Colleen Jones: AI and The Content Advantage – Episode 39

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Now in its third edition, Colleen Jones’s book “The Content Advantage” has become a classic in the content-profession literature.

The new edition of the book continues to highlight content intelligence and content effectiveness and adds a new focus on the impact and use of AI in content programs. It also takes a fresh look at the enduring concepts of digital disruption and digital transformation, both of which have been accelerated by the arrival of new AI technology.

We talked about:

• her work at Content Science and how it informs the forthcoming third edition of her book, “The Content Advantage”
• her take on the concepts of “digital disruption” and digital transformation, both of which have been accelerated by the arrival of AI
• the title she’d give a movie about pace of organizational adoption of AI: “Slow and Slower”
• how elevating content concerns to the C-suite has garnered better results for companies lke the pharma giant Pfizer
• how AI can accelerate the implementation of content visions, strategies, and experiences
• how AI can improve content intelligence and aid in the assessment of content effectiveness
• how the structure, framework, and methodology for assessing content effectiveness remains the same in the age of AI
• her push to get organizations to use digital transformation as the lever to take an end-to-end view of their content
• how she consciously crafts the language she uses to talk about her consulting services – for example, using the term “end-to-end” instead of “omnichannel”
• a correlation that she’s identified between operational maturity and AI implementation
• how AI might improve the process of improving content performance
• her optimism about the prospects for content professionals in the new AI-dominated tech world

Colleen’s bio

A content expert and Star Wars fan, Colleen Jones is the founder of Content Science, an award-winning content firm where she has advised or trained hundreds of the world’s leading organizations to become content Jedis. She has worked with many of the Fortune 50, the largest U.S. web properties, the largest nonprofits, and several U.S. government agencies. She also served as the fractional head of content at Mailchimp during its high-growth period before its $12 billion acquisition by Intuit.

A member of Mensa, Colleen shares insights about content, AI, and business by writing for Entrepreneur, MediaPost, Forbes, and Content Science Review and by speaking at events around the world. She has earned recognition as a top content change agent by publications such as Technical Communication and a top voice for content strategy and artificial intelligence by LinkedIn. As a top instructor on LinkedIn Learning, Colleen’s courses have reached hundreds of thousands of professionals.

Connect with Colleen online

• LinkedIn

Resources mentioned in this interview

• Content Science
• The Content Advantage, third edition November 2024

Video

Here’s the video version of our conversation:

Podcast intro transcript

This is the Content and AI podcast, episode number 39. The arrival of generative AI has upended many corners of the content world. As a long-time content consultant and researcher, Colleen Jones is very aware of this phenomenon. But Colleen is equally aware of the enduring value of intelligent, effective content, and the fact that all content efforts must ultimately engage and motivate actual human beings. When applied thoughtfully and strategically at an organizational level, AI can help achieve all of these goals.

Interview transcript

Larry:
Hi, everyone. Welcome to episode number 39 of the Content + AI Podcast. I am really delighted today to welcome to the show Colleen Jones. Colleen is the president of Content Science, and also the author of the forthcoming book, The Content Advantage, in its third edition. It’s been out for quite a while and the new edition has a lot of new additions about AI. Welcome, Colleen. Tell the folks a little bit more about what you’re up to these days.

Colleen:
Thank you so much, Larry. It is great to be here, and fantastic to connect with you again. Content Science, we have been doing all kinds of interesting things in and around content. We do a lot of professional services as part of that. We do a lot of research and analysis, and we get the opportunity to do it for clients, but also independently, just delve into things that are of interest to us or that relate to trends that we’re seeing. We’ve been continuing that over the past several years, and I’m really excited with the third edition of the book to bring some of those updated insights, facts, stats, all that kind of good stuff into our current, very interesting situation with AI and content.

Larry:
Yeah, and I think that very interesting in air quotes is appropriate. And one of the things, I can’t remember, I read the second edition of your book maybe five years ago, so I can’t remember if digital disruption figured as prominently then, but that’s how you open the third edition of the book, is with this notion of digital disruption, which I think is really apt in the age of AI, but I think it’s also just in general, it’s related to digital transformation and a number of other phenomena that are going on. Can you talk a little bit just about what your concept of digital disruption, and how it applies especially to content practice?

