AI adoption among marketers hits 86%, but skills training lags far behind
Eighty-six percent of brand and agency professionals now say their companies are investing in AI technology, according to annual research tracking the sector since 2022. That's up from 71% in 2024 and 44% in 2022.
The surge has prompted major brands and agencies to create chief AI officer positions. General Motors, Mastercard, and ZocDoc appointed AI chiefs in 2024 and 2025, as did agencies Golin, Luckie & Co., and Horizon Media.
Yet marketers are struggling to build the expertise needed to use these tools effectively. Training programs haven't kept pace with adoption, creating a gap between how much companies are spending on AI and what they're actually getting back.
The skills problem
Dan Gardner, co-founder of creative agency Code and Theory, said the issue isn't learning new software-it's rethinking how teams work. "Anybody can learn a new tool," Gardner said. "Upskilling and reskilling is multiplying the value of your human ingenuity. Using an AI tool to design a little easier is not making them more skilled. They're just using a new tool."
Matt Maher, founder of research firm M7 Innovations, found a similar pattern. Users understand basic AI tools like ChatGPT and Gemini at a surface level, but companies aren't using them to their full capacity. "There is a delta between understanding tools like ChatGPT, which has 800 million weekly active users, and then using them to their utmost potential," Maher said.
Marc Maleh, global CTO at design and technology agency Huge, tied the problem to cost. When organizations adopt AI before developing a clear plan for how to use it, they often end up paying for infrastructure-GPUs and TPUs-without seeing proportional returns. "What if I want to turn on 500 more seats of Claude code? What does that look like financially? Am I going to get that money back if I'm only getting a 30% productivity increase?" Maleh asked.
Most marketers stick with off-the-shelf tools
Eighty-five percent of survey respondents said their company uses out-of-the-box AI tools rather than building custom solutions. Only 40% are building proprietary tools with existing large language models like Google's Gemini or OpenAI's GPT, and just 19% are building and training their own LLMs in-house.
The cost and complexity of custom development explain the preference. Smaller companies often lack dedicated AI teams to handle the work.
The market is shifting to make this easier. Adobe and Google recently integrated Google's Gemini, Imagen, and Veo models into Adobe's creative tools. "A year ago that wasn't the case. It was Firefly or nothing," Maleh said. "We went from a place where a lot of platforms were walled gardens to where it's more opened up."
Maher said brands are now stacking multiple tools together-using Copilot as a base layer, then adding Claude and custom APIs on top. This approach is cutting costs. "I'm starting to see cost efficiency gains-partnering with the bigger companies, but creating their own version or sandbox. You're saving a lot of money because you're not having to build it from scratch," he said.
Consumer-facing AI is already in use
Brands are deploying AI in customer-facing applications. PetSmart relaunched its member program using AI to personalize deals based on purchase history. Guitar Center built a chatbot called Rig Advisor to help customers find the right products.
For marketers looking to close the skills gap, AI training programs designed for marketing managers can help teams move beyond basic tool usage to strategic implementation. Understanding how to structure AI workflows and measure their impact is increasingly essential as adoption spreads.
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