By Joe Stanhope, VP and principal analyst at Forrester
As a longstanding staple of science fiction and academic research, AI isn’t new. What’s different today is its shift into practical, consumer-facing applications. AI does real things for real people. For example, it quietly makes many of our daily tasks possible, such as shopping on Amazon, listening to music on Spotify, and requesting driving directions from an iPhone. AI is big business, and tech firms, enterprises, investors, and the media all want in on the action.
It’s no surprise that the excitement of AI has leapt into marketing technology – it’s an ideal environment for AI to strut its stuff. After all, marketers utilize massive technology stacks to leverage prodigious amounts of data to guide billions of decisions that drive trillions of dollars in consumer spending. And the timing is perfect because the demands of modern marketing have exceeded human cognitive capacity. That isn’t a slight on marketers’ skills, motivation, or smarts in any way. The truth is that it’s impossible for traditional marketing technologies, processes, and organizations to keep pace with the volume, velocity, and complexity of cross channel, personalized customer engagement in 2017.
Marketers are bombarded daily with bold statements that AI will make them faster, smarter, better, and more attractive. While it is highly likely that AI is leading us to autonomous marketing, marketers are neither prepared or willing to turn customer engagement over to HAL 9000 or any other AI system.
We’re in the very early stages of transforming marketing with AI. Marketers need time to develop trust in the technology and validate the long-term results. And AI represents a very different operating model for marketers that will require revised processes, skills, and organizational design. This takes time.
AI adoption is a process that will play out in phases over the next five or more years, as the technology improves and gains credibility with marketers:
- Phase 1 – Find patterns using more data, more quickly
- Phase 2 – Make suggestions that marketers review and choose to act on
- Phase 3 – Make and execute decisions within guardrails and thresholds
- Phase 4 – Fully autonomous marketing across the marketing mix with control of spending
Given this trajectory, the questions become: What is possible today? How can marketers safely adopt AI? How can they hold the technology accountable?
I did some research on how to assess the real potential of AI in martech, I discovered that:
- AI-powered marketing tech is initially an efficiency play. AI offers many benefits in the long term, but initially it will improve firms’ capacity to handle resource intensive tasks such as data integration, segment and rule creation, and experiment design.
- AI-powered marketing tech is turnkey. To encourage adoption and ensure seamless execution, AI must be productized within marketing technology systems rather than forcing marketers to develop or integrate AI into existing solutions on their own.
- AI-powered marketing tech adoption starts with basic applications. AI’s initial foray into marketing focuses on enhancing mainstay use cases such as buying ads, personalization, surfacing insights, and optimizing message send times.
- AI-powered marketing tech doesn’t have to be a black box. AI is incredibly complex, but marketers can still demystify the technology and define their requirements if they ask the right questions.
AI isn’t simply another buzzword; it absolutely has a place in marketing technology and will yield substantial benefits. We’ve arrived at the inflection point where legitimate AI-powered marketing solutions align with marketers’ readiness. To prepare for the future of marketing, brands need to advance their understanding of AI and start testing solutions today.
To learn more about the research mentioned above, and how you can incorporate AI into your marketing strategy, check out Joe’s recent report, titled “AI Must Learn The Basics Before It Can Transform Marketing.