More than $30 billion goes into R&D of Artificial Intelligence in a year! Though AI in marketing is still an intangible concept for many, I think it’s safe to say we’re now looking at a proliferation of AI-based tools already. The potential of AI in marketing is still largely abstract, but that’s okay.
Let’s take a look at the AI opportunities and work through some steps you can take today to get in position for the AI proliferation if you haven’t already done so.
1. Prepare your data and the processes/practices around it
While AI is proving to be effective in creating new information, it’s equally effective at distorting data, which results in false information. Already folks are consuming more false information than true information. Fake news is now all-over that the likes of Facebook has had to take steps to combat it, and even other businesses are developing opportunities around the filtering out of false information.
Brands are going to have their work cut out for them. As brands increasingly function as publishers and curate content to share, fact-checking and data cleaning has become more important — and resource-consuming. AI has the potential to assist in the automation of these tasks, but hybrid marketers skilled in interpreting and cleaning your data will be key.
Whatever the specific marketing application, your AI tools will need clean, optimized inputs, as well as experts in place to make sense of the outputs.
2. Prepare your people
AI applications are only as good as the people who drive them. AI is a “positive net job motivator,” set to create 2.3 million jobs while doing away with only 1.8 million jobs. If this comes to fruition (and all indicators say it will), all of the anxiety over machines taking over will have been for naught.
Even so, the types of jobs that will be available — and the skills and competencies required to succeed in those positions — is changing rapidly. The demand for specialists will decrease. Brands will be looking for people able to perform across multiple disciplines — those who are able and willing to acquire working knowledge of many platforms and disciplines.
“Because the technology is so powerful, there’s a large demand for talent that understands how to apply it,”
– Scott Penberthy, Director of Applied AI for Google Cloud.
Major tech brands are investing heavily in new AI positions, so should you. Amazon is in for $228 million, Google has invested $130 million in new AI jobs, and Microsoft is in the mix with $75 million, according to research firm Paysa.
3. Tailor your content to capitalize on the voice search opportunity
This is not a trend, and it’s something you can implement now to make your future AI applications even more successful.
Between 20 and 25 percent of queries on the Google mobile app and Android devices are already voice searches. Voice-based search queries are the fastest-growing mobile search type, early adopter brands that redesign their websites to support visual and voice search will grow their digital commerce revenue by at-least 30 percent.
4. Boost your content performance with AI
How can you prepare your content for AI? Your language strategy goes beyond voice search; prepare for AI technology like chatbots as well. Natural language is becoming the standard as AI tools become smarter and learn to adapt to the natural speech patterns of each audience.
Marketers need to get infinitely intentional in planning, creating and promoting content. You’ll need to understand the entire customer journey, start to finish, and which content formats, platforms, channels and device targeting will get your content in front of the right customer at the right point, at just the right moment.
This is perhaps where AI will have the greatest utility in marketing — in learning user behaviors and needs at a level so granular that each consumer has a completely custom, personalized experience.
5. Examine your potential IoT and AI use cases
“Showing up in 2018 without an AI chip in your flagship device is going to get your product dismissed by the general public.” – Tristan Greene
Start with that assumption and begin projecting out from there. AI is using cases inside your business, and it is also going to be the new normal for the consumers you’re trying to reach. Begin documenting the problems you believe AI may be able to help you solve — both internally and for your consumers — and examine each use case.
Smart Insights provides some great examples of use cases in the visual below by breaking down AI into three components: Machine Learning Techniques, Applied Propensity Models and AI Applications.
AI is not going to be the answer to every challenge. Focus on your goals and utility, not just the cool factor of the technology.