AI is Only as Good as Its Data Fuel and the Human Touch

There are countless areas where AI can be used in advertising—hitting the right KPIs, buying on brand-safe traffic or using smart targeting strategies.

The real goal of AI is to automate as much of the work as possible and make life easier for marketers by mimicking human decision-making. Humans still need to guide AI, telling it what to target and how to approach specific goals. AI can handle a lot once given that direction but it’s not yet at a point where it can fully replace human oversight. Marketers must understand AI's limitations while being comfortable with its growing capabilities.

As AI develops, marketers must find tools to handle more tasks effectively, especially when combined with first-party data. The more data AI can learn from, the better it performs. For example, if AI can understand what has already worked in a campaign, it can replicate those successes. Without data, AI faces a "cold start" problem, where humans must step in to guide it.

Human involvement is still needed in creative areas where decisions aren't strictly data-driven. For instance, AI struggles to build something entirely from scratch, as it tries to do too much at once. However, if a human provides an existing image or creative asset, AI can adjust and optimize it more efficiently than humans.

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The key is knowing where AI excels and putting it in the right places. Organizations need to rethink their structure by identifying highly data-driven and repetitive tasks—those are ideal for AI. Manual optimizations and processes with prior data for AI to learn from are perfect use cases.

If a company doesn’t have a lot of data, it should consider partnerships. The first question to ask is whether the problem they’re facing has already been solved by someone else. In that case, partnering with a company with the data and models needed to solve the problem can save time and resources. However, if the problem is unique—such as in advertising, where a brand may have specific goals that no one else has perfect data for—the company will need to find the next best thing. This might mean looking for a model that has been proven effective within their industry, even if it’s not a perfect match. The key is recognizing how unique the challenge is and finding the right tools or partnerships to address it.

AI thrives in scenarios involving massive amounts of data, like making split-second decisions on bidding in advertising, which would be impossible for a human to do manually. But humans are still essential for more open-ended, creative tasks. That balance might shift as generative AI evolves, but for now, it's all about knowing which tasks AI is best suited for and where human input is most valuable.