As we step into 2017, we find ourselves face to face with that familiar sensation that often accompanies a change. It’s equal parts uncertainty, hope, energy, and anxiety, a combination of the feeling of trying to fall asleep before your birthday as a child, and trying to fall asleep before a big presentation as a business professional.
Late last year, while I was diving deep into research for my machine learning series, I found myself faced with the questions that many marketers have been asking themselves, especially as we head into what will almost certainly be a big year for artificial intelligence. What does this actually mean for me and my company? Is my career at stake?
At the same time, like many marketers, I’m very interested in the technology. It fascinates me. Its evolution from fictional obsession to mainstream tool has been beautiful and messy. Whatever—it’s just straight-up cool.
But watching artificial intelligence from the outside and understanding the technology are two completely different things. I wanted to get closer to this digital marketing technology so I could understand what was around the corner (and, if necessary, re-evaluate my professional choices). Inspired by his presentation at MarketingProfs’ 2016 B2B forum and his work on the Marketing Artificial Intelligence Institute, I reached out to Paul Roetzer, CEO of PR/2020, author of The Marketing Performance Blueprint, and creator of Marketing Score, to learn more about the future of work and where AI fits in.
Artificial intelligence is the broad term that refers to the technologies and processes of making machines smart, which in turn augments human knowledge and capabilities. Artificial intelligence may seem like a futuristic concept, but its use is widespread among companies we interact with daily, including Netflix, Amazon, UPS, Facebook, Google, Microsoft, and Apple. AI is transforming industries and redefining how we learn, communicate, and live as consumers.
Machine learning (ML) is a subset of artificial intelligence. While traditional marketing technology is built on algorithms in which humans code sets of instructions that tell machines what to do, with ML, the machine creates its own algorithms, determines new paths and unlocks unlimited potential to advance marketing, business, and mankind.
John Koetsier has a great post on Medium that shows a simple visual to understand the relationship between the terms.
Disruption of the marketing industry is coming—but in the short term, AI technology will largely enhance human capabilities, not replace them.
While there have been tremendous advances in AI recently, specifically within sales and advertising, the reality is that most marketing AI solutions are still very narrow in their application and require a high degree of human interaction to deliver on the value promised.
For example, we’re very bullish on machine-assisted content using natural language generation (NLG), which takes structured data and turns it into text. The Associated Press uses Automated Insights NLG technology to write thousands of earnings reports per quarter, and we’ve been using NLG for more than a year to produce Google Analytics reports (cutting analysis and production time by more than 80 percent). We’re now building models to automate data-driven reports and content, such as blog posts, emails and ebooks.
But NLG is surface-level AI. It still requires humans to create and evolve template narratives. Once those templates are written, then the machine can tell the stories at scale. There’s a chance that it could eventually replace some writers, but the more likely outcome is that it will continue to free writers up to work on the creative and qualitative content humans are uniquely capable of producing.
While content creation seems to be safe for now, the roles most likely to feel the affects of AI first include telemarketers, market research analysts, SEO specialists, paid media buyers and website content managers. I would also pay very close attention to the role of content strategist. While it’s not currently possible to automate marketing strategy as a whole, many of the AI-powered marketing companies we’re seeing emerge are focused on driving efficiency, productivity, and performance within the content strategy space.
What will change is that marketers will have more power than ever to tailor their communications to the needs of consumers, often in real-time. They’ll have more insight and impact for less time, money and effort than ever before. But that won’t change the need to provide relevant, useful and valuable content to consumers—at the right time, in the right way.
For SEOs in particular, this is more important than ever. Google is at the forefront of AI and ML research. AI is baked directly into their search product, using technology like neural networks and deep learning to surface the best search results based on user intent. Rand Fishkin of Moz has published a number of valuable pieces on the impact of AI on SEO:
There will always be a place for human beings in the story of artificial intelligence, as long as we emphasize the high-value creative tasks that only we can do. The future of marketing—and social media marketing—is going to be written by highly skilled humans working hand in hand with intelligent machines. Machines already automate repetitive social media marketing tasks like scheduling. They are beginning, through chatbots, to automate customer messaging and support.
As in content creation, strategically leveraging AI allows savvy marketers to focus more of their time and resources on communicating brand stories and value propositions to consumers. It will help them scale those efforts using fewer resources, providing brands that effectively leverage AI a massive advantage in the marketplace.
Marketing AI content will be everywhere. Once you’re familiar with the basic AI keywords–machine learning, deep learning, image recognition, natural language processing, cognitive computing–you’ll start to notice articles, blog posts, podcasts, events and, in the near future, books all focused on the topic. I have an “artificial intelligence” keyword alert set up in BuzzSumo that produces 200+ new articles per day.
Case studies will emerge, and not just from big enterprises. Right now, the majority of case studies come from large businesses with massive budgets to custom-build AI solutions. As companies like Facebook, Google, Amazon, and IBM continue to open up their AI technology, more businesses will have the ability to get into the AI game.
Marketing automation and CRM platforms are racing to compete on AI. Salesforce struck first with the introduction of Einstein in September 2016, and now every major player must be focused on building machine-learning technology into their products in order to deliver intelligent personalization, predictions, and recommendations.
Ironically, marketing automation technology today is largely manual. Humans construct strategies, build personas, write and optimize content, define and manage email workflows, create digital ad copy, run A/B tests, predict outcomes and assess analytics. All of those activities can be more efficiently and effectively performed by machines.
However, marketers anxious to integrate AI into their marketing technology stack today would need to piece together more than a dozen AI-powered products, many of which are still raw in terms of development and proven success in the market.
It’s only a matter of time until the leading marketing automation and CRM platforms buy up the most promising marketing AI-powered products and bundle them into their solutions.
As of today, if you need to tell a data-driven story at scale, a machine can do it better and faster than humans using natural language generation (NLG) technology offered by companies such as Narrative Science and Automated Insights. This includes financial reports, earnings reports, sporting event recaps, and analytics assessments. But, as we touched on earlier, humans must still “train” the machines how to tell the stories. So, in the specific case of NLG, the creativity is still 100 percent driven by humans.
When you look at companies like Persado, you start to get into more advanced applications of AI that creep into the realm of replacing human creativity. Persado uses natural language processing (the same subset of AI that is prevalent in consumer technologies like Amazon’s Alexa and Apple’s Siri) and ML to generate words, phrases and images most likely to trigger an action.
In this case, there is little to no human involvement in the creative, and Persado claims that the content outperforms man-made message 100 percent of the time. Currently the technology can be used to generate landing page text, email subject lines and body copy, display ads, Facebook content, SMS, and mobile push notifications.
We’ve also recently seen examples of AI taking on more complex creative projects, including a movie trailer and music. But, for now, creativity is largely a human-powered endeavor that will be increasingly assisted by machines.
Check out the previous posts in the series: “5 Brands That Are Marketing Smarter with Machine Learning,” and “Marketers: You’ve Heard of Machine Learning, But What Is It?“
To read more interviews with leading digital marketing marketing professionals and storytellers, check out the Content Standard’s Innovator Series.