Colleen:
Yeah, absolutely. You know what? I mentioned it in the second edition without really having any clue of just how much disruption would happen between the second edition and the third edition, so made it much more prominent in this third edition. And really, what that is about is the pace, the acceleration of change driven by technology. And right now, what’s really driving that is artificial intelligence. At a macro level, big picture view, when disruption happens, that really drives the need for change. Business models might need to change just the way a current business model is executed, might need to change all kinds of implications.

Colleen:
That really is what digital transformation is trying to address. And I know a lot of people see that as jargon, but in the business world it is taken kind of seriously, a lot of big budget around it. And with my book, The Content Advantage, I am really trying to tie in content to business decisions. I thought it was important to mention both digital disruption and digital transformation, and really kind of make the case for how important content is to both of those concepts.

Larry:
It just occurred to me literally, as we were talking that in both the case of digital transformation and the adoption of AI, you get the sense that there’s a lot of director and VP and management level people who are getting the charter from on high, “We have to do digital transformation, we got to do AI.” And I think that’s the level that most of us operate at. Is that a correct assumption on my part? Because you’re way more in the management consulting side of this than I am, I think.

Colleen:
Yeah, I think that there’s certainly that reactive stance of, “Hey, there’s a lot going on here. We really need to take this seriously. Do we really need to get into implementing AI and so on?” AI, in some ways is a shiny object. It is getting a whole lot of attention. There’s that kind of reactive stance, but then we’re also seeing a little bit more of a strategic approach. Something that I think is interesting is that individual adoption of AI, what we’ve seen over the past couple of years, especially generative AI, that can be fast. Someone creates their own account and they can start generating content, refining their prompts and so on. But organization-wide AI adoption, it has been slow and it’s getting slower. If I gave it a movie title, I think I’d call it, Slow and Slower.

Colleen:
And I think that’s a good thing because there’s a little bit of pause around all of the potential pitfalls that come with AI. I think there’s more realization of just how much impact generative AI can have, how much it affects an organization because content supports just about every business function. So it’s far reaching in terms of implications, and so it’s an opportunity to get more strategic. I think the slowness isn’t necessarily bad. It’s an opportunity for organizations who are really looking at potentially implementing AI at a larger scale to think about doing that strategically. And it’s a big opportunity for content leaders, professionals or allies of content leaders and professionals to be a big part of that conversation. That’s what I’d really love to see more of.

Larry:
Yeah, I’ve talked to a couple of people on the podcast too, especially in the content design world, in that product content world where they’re often like the perennial fight for the seat of the table on these product and teams. And when they demonstrate their AI chops, they often not only get a seat at the table, they have the C-suite calling them for advice about stuff. Are there any examples of that in your practice? I’m going to keep in mind throughout the conversation that you do all this kind of independent curiosity of your own research. Are you finding any places where content people have sort of an edge, like an edge in that AI gives them a competitive edge in terms of that seat at the table or influence in an organization?

Colleen:
Yeah, absolutely. We’ve worked with, over the past year, director-level content leaders and above who really are trying to update strategy and operations to factor in AI in the right way, which I think is super exciting and that’s the right way to do it, doing everything from a series of AI readiness workshops to really kind of dig into, where are the opportunities, what are the gaps we have to be able to make the most of those opportunities? That type of thing. And then in terms of examples that I personally haven’t been involved in, but I think are really interesting, one that really jumps out at me is Pfizer, which brought transformation led by content. That’s kind of their terminology, content is at the heart of this transformation.

Colleen:
Pfizer brought up to the CMO level and CIO level, improving the approach to go-to-market content, doing things like accelerate the creation by more than 50%, while also maintaining a high level of quality. I think that is remarkable given the size of an organization like that, how regulated an organization like that is. And I obviously don’t have any stake in that example. That’s why I’m mentioning it, is I think it’s really one for many other organizations to take note of. That’s the level of priority that an organization that’s really serious about AI and content is taking at the C-level. Absolutely.

Larry:
Yeah, and pharma is an interesting example because boy, accuracy and regulatory compliance and all that stuff are so huge in that field. And I know you didn’t work on it directly, but I’m wondering if you published that research in the book about content uses for AI and some of the use cases where AI makes the most sense. And you said at Pfizer they were increasing, sounded like accelerating the supply chain while maintaining high quality. I know you don’t have direct experience with that, but just generically, how can content operations do that? Because I think that sounds like the promise of AI, is you can do a lot of stuff quicker, but there’s been challenges with quality. And I guess do you have any thoughts about how to address that?

