There are five levels of maturity for AI-driven content operations. Which level are you in? In this episode, Sarah O’Keefe and Bill Swallow walk through the AI content ops maturity model, from ad hoc experimentation to fully autonomous workflows.

Sarah O’Keefe: We want this automation, right? We want the ability to go in and extract release notes and do something with them. We have to have a certain level of maturity on the software development process so that we can grab the appropriate information. The same thing is true on the content side. You have to have a certain level of maturity in your content development processes, in your content management, so that you can identify the right things to process and the right things to access.

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Transcript:

Introduction with ambient background music

Christine Cuellar: From Scriptorium, this is Content Operations, a show that delivers industry-leading insights for global organizations.

Bill Swallow: In the end, you have a unified experience so that people aren’t relearning how to engage with your content in every context you produce it.

Sarah O’Keefe: Change is perceived as being risky; you have to convince me that making the change is less risky than not making the change.

Alan Pringle: And at some point, you are going to have tools, technology, and processes that no longer support your needs, so if you think about that ahead of time, you’re going to be much better off.

End of introduction

Bill Swallow: I am Bill Swallow.

Sarah O’Keefe: And I’m Sarah O’Keefe.

BS: And today we’re going to talk about AI in content operations, or more specifically, a maturity model for AI.

SO: Everything needs a maturity model, even AI.

BS: Even me.

SO: I have no comment.

BS: My maturity model is written in crayon, what can I say? So okay, so we need a maturity model for AI as far as content operations are concerned, and probably in you know, many different degrees, but we’ll focus on content operations. So what might that look like?

SO: I’ve been thinking about this and what it looks like to employ AI as a tool to help you with content. And as I was thinking about what this looks like, you know, you always fall back on that standard five-step model where one is basically mass chaos, and five is the perfect world, generally. also, one is nearly always cheap, and five is nearly always expensive enterprise things. But, you know, let’s go a little beyond mass chaos versus governed, regulated, etc., and sort of sort of back up a little bit and talk about what this might look like. So level one in every maturity model typically is ad hoc. And what that means is that in this case, AI is being used sporadically by some people. It’s inconsistent. And I would say that when we look at AI and content specifically,

BS: Mm-hmm.

SO: This is going to be things like reprocessing your content using public-facing models. So I wrote a draft of something, I shove it into ChatGPT and I ask it to shorten it or tighten it up or identify areas that are problematic. Or I just say, hey, you know, write my article for me. The outcome that you’re gonna get on an ad hoc model is going to depend on an ad hoc level one.

BS: Mm-hmm.

SO: AI thing is going to depend on how good you are on the individual’s expertise and their level of interest. So if you want to just go in there and say, hey, I have a bio and it’s too long, and I’ve been asked to produce one that’s only 50 words for a particular conference, for example, then, you know, this is this is actually a really good example of ad hoc, right?

BS: Mm-hmm.

SO: We have these long multi-paragraph bios and every conference I’ve been to has a different requirement for how that bio needs to be shaped. And the fastest way to success is to just shove it into a chatbot and say, give me a 50-word version. And and then read it and make sure it didn’t invent things or give you a PhD or anything like that, and then ship it off to the conference organizer. But this is much, much faster than rewriting it from scratch by hand. And also I think, it’s a good example of something where I have the extended version and I’m going to summarize down. And that usually works pretty well. So level one is ad hoc. It’s kind of sporadic. There’s no standard across the organization. It’s just me saying, this looks useful, or you’ve probably got some use cases in this space as well.

BS: Right. So it it kind of aligns with I guess level one of the the content maturity model that we talked about a while back, where level one is is simply content exists. Could be, you know, someone typing stuff up in Word or, you know, using a myriad of different tools, no style guide, just kind of getting content out there because people need it.

SO: Yep. So level two is tactical. And tactical is sort of like we’re using this tool to solve some specific problems. And what you’re going to see here is something like that Bill has invented some nifty time saving tool and he has shared it with other people. Or in a larger organization, maybe somebody invented a nifty validate or or something like that and they’ve rolled it out across maybe the department, probably not the entire organization. Aomething like AI support is being rolled out. Maybe the organization has created a chatbot internally for customers, right? So there’s a chatbot, it’s sitting on the company website, people can use it to get answers, but it’s really bad. And the reason it’s really bad is because nobody thought too carefully about the content going into the chatbot, because again, we’re tactical. So probably this looked like the AI team just raided the local SharePoint, grabbed a bunch of content, did not pay a whole lot of attention to the question of whether this content was up to date in release status. Those things don’t exist, right? It’s just, look, a bucket of PDFs. Cool. Let’s dump them into the AI and go for it.

BS: Mm-hmm.

SO: And tragically, in many cases, the techcomm team is sitting on rigorous, structured, vetted, approved content, and nobody remembered to go ask them, can we have your content? Or where is your official content source? Or how do I know what version belongs with which document?

BS: Right, because you know, in in their point of view there’s a PDF of it, so I don’t need to ask them.

SO: Yeah, it’s it’s just PDF. How hard could it be? So something like AI was support was rolled out, but nobody really thought about it. Maybe it’s at a departmental level, probably it’s not enterprise-wide. And nobody has really thought about connecting this AI thing to the assets inside the organization in a reasonable, rigorous, governed, organized kind of manner.

BS: And I suppose that’s where you get to the next tier.

SO: Right. So the next tier after tactical comes strategic, right? So we have an actual strategy. Now, one of the difficulties in talking about AI is that AI is a tool and it’s kind of like talking about electricity. You can apply it to lots of places and it’s more sensible in some places than others. But when we say what’s your AI strategy, like how do you use water? I mean, come on, and the answer is of course to drive the AI and you know destroy the environment. But there are things that you can do with AI that are useful for content. There are also things that you can do that are not. So if you have a strategic approach to this, a strategic approach to use of AI, backing up to the authors again rather than the delivery side, maybe this looks like a collection of prompts that have been built that are shared.

BS: Not with electricity.

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