As AI continues to transform digital advertising, there is no shortage of potential use cases. However, successfully leveraging AI in digital advertising requires more than the adoption of new technologies. To maximize its immense potential value, ad ops leaders must combine AI with both human oversight and a comprehensive automation approach.
By understanding the relationship between AI and automation, advertisers can better leverage the two technologies together to mitigate their individual risks, overcome traditional barriers to success and achieve transformative benefits that extend across the organization. For advertisers, that can mean increased operational efficiency and more productive staff.
Practical benefits of automation and AI
There are myriad benefits for advertising leaders looking to adopt automation. Because of the many inherently pattern-based, predictable tasks involved, as well as the vast amounts of data needed, digital advertising lends itself well to robotic process automation. Predictability, consistency, scalability and centralized management, and cost reduction for repetitive tasks are among the few at the top of that list of core benefits.
The day-to-day impacts that teams will feel are related to significant time reduction on critical, yet historically time-consuming elements of their advertising campaigns, including new account builds, budget management and pacing, and report generation. Handing off essential taskwork to automation has the potential to positively impact your service levels, and in turn, improve the customer experience and overall satisfaction.
As a closely related technology, AI can amplify these benefits by helping advertisers provide value that requires a human touch.
While a large portion of ad execution centers around settings and non-human to human interactions, things like creative messaging have been difficult to automate because they require a “human feel.” AI does an amazing job here, coaxing a potentially cold tone of a message into one that is compelling to interact with.
For example, you may use AI to increase variation in ad content. If the outcomes are scrubbed for quality, content libraries can be incorporated with business data to generate quality messaging. It can also help with customizable reporting, allowing creativity to flourish in how you convey value to your clients. Ultimately, AI in advertising is most powerful when used to simplify execution, and therefore it is most valuable when activated at scale. And only automation can make that possible.
How to evaluate automation readiness
Automation is a gateway to a better version of your organization, but automation itself does not happen at the snap of a finger. Organizations must prepare for what will likely be a major shift in how they approach their work. It is a journey, which for enterprise-scale advertising organizations often includes potential barriers such as brand/co-cop compliance, a need for advanced experimentation and customization, lack of aligned business data hygiene and consistency, as well as inertia—resistance around adopting an automation mindset.
Automation does require an organizational change. However, advances in data ingestion, automation technology and now the ability to deploy AI through automation can reduce the barrier to entry. Often, most organizations considering automation are more ready than they may think and automation and AI make it a no-brainer for long-term growth.
Just think of your own best practices within your organization—with automation, you can take those best use cases of your business to create sustainable processes and develop a value proposition with endless possibilities for scale.
Combining AI with automation
Once you have established your automation foundation, you can now more effectively leverage AI. To do so for maximum intelligence, advertisers can mitigate its risks and focus on its best uses.
Just like anything, automation comes with risks that advertising leaders should be cognizant of. Many wonder how automation will impact compliance, for instance, robotic process automation technologies can be modeled to be brand compliant as tools exist that can interpret rules like automotive OEM compliance rules and Fair Housing Act regulations.
AI also shows great promise in data normalization, campaign content generation and even performance interpretation. All of those should be options for your use case, but you need to understand if and when they should be used. If you are unsure if AI-driven automated solutions will cause compliance violations or will violate data use rights, don’t use them.
AI can augment a well thought out strategy. However, while automation can improve predictability, the more AI does, the less you are in control of predictable outcomes. Strike a balance here. Rule systems are emerging to self-audit the use of AI to allow safer use of it.
The possibilities for an ad ops team
The analogy to reflect upon is the difference between an excavator and a shovel. No matter how skilled your team may be—or the big visions they have for your landscape—if they’re all using shovels to execute on your vision, it may never come to life. Put them in excavators, however, and they can quickly move more earth with far less exertion.
This analogy can be applied to automation. By simplifying execution where your teams need it most, a thoughtful and human-guided AI approach can help you maximize these benefits.
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Eric Mayhew is the co-founder and chief product officer/president of Fluency, a leader in robotic process automation solutions for the digital marketing industry. Mayhew’s years of experience in software engineering and digital advertising have led him to develop solutions that have helped change the way global enterprises and brands operationalize advertising.
