Paul Roetzer couldnt stop watching. It was 2011 and Watson, a then-new IBM supercomputer, faced off against 74-time Jeopardy! champion Ken Jennings and the shows all-time money leader, Brad Rutter. , a question-answering artificial intelligence system, would buzz in within a second of host Alex Trebek asking a question, giving what the AI determined to be the most probable answer. By the end of the game, Watson had dominated the shows all-time greats by more than $50,000.
By late 2016, Roetzer had become so obsessed by AIs potential in marketing that he founded the , a group with the mission of making AI approachable and actionable for modern marketers. Roetzer still runs his company, PR 20/20, but he says that his AI group now takes nearly all his time. He badly wants to figure out how organizations can pilot and scale AI tools to increase efficiency and reduce costs.
So far, he has nearly the entire marketing industry to work with.
The vast majority of the industry is at what I consider the pilot phase, he says. Most are trying to understand what AI is, then how to apply it.
A 2018 report by Boston Consulting Group and MIT Sloan Management Reviewtitled finds that only 18% of companies are pioneers, or organizations that understand and have adopted AI. A third of companies (33%) are investigators that are in the pilot stage and know a bit about AI, while 16% are experimenters that are piloting AI without fully understanding itthey hope to learn about AI as they use it. The rest (34%) are passives, or organizations that havent adopted and barely understand AI.
Over the past few years, many marketers have marveled at AI and wondered the same thing Roetzer did after watching Watson dominate its fleshy opponents: How does that work? As 2019 begins, marketers can move beyond passivity and into being AI pioneers.
Learn Now
Like Roetzer, Robert Redmond watched Jeopardy! in awe as Watson dominated the shows legends. Redmond, a self-described sci-fi geek, had been hearing about AI since he was a young boy, but the AIs game-show performance was a glimpse at the technologys capabilities.
At the time, Redmond was working as a creative director of teamDigital Productions; by 2016, he worked at IBM with Watson Advertising as creative and strategy director. Redmond is tasked with figuring out how Watson can help brands have unique, AI-driven chats with their customers.
When Redmond first learned that hed be working with Watson, he says that he knew close to nothing about how AI worked, especially from an engineering perspective. Redmond calls the six months leading up to working with Watson his baptism into AIhe was already an AI convert, he says, but he still had to fight to understand what was possible with the technology.
I read a lot and I asked more questions than most would probably be comfortable answering, he says. There was a lot of Can we do that? And the learning came by understanding the implications on the back side of those questions.
Marketersmost of whom likely dont fully understand AI, let alone its true potential in businessshould also be asking a lot of questions. Redmond believes that businesses should learn by digging into possibilities and seeing what AI tools are available on the market. Both he and Roetzer have encountered some companies that use AI-based software without realizing itthis is likely the case for many companies searching for their first piece of AI-based software.
For marketers eager to learn about AI, Roetzer suggests reading by Paul Daugherty and H. James Wilson and by Ajay Agrawal, Joshua Gans and Avi Goldfarb. Most of the really valuable AI education has nothing to do with marketing or sales, Roetzer says. Even so, books like these can give marketers a window into AI and its business potential.
Marketers should learn how their competition is using AI. They should also ask vendors pointed questions about the AI software theyre selling. A lot of tech vendors are slapping machine learning and AI on their branding, Roetzer says. A lot of times, they dont even know what that means. The sales and marketing teams cant explain how their products use AI. Theyre just told by the engineers that its AI.
Marketers can also play with online AI demos to get an idea of how AI-driven tools work. , Roetzer says, as does IBMs Watson. One Watson toolallows users to log into their Twitter account and receive a personality analysis based on their tweets.
There are a lot of resources out there, and you can connect the dots pretty quickly if you just consume the right resources and understand the ways you might be able to apply it in your business, Roetzer says.
Find Easy Wins and Tough Problems
Companies without AI experience will likely have a steep learning curve, Redmond says. Theres definitively going to be a training period, a modeling period, and probably a fail period if youre stepping into a scenario where you are really starting from scratch, he says. Its a difficult transition.
Redmond and Roetzer both say that this difficult transition will make early, easy wins essential. One potential easy win, Redmond says, is using AI-based programmatic advertising tools to bid on media buys. Another he suggests is natural-language processing tools that can quickly judge the tone and intent of business communications, such as emails, memos or marketing materials. You can discover new ways or new features that might be important that you didnt realize or pressure points that may be bigger than youve been admitting, he says. You uncover the insights, and you can act upon them.
The simplest way to find easy wins, Roetzer says, is to make a list of all the tasks in the businessfrom quick to time-consumingand measure how much time employees spend on each task, as well as how much money the company spends on software or outside services for each. Then, marketers can rate each task from one to five based on how much value AI could bring. A one would mean little to no value, a five would mean a good AI solution would be transformative. Listing, measuring and rating may sound arduous, but Roetzer says that the process will give marketers an idea of AIs potential value in cutting down time and costs.
If youre the director of marketing, and youre trying to get buy-in to try this, you can go and say, Hey, I went through an analysis. Herere the five use cases where I think we create the most value, Roetzer says.
The C-Suite Must Buy in, Time Must Be Given
Redmond normally works with companies that have a mandate from the top to adopt AI, now. The chief technology and chief information officers with whom he tends to work are focused on a problem at a high level and want to solve it with AI; that desire spreads through the rest of the organization.
But not every marketing manager will be so lucky. Roetzer says that even marketers who get the C-suite to buy into AI software often have executives quit on their AI project before it can prove its efficacy. AI systems, especially at small or midsize companies, sharpen over time and often need months to learnits hard work to get AI right, it likely wont work right away and it may even fail during the first pilot. If a CMO adopts an AI-powered media-buying tool, for example, and it doesnt show lift three months and $20,000 into adoption, many executives will scrap the idea of AI altogether, convinced it doesnt work.
Its a hard thing to explain to the C-suite if theyre not the ones driving it, Roetzer says. Even at the pilot stage, there needs to be buy-in at the top level. [They need to know] that this is going to be an ongoing experiment, and its going to transform everything we do. But we have to have the right investment and the right patience to see it through.
Organizations must understand from the start that AI is not a magic switch, Roetzer says. Companies cant just expect to adopt AI andpoof!solve all their problems. Adopting AI is a lot of work and requires a lot of data to train its models; it takes a lot of strategy to prioritize what cases are helped by AI and what cases should be left for another day. Some people may give up too easily, he says.
Although Roetzer knows that it may sound as though hes trying to scare people away or downplay AIs potential, he believes that marketers who properly adopt AI will be given superpowers. Its going to fundamentally change the way we do marketing, he says.
Hal Conick is a freelance writer for the 蹤獲扦夥厙s magazines and e-newsletters. He can be reached at halconick@gmail.com or on Twitter at @HalConick.