Let's be honest, AI has moved way beyond the buzzword stage. We're not talking about what it could do anymore; we're seeing what it's actually doing for businesses right now. And in media? It's completely changing how we work, think, and create.
We're witnessing a fundamental shift where AI isn't just a nice-to-have consideration for media professionals — it's actively optimizing campaigns, transforming how we search and interact with information, and reshaping entire workflows. This isn't just another trend, it's a seismic shift that'll continue driving major changes in our industry.
The Reality Check
Here's a sobering stat from Boston Consulting Group: 74% of companies are struggling to get real value from AI investments. Only 26% have figured out how to move beyond fancy demos to actual results. With all the money being poured into AI, we need to think seriously about how it impacts business results, workflows, and long-term strategy.
That's why we're shifting our thinking from "artificial intelligence" to "applied intelligence,” focusing on practical impact rather than flashy possibilities. At this year's Carat Innovation Summit, we explored what this shift really means with leaders from the AI tech and marketing space.
Busting the AI Myths
Let's clear up some common misconceptions that keep coming up:
"AI is a magical oracle" - Nope. AI isn't one singular thing, and it definitely can't solve everything (maybe not yet anyway). We're still figuring out how AI learns and identifying the best ways to train it for our specific use cases. In media, areas like creative generation, attribution, and user journey mapping still need significant development and human input. But there are also areas, like contextualization, data processing, and market research — where AI excels, though they still require human discernment and expertise.
"AI will steal our jobs" - Actually, it's more like getting a really smart assistant. We're seeing AI expand our capacity to handle specialized tasks, freeing up teams to focus on strategic thinking and long-term planning. Human insight remains irreplaceable for strategic decision-making, creative development, data interpretation, and output validation, especially for catching biases or AI hallucinations.
"Just feed it data and it works" - If only it were that simple. Data quality issues persist everywhere. AI struggles to distinguish quality data, leading to potential bias problems and inaccuracies. And here's the kicker: the way AI learns means these little data issues can compound over time, sometimes becoming nearly impossible to remove from knowledge repositories. AI is only as good as the data it's trained on.
Real Talk from Our Team
We asked our Carat colleagues what applied intelligence looks like in practice, and their insights reveal how this shift is playing out:
John Fraze (Paid Search): "AI for me is a little buzzy. There are algorithms out there that do a good job at providing logical answers based on the entirety of the internet. But Applied Intelligence is when a human can take those AI capabilities and put reasoning, logic, and human thought into using them the right way to solve problems. It's about using AI for the time-consuming legwork, then applying that extra check and balance to ensure it's accurate and solving the right problem — not just steamrolling everything with AI responses."
Amy Siegel (Innovation): "We need to stop talking about hypotheticals and put AI into action. For some clients, we partnered with an AI audio and video technology company that took the legwork out of creative versioning in minutes. We could A/B test all the way through Z and include different messaging points without straining planning and creative resources. The performance metrics spoke for themselves: brand awareness increased 6-12 points, favorability jumped 9-22 points, and purchase intent rose 3-18 points. Users were 73% more likely to pay attention to personalized ads."
Mike Gantz (Planning): "Applied Intelligence reframes AI as a tool that enhances our way of thinking rather than replacing us. Today's media landscape is more complex than ever; more data, expectations to execute with speed, and demand for personalized experiences. Smart tools help us work more efficiently so we can deliver faster, smarter, and more tailored outcomes."
Pro Tips for Using AI Tools
Our team shared some practical advice for making AI work better:
Sam Morgan (Senior Manager): "AI augments our work. All writing starts and ends with original thoughts, but AI is great for adjusting tone and giving specific feedback. Image and video generators are fantastic for presentations. AI can do deep research instantly, but you need to give it tons of context. Here's a key tip: it's easier to talk to AI and explain your problem than try to type it all out. I recommend everyone talk to AI about their problems daily. It might give you the wrong answer, but it will give you different ideas about how to approach your bottlenecks."
Jenny Horowitz (Content Director): "When I need quick thought-starters and don't have time to gather a team, AI acts like a fast, flexible brainstorming partner. It's powerful for inspiration when time or resources are limited, but you need to craft prompts that reflect your brand's objectives, tone of voice, and key messaging. And always fact-check cultural references since AI can be outdated or biased."
Bin Wu (Innovation): "We're still experimenting, but AI has significantly changed how we communicate with interfaces — from keywords to complete sentences to visual illustrations of our thoughts. Context is everything: setting the meaning, providing background information, sharing reasons for the task, and being mindful of tone. But even with all these parameters, outputs need human discernment like checking for accuracy, requesting citations, asking the same question different ways."
The Bottom Line
As we continue integrating AI into our work and lives, remember that this technology is still developing. While AI offers incredible potential and exciting possibilities, it's not a magic pill that can solve every problem effortlessly.
When we think about implementing AI as applied intelligence, we need to thoroughly understand the challenges of data quality, how it integrates with existing systems, ethical and legal considerations, usability for our teams, and observability — allowing us to understand and validate how AI systems make decisions.
We must apply discernment and critical thinking when adopting AI solutions. The future isn't about artificial intelligence taking over; it's about applied intelligence making us more effective at what we do best. By shifting our thinking this way, we can utilize AI responsibly and effectively, paving the way for technology that truly enhances our human capabilities.
