bypass them no matter how advanced they are.
“UX is what made app stores and iPads take off when the Palm Pilot already existed.” — Irina Bukatik
Key takeaway: If it’s not intuitive, it’s not scalable. Think about how your teams will use it, not just its outputs.
4. Transparency builds trust
AI-generated content is everywhere, and audiences are paying more attention to how brands use it. Consumers can spot AI slop from a mile away.
That’s why transparency matters. We’re starting to see brands be clearer about when and how AI fits into their processes. When marketers use AI to extend human creativity (and capacity!) instead of replace it, the result feels thoughtful and consistent.
“We’re at an interesting point where we’re testing what customers are comfortable with, and brands are pushing the boundaries. We’re just starting to find out what level of risk is worth it and where AI should take a backseat.” — Irina Bukatik
Key takeaway: The goal isn’t to make AI invisible, but to make it intentional and trustworthy.
5. The future is human and machine
Despite all the talk about AI replacing jobs, the real story is collaboration. AI can crunch data, spot patterns, and execute faster than any team, but it can’t replicate human empathy, creativity, or strategy.
The best marketers understand that balance. They use AI to surface insights and free up time, then apply their own judgement to turn those insights into big ideas.
“We’re already seeing that consumers are smart. They don’t want pure AI. It’s marketer and machine together, and it’s going to be that way for a long, long time.” — Erica Dingman
Key takeaway: The most effective teams know where AI ends and human creativity begins, and they design workflows that let both do what they do best.
