What you’ll learn:
- What factors will drive the adoption of AI-powered content tools?
- How do you assess where you stand in this evolution?
- How to build an AI Content Maturity Model
Why use a Content AI maturity model? Because the use of artificial intelligence in content development and publication will become a matter of course for most large organizations, sooner than some might expect.
So it’s crucial to have an understanding of where you stand in that transformation. Because it’s a very real and very imminent one.
What will drive content AI platform adoption?
We recently had the opportunity to offer a presentation about that transformation at a ContentTECH Summit from the Content Marketing Institute, with the help of Venkat Nagaswamy, a leading expert in empowering B2B marketing by applying advanced AI and machine learning.
During the presentation, we dug into the reasons why companies need to understand the tools already on hand and likely to take hold in the future.
What are some of the factors driving AI content marketing platform adoption?
- The increasing demand for greater personalization of content across multiple platforms and channels allowed by the huge amount of available data about groups and individuals.
- The need for real-time retargeting and updating at scale that takes advantage of this data, a need that far exceeds the capability of human teams to meet it.
- The availability and economics of evolving technology tools: There comes a point where the ease of adoption and quality of output these tools provide justify the cost, a cost that’s invariably declining over time.
- Competitive pressure: Your competitors may be advancing in this space and realizing the gains to be had. In years past, many B2B companies learned hard lessons by ignoring the power of content marketing while their rivals embraced it, and learned from that mistake: They’ll try to stay out in front by leveraging the best new techniques and technologies.
How do you know where you stand in this evolution?
The simple fact is that the majority of companies that rely on content, and content providers and agencies, have no real handle on the possibilities of AI content development and publication platforms.
In fact, many content professionals recoil from the idea that AI will take a hand in developing and delivering content. To them, it’s a death knell for their own jobs.
As we say in our ebook on the subject, Convergence or Collision? AI and Content Marketing, there’s not as much to fear as they might think. In fact, there’s a huge potential upside for organizations that take the right steps forward in adopting these new tools.
Building a Content AI Maturity Model
As in nearly every other area of enterprise technology or process adoption, it’s extremely useful to understand where you currently stand in terms of transformation. Plus, it’s good to have some idea of where you can go from here as you ascend toward higher levels of expertise and functionality.
The digital transformation maturity model is one of the most familiar for a lot of companies, and we’ve applied a similar structure to the AI Content Maturity Model we’ve developed below.
What are the stages in this evolution toward AI Content Maturity?
- Unstarted: Exactly what it sounds like. An organization isn’t using AI-powered tools to analyze data, develop content targeting, or create content of any type, even for the most routine and rote purposes, such as product listings or financials.
- Content Measurement: At this level, an enterprise has instituted content metrics and analytics (e.g. reading level, sophistication, audience metrics, engagement metrics), and adopted tools such as Grammarly, Google Analytics, and other basic SaaS platforms. The benefits? Improved analytics that aid content efficacy and ROI.
- Content Tailoring: This is where an organization is creating and targeted content tailored to the desired audience. Among the tools they put to use? Triblio, 6sense, Persado, and others. The benefits they see? More relevant content is delivered relevantly, driving engagement at higher levels of efficiency; meanwhile, content teams are liberated from mundane tasks to deliver more high-value content.
- Content Automation: This is the on-the-horizon-but-not-quite-here level of Content AI. Here, an enterprise can automate content creation and delivery from start to finish of the process, including high-level content generation, precision analytics, and real-time customization. Most of the tools to do this are yet to be developed, but the benefits are potentially huge, with the highest possible level of engagement with your target at the highest efficiency and ROI.
Where do you and your organization stand in this AI Content Maturity Model? If you’ve got questions about how to measure where you’re at, or what strategy and plan you need to utilize to get to the next level and beyond, we’re here to help.