Every year, Audience audit publishes a study on what clients really want from agencies, and the 2025 edition revealed a statistic that should give any agency leader pause: 77% of clients say they are more likely to hire an agency that is a recognized expert in AI (not just a self-proclaimed one). But only 32% believe their current agency fits that description.
Here’s what’s most telling: When asked what they expected from their agency when it comes to AI, clients didn’t say “efficiency” or “cheaper deliverables.” They want new ideas, more precise analysis, and real guidance on how to use AI themselves. In other words, they not only look for agencies that wear AI. They want partners who know how to think with it.
At Quantious, mastering AI is not a feature, it’s a team standard. Every producer, strategist and designer is expected to not only keep pace, but to lead. And we don’t just talk about it at launches, we practice it every day.
Want to develop true AI fluency across your team? Here are five ways we’ve made it part of our daily work.
1. Invest in professional development as if it were our job (because it is)
Professional development here isn’t a once-a-year checkbox, it’s a cultural value. We budget for AI courses, certification programs, and conferences because we believe time spent learning is time well spent. We’ve encouraged team members to tackle everything from AI marketing bootcamps to building apps with vibe coding tools like Replit, Lovable, Replay.io, or Base44 (seriously, a project leader with no coding experience just built their own app!).
We believe in fostering a culture of experimentation, and to some, our approach seems a bit risky. When we invest in the professional development of our team members, we know that it will not always instantly translate into value for our clients. But guess what? Innovation comes from learning and exploration, and that’s exactly how our teams always end up ahead of trends.
2. Host team-led AI workshops
Our favorite AI forecasters are each other. When a team member discovers a new use case, such as creating a custom GPT or using AI to develop complex Excel formulas, they host internal workshops to share what they’ve learned. We’ve held workshops on everything from generating AI product images to deepfake identification. We document our processes, record quick tutorials of what we’ve learned, and aim to keep knowledge moving quickly.
3. Encourage experimentation in live work.
We don’t treat AI as a lab project. We build with it every day. Designers test design variations with imaging tools. Marketers use AI to conduct research for brand sentiment audits or to map user journeys. Copywriters turn notes into outlines and organize their thoughts before drafting. We’ve learned how to craft meaningful prompts, how to develop our own agents, and how to develop some very complex spreadsheet formulas using AI. We automate time-consuming processes and use Bluedot, Slack, and Limitless to transcribe company meeting notes in real time. We use these tools with our brains, not instead of them.
In every aspect of our work, we remember that AI is a collaborator, not a substitute for hard work and creativity. Say it with me: you can’t just check out and let the AI do it all for you. (Just ask Randy Marsh from South Park; it doesn’t end well!)
4. Treat AI Usage and Safety Guidelines as a Living Document
AI is advancing rapidly, as are conversations about safety, security, and ethical use. That’s exactly why we treat our AI guidelines as a work in progress, rather than a static rulebook. Leadership actively invites participation from our entire team to highlight new risks, suggest safeguards, and share best practices.
AI accountability is a shared approach we take and we want to ensure everyone has a role to play in mitigating data privacy and bias. This has led us to adopt a smarter, safer and more thoughtful AI practice that evolves alongside technology.
5. Help customers navigate the AI maze
AI tools evolve daily and most of our customers are trying to understand what is worth their time, what is safe and what really works. The real value lies in making AI seem less overwhelming and more actionable.
That’s why it’s vital to not only use AI to drive internal efficiency, but also help customers make it work for them in their own workflows. Whether creating custom GPTs, mapping out automated content workflows, or guiding teams through rapid strategy, we treat AI as a collaborative layer in the customer relationship.
And we are transparent about it. When AI plays a role in our work, we explain how, why, and what it means for outcomes. That clarity builds trust and helps prepare our clients’ teams for the future.
Our work is not only wear AI: is to help our customers understand it, apply it responsibly and stay ahead. That’s where the real value is.
The future of creative work won’t depend on opening a browser tab and launching ChatGPT. It will be powered by humans who can automate a tedious quality control process, use artificial intelligence to detect brand inconsistencies in campaigns or extract information from raw customer feedback, securely. Because knowing when not to use AI is as important as knowing how to do it.
Lisa Larson-Kelley is founder and CEO of Quantious.
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