From automation to opacity: Overcoming marketers’ AI anxieties

Artificial intelligence is revolutionizing businesses across industries. More than half of the executives surveyed in a 2017 PwC report said that AI solutions were already increasing their companies’ productivity. As usual, marketers are at the forefront, embracing AI at a particularly rapid pace.

But while any new resource can create excitement in some, it can make others feel uncertain—sometimes even worried about their futures. Many marketers fear that onboarding AI will fundamentally change the way they do business, and not completely for the better.

Below, we’ll take a cool-headed, logical look at how an AI-powered industry is an opportunity for all. We’ll dive into each area by exploring the misperceptions at the heart of these anxieties through the anonymous confessions of several marketers.

Marketers’ jobs have become more and more unwieldy. Their customers are spread across a growing array of devices and channels. It can be tough—and monumentally time-consuming—to try and make sense of all that data. AI tools are designed to cut through the muck, swiftly organizing information and surfacing insights into customer behavior.

The real problem is that so many humans are expected to function like computers. Today’s marketers are asked to comb through oceans of data, assembling it into something structured and coherent.

AI’s job is to take on that extra workload and free up marketers’ time to do higher-level thinking—what they do best. AI isn’t going to make marketers’ jobs obsolete; it will make certain aspects of their jobs manageable for the first time.

It’s true that AI can eliminate mountains of rote, mindless tasks. For example, the Associated Press used AI automation tools to speed up the arduous task of filling out earnings reports. That allowed its staffers to invest that time in telling stories instead. That value is anything but “limited.”

But AI can do much more, augmenting our work by making new connections that give us an edge. For instance, AI tools can comb through social media conversations at breakneck speeds, then take that analysis to the next level by closely analyzing tone and sentiment.

AI can provide invaluable insights that inform our decisions; all we’ll have to do is apply those insights to our creative and strategic decisions. And AI lets us do that in real time.

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Hiring engineers and data scientists is never a bad idea, if you can afford it. But with well-designed AI software, it isn’t necessary. The most advanced AI-powered marketing tools now come pre-trained with tons of industry knowledge, and they’re designed to present their insights in marketer-friendly formats, like dashboards.

That’s the whole point: The computer handles the number crunching behind the scenes, then presents its data-based recommendations in a relevant way through the systems and tools you’re already using. Gone is the day of relying on IT, or on constant manual data reports, to get our jobs done. Finally, everything gets faster.

The right AI tools will merge dozens of different data sources onto a single interface on one platform. That alone will help cut through the confusion. Still, you’ll need a solid idea of where you want to elevate your workflow and illuminate new insight within your business. Select AI tools that can be customized to address as many unique needs and costly inefficiencies as possible.

Of course, companies can, and should, speed up the learning process for staffers. Calling on tech partners to share guides and tutorials on their tools is a great start, and it’s very easy to learn from there.

There’s a term for this: the black box. It’s the idea that humans won’t understand all of the nuanced calculations and connections that go into a decision. And the more opaque the box, the less connected you might feel. After all, marketers are used to making deeply informed decisions based on intimate knowledge of the consumer.

But tech partners can do a lot to make sure their software’s reasoning is transparent. IBM Watson Marketing, for instance, shows its work when it does things like suggesting “personalization rules” that determine what message or offer each consumer receives. That helps marketers understand exactly how the software reaches its conclusions—and exactly how confident it is that its recommendations will work.

Then there’s Watson’s Customer Experience Analytics tool, which allows marketers to “replay” digital sessions, observing the customer journey from an individual consumer’s perspective across any and all digital platforms, spotting any missed opportunities or customer issues along the way.

With the right AI platform, your job will become less opaque, not more.

It’s crucial that human marketers get the final say. Small mistakes are part of the machine learning process; that’s why marketers need to be sure that their AI tools are offering recommendations, not taking unilateral action.

Fortunately, no AI system worth its salt is going to decide which creative copy to use, or which social platform to advertise on. What it can do is provide us with context and analysis that used to take us weeks to arrive at. It’s a partnership: On one side, AI extracts and analyzes immense amounts of information; on the other, we use that insight to make smarter, faster decisions.

The real mistake can come on the human end—by not onboarding AI in the first place. With more data streams available than ever before, each one affecting the success of campaigns across every conceivable digital channel, marketers need the help of these augmentative systems to predict and outthink the challenges of both today and tomorrow.
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