Should marketers be worried or excited about new artificial intelligence (AI) technologies? After generative AI (Gen AI)  suddenly became productized, commercialized, and evangelized, the sheer scale of the opportunity to leverage AI for marketing seemed to have surprised many. It shouldn’t have.    

Pockets of experimentation with AI over the last few decades have delivered a series of programmable tools to help people think differently about art, games, and more. This idea still holds true, as AI offers marketers an immense opportunity to reimagine how to effectively engage people while doing more with less, a pervasive directive with which every CMO today is expected to comply.  

The Value of AI and Generative AI         

Marketers have long analyzed data to personalize and predict offers and engage prospects and customers. However, unlike traditional approaches, AI can learn to automatically refine its methods, handle intricate and non-linear patterns, and manage vast volumes of data. In a business context, this means it can not only automate tasks but also continuously improve its performance and adapt to evolving challenges.  

Gen AI is the subset of AI primarily focused on consuming and creating content, executing creative tasks that aim to emulate human-like cognitive abilities. When combined with decision-making capabilities in a well-designed process, AI can help marketers select and render the content most likely to drive people to take the next step in their buying journey.  

Analyzing data to predict next best actions and then generating relevant messaging has applications across every industry. This means retailers can personalize offers at scale by using AI to analyze purchase history, and hotel brands can generate a contextual stream of ongoing communications to provide personalized recommendations based on relevant third-party data such as travel behaviors or preferences. Banks can use first- and third-party data to quickly produce offers to potential high-value people making large deposits, promoting favorable savings products they may not be aware of.  

Think Big, Start Small 

AI promises to help marketers discover innovative ways to improve and accelerate many day-to-day tasks, drive greater efficiency, and maximize resources. How should brands approach incorporating AI into their marketing operations? First, they should start small and evaluate existing data and processes, identifying areas where AI can make immediate gains while minimizing the initial cost of entry and risks.  

Here are the four steps we recommend marketing leaders take to begin leveraging AI technology: 

Step 1: State your vision.  

Articulate a clear vision or end-state, focusing on what is most relevant and important for your business or industry. Start by identifying your goals and determining if AI can help spur improvement. To evaluate your readiness, ask yourself questions like, “Do we have the right data, infrastructure, and talent in place?” Or, “could a partner help?” Then develop a high-level test plan that includes aligning across all areas of your business. 

Step 2: Power up your data.  

Once you have a plan outlined, consider enhancing your first-party data to further power the decisioning process. Without a robust data foundation, your AI solutions may not have enough information to develop accurate insights to produce impactful actions or creative messaging and offers.  

Step 3: Fill important gaps in your customer journey.  

Resource-constrained marketers are often unable to create all the content necessary along key points in the customer journey to enable a true omnichannel experience. GenAI can help take a library of human-created assets and optimize or version to fill the gaps, improving creative teams’ productivity.   

Step 4: Take a more dynamic approach to campaign execution and optimization.  

In more advanced cases, marketers can integrate AI for decisioning and campaign execution. Media strategists and buyers can become better equipped to optimize channel selection and automatically cap audience frequencies or leverage more sophisticated modeling for planning purposes. Analysts can dynamically model audiences to enhance reach and precision and test and optimize campaigns in real time.  

Challenges to Watch Out For 

As with the adoption of any new technology, embracing AI does come with some challenges. Marketers should consider ethical concerns that require strict data governance so brands stay on the right side of protecting people’s privacy. Well-trained staff is needed for the human curation required to maintain brand safety. Poor data quality and data silos continue to obstruct progress, and black-box measurement providers limit the effectiveness of AI-generated insights.  

An effective approach starts with identifying gaps in data, technology, and analytics, leveraging first-party data to optimize operations, and developing a vision for which enterprise goals AI can solve. It’s time to be excited about the time savings and rapid optimization cycles AI can enable for marketing, including the potential to shatter the limits of human capacity for creativity and innovation.             

To find out how Acxiom can support your AI initiatives, email us at [email protected].