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Automation vs AI

Everyone’s talking about automation and artificial intelligence (AI). In the world of advertising, agencies and brands are investing in automation to reduce manual tasks, streamline operations, and improve customer engagements and experience. AI, on the other hand, ranked as the second most-popular area of increased investment for consumer experience strategy in a July 2021 survey of U.S. senior marketers—beat out only by data quality. 

On one hand, AI and automation are hailed as frontiers of innovation in technology. On the other, a lack of understanding has contributed to the fear that these innovations will take jobs away from (human) workers. Luckily, experts say that advances in automation and AI generally don’t eliminate jobs—they eliminate tedious and manual tasks. This in turn enables highly skilled people to do high value work, generating higher performance and revenue. 

Even as these technologies spur conversations and make news, how many of us truly understand the specifics of what’s being discussed? The terms “AI” and “automation” are often used interchangeably, but in order to make smart decisions about how to invest in them, it’s important to know the difference. 

What’s the Difference Between Automation and AI? 

Automation is a broad category that encompasses artificial intelligence, software, robotics, and more. Importantly, the concept of using technology to perform a task in a way that minimizes human manual labor is nothing new. For example, simple everyday tools like coffee makers would fall under the automation umbrella. 

AI describes a specific way of automating tasks. In AI, computer systems utilize large amounts of data to mimic human intelligence—they learn, predict, and recommend what to do next. 

How are Automation and AI used in Marketing and Advertising? 

Automation in Marketing and Advertising 

Marketers and advertisers use basic automation in many ways, from leveraging programmatic advertising to scheduling payments ahead of time. Yet the advertising industry lags behind in its adoption of more advanced opportunities to automate. Media complexity has tripled in the past two decades, and without the right automation tools, marketers waste much of their time switching between various disparate platforms and spreadsheets.  

What does good marketing automation look like in practice? Basis unites automation with holistic media management, allowing users to plan direct buys, programmatic, advanced TV, search, and social via a single interface. Its integrated reporting feature pulls data across all digital campaigns into one place for easy report generation. Automated billing, built-in messaging and negotiation tools, and a universal dashboard all serve to allow media planners to focus on more complex tasks. 

Workflow Automation 

Workflow automation describes processes that employ preset rules to run a series of tasks that are automatically executed without human intervention. For example, Basis automates planning, negotiating, buying, reporting, analytics, optimizations, and billing into one seamless workflow.  

This type of automation results in increased efficiency and speed for media professionals, removing manual tasks and freeing up time for more creative, strategic, and fulfilling work. 

In Moving to Simplicity and High Value: A Call to Action for Workflow Automation and People Augmentation, the 4As and 614 Group note the COVID-19 pandemic as the perfect opportunity to “move digital advertising away from the constraints of legacy technology and cumbersome workflow.” As factors outside of our control accelerate the formation of a new status quo, our industry has a big opportunity to make the “new normal” a more fulfilling one for media professionals. Automation is the perfect place to start.

AI in Marketing and Advertising 

The list of ways in which AI can be leveraged in the marketing space is growing every day. However, there are a variety of subsets that are already tried-and-true—such as machine learning, behavioral marketing, contextual marketing, and conversational marketing. 

Machine learning describes any tech that uses algorithms to find patterns in large amounts of data. Given that reporting is a common pain point for marketers due to the volume and disparate nature of the data they have access to, machine learning provides immense value when it comes to campaign measurement and analytics.  

AI solutions like behavioral marketing, contextual marketing, and conversational marketing can all provide crucial information about a target audience without resorting to cookie-based identity solutions. These types of AI help to build personalized customer experiences and target precise audiences. 

AI technologies often work by recommending solutions based on the patterns they find. Importantly, most uses of AI are still dependent on humans to establish strategy and parameters, as well as to evaluate the insights provided by AI, and make adjustments accordingly. As AI eliminates manual tasks, marketers are freed up to focus on high-level strategy.

Basis, for example, leverages a variety of AI tools, including machine learning, algorithmic adjustments, bid multipliers, and group budget optimization. These features allow our team members to spend more of their days on the creative and strategic work they enjoy, versus the manual work that reduces efficiency. 

The Future of Digital Media 

Automation and AI are broad categories that encompass a variety of complex technologies, and it’s by no means essential for every marketer to be an expert. Looking into the future of digital media, however, automation and AI will have enormous impact in setting apart the brands and agencies that implement them—in regard to both marketing success and employee satisfaction. 

Now that you know the difference between these types of tech, you’re already ahead of the pack!