That larger question is important, and has wide-reaching ramifications on the livelihoods of countless creative professionals. As it stands, the answer tends to be somewhere in the middle: AI can be a vital tool in idea generation and research for content creation and digital marketing campaigns (read more about ideal uses for ChatGPT here), but demands human oversight to ensure accuracy, provide brand voice, and many other key factors that give content personality.

While questions surrounding ChatGPT for creative campaigns remain open-ended, it can’t be understated how important AI technology is broadly for digital marketing. Specifically, machine learning algorithms — a subset of AI — can find efficiencies and areas of impact in the mountains of data even the most skilled marketers simply don’t have the time to analyze.

Progressive advertisers should be leveraging AI in a host of applications; in this piece we’ll cover four key areas where AI can have the greatest impact.

Improving Targeting and Audience Segmentation

In the good-old, Mad Men days of advertising, brands could get by on effectiveness of creative and market saturation; produce a memorable ad and blast it to as many people as possible. The larger your budget, the broader your reach.

And while those “good old days” may have been preferable in their simplicity, the digital advertising space is a completely different world. With hundreds of digital channels that consumers engage with in a given week, even the most compelling creative, product, or offer may not be seen by the audience it would have the most impact on, regardless of budget. Furthermore, managing this galaxy of digital channels and millions of potential customers is impossible for a team of even the most competent marketers. This is where AI and data modeling are so vital in digital marketing.

AI can analyze a nearly infinite scale of consumer activity in order to segment groups based on a host of factors from their demographics to their interests to their observed behaviors. This ability to hyper-segment audiences creates the data needed to determine the efficacy of campaigns and ensure that the right ads are getting in front of the right audiences.

Better Messaging Personalization and Product Recommendations

Audience segmentation is great for culling a massive cohort down to more focused groups, but AI can also provide a more granular, consumer-level benefit in messaging personalization. In the same way analyzing data for segmentation is impossible by human teams at the scale required of digital marketing, personalization presents an even tougher challenge for marketers. It’s not like every consumer is assigned a marketer to produce individualized messages for, right?

Building off of audience segment data, AI can analyze consumer-level data to provide contextual personalization to maximize ad efficacy. This personalization can be everything from targeting specific products a consumer has previously shown an interest in, to contextual personalization of tailored messages based on device or channel and beyond. AI can help ensure that the right message is put in front of the right customer in the right place at the right time.

Additionally, this use of AI for personalization can drive more predictive and intelligent product recommendations based on consumer browsing habits and observed preferences. Rather than simply offering similar products, consumers can be given more focused recommendations that align with their purchase history or interests, which creates better customer experience and promotes retention efforts.

Optimizing Digital Ad Spend

Better targeting and personalization are transformative ways to utilize AI to improve customer experience while also bolstering key KPIs in lead generation and conversion. But all of that would be less relevant if it didn’t also impact the bottom line. AI can and should be leveraged to make real-time budgeting decisions.

While these hundreds of digital channels may be the same from a consumer perspective, for advertisers, each unique channel comes with its own value. Having the right audience and right messaging for that audience is essential, but there are mathematical implications to the value of ad placement on each of those channels in terms of ROI.

By leveraging AI, advertisers can automate their bidding strategies for each channel to maximize efficacy and better manage budgets. Rather than spending large percentages of budget on higher-profile channels that may not yield optimal ROI, automated bidding can place more ads on less costly channels for greater impact.

What’s more, these strategies can be automated to A/B test against one another and adjusted in real time to yield the best results. Once again, AI takes tedious tasks that can’t be effectively executed by teams of marketers and streamlines them to achieve optimal ROI and better understand the value of specific bidding and ad placement strategies.

Building Reliable Data Stores and Fighting Fraud

One of the more difficult aspects of digital marketing is understanding the mountains of data generated on a daily basis. And without a handle on what placements, bidding strategies, or audience data were most effective, advertisers won’t have metrics to build off of going forward, or have sound numbers to present their business case. As any marketer knows, it’s imperative to show successes in order to instill organizational confidence in the department.

AI is instrumental in organizing and making sense of data. From site analytics to campaign performance, AI and machine learning can make connections across countless channels to uncover insights and efficiencies human analysts might miss. Oftentimes these analytics are siloed in different systems, and more often than not those systems are unable to communicate with each other. AI is sort of like a common language, and that language is data and pattern recognition.

Further, with so much data, there is always a difficulty in verification. As mentioned, AI is particularly skilled at finding patterns and identifying anomalies. Users producing aberrant behavior, or large click volumes from single addresses that could potentially impact campaign performance can be easily identified and rectified using AI. Predictive modeling can also work to fight these fraudulent activities before they occur by identifying users likely to commit fraud based on past behavior.

AI Can Be Your Greatest Asset

Artificial intelligence and machine learning can be a source of stress for digital advertisers worried about their roles being automated. But as many experts are now predicting, it’s not so much a matter of AI replacing jobs, but a matter of workers understanding how to utilize AI to improve their jobs and manage it effectively.

While there are certainly some ethical questions on the uses of AI, particularly for creative output, the truth is that the capabilities of the technology can find unprecedented efficiencies that can be transformational for both customer experience and budget management. So now is not the time to fear or reject AI, but do your research and figure out the best ways to leverage it to your advantage.

Interested in learning more about how AI is transforming digital advertising? Check out our latest webinar, Rise of the Robots, on YouTube.