Colleen:
Yeah, definitely. Something I’m really excited about with AI is that it makes the implementation of the fantastic content visions and strategies and experiences that many of us have had more achievable to implement, if you’re thinking about it the right way. With areas of AI, we’ve seen certainly an increase in using AI to help with creating content or generating content. That’s where the progress really has been over the past a couple of years especially. But it also can help with things like operations, automating workflow, tying different types of workflow to different types of content or really weaving it into the content models that you have. And that obviously helps with things like ensuring quality or accuracy or the right people have reviewed. It also can help with automating checking for adherence to standards. That’s obviously been around for a while, but that’s getting better and better.

Colleen:
And that certainly can free up people from doing checks for, “Is this compliant with accessibility, or style, or search engine optimization requirements?” Whatever the case might be. But it also can help if you’re looking as an organization to leverage AI more to generate content, you can use other AI to check it and QA it. You need a bit of a tech stack with different types of AI to make the most of the operations. And then another big area where AI can really help is with content intelligence or measuring, assessing content effectiveness. And AI can help with automating reporting or getting to potential insights faster. I’m really excited about the potential for AI to make it easier for content leaders and teams to actually use data.

Colleen:
Even though in our research we found that measuring content effectiveness and impact is a huge success factor, it correlates really strongly with reporting success around content. Only about a third of organizations are doing it. It’s just hard to get the support for it, hard to really get that established. But with AI and more help, more sophistication and the tools making it more achievable, I’m really excited for more organizations to benefit from measuring the effectiveness and impact of their content.

Larry:
Yeah, because that content effectiveness, that’s one of those phrases that’s always in my head when I think about your operation. And have you changed the way you measure effectiveness, or do you feel like the workflow improvements, just you automatically get more… Tell me a little bit more about how AI is affecting ability to measure and report on the effectiveness of the content you do.

Colleen:
A couple of interesting aspects to it. In terms of the model of effectiveness, AI has not changed that, but the rise of AI has made what in the past we might’ve considered to be basic, to actually be more valuable and insightful than ever before. For example, one dimension of content effectiveness is accuracy, especially whether customers or users perceive the content as accurate. And with the rise of AI misinformation, disinformation, organizations just letting AI-generated content loose with all of the quirks and the tells that it came from AI happening, and people realizing that that’s happening really kind of complicates perceptions of content accuracy. It makes measuring that, tracking that in some way more valuable.

Colleen:
And another implication is that we think it’s more important than ever to measure content effectiveness, especially if you are looking to implement AI-generated content widely. Because no matter whether content comes from AI machine or people or a mix, what really matters is how that content has an impact ultimately on other humans. That really is where the content is successful or not.

Colleen:
And also, if you’re doing that, then you can compare, maybe you have certain types of content that you let AI be more involved in generating than you did in the past. And if you’re measuring that, compare, is this making much of a difference in terms of effectiveness with customers or users, or not? There’s that whole side of, does the model of effectiveness change? And I think not.

Colleen:
And then there’s the side of making it easier to track and measure effectiveness. In ContentWRX, we’ve been using natural language processing, one form of AI, for eight years now, I believe, to help with speeding up tracking themes or sentiment in open feedback people give about content, and always used algorithms to help speed up core analysis. What I’m really excited about is being able to add even more automation and doing a little bit more sophisticated algorithms. So I think there are lots of great benefits to speeding up and scaling the assessment of content effectiveness that come from AI being more achievable to implement.

Larry:
Yeah, as you talk about that, you’re reminding me, you talk in the book about systems and systems thinking and Donella Meadows and that stuff. And as you were talking, I was reminded of that diagram in the book about data collection analysis, interpretation, synthesis of some kind. And if I recall correctly, that was in your second edition too. It sounds like, has your basic methodology stayed the same, but you’re just some of the details are handled a little differently with AI tooling?

Colleen:
Yeah, I think for measuring content effectiveness, it’s the same structure, framework, methodology, and just more, I think to factor in the interpretation and what you do, how you act on the insights you get from content effectiveness. And then I think with systems, and we really think of content intelligence, which is a little bit broader than effectiveness, but effectiveness is a big part of it, thinking more about systems in the third edition, and with the rise of AI and digital disruption, and the reason that we’re thinking more about that is with digital disruption and the resulting digital transformation, most organizations realize that they need content to support lots and lots of business functions across entire customer experiences, across entire user experiences, audience experiences, whatever the case might be. It’s not just marketing content, it’s not just sales content, it’s not just technical documentation, it’s not just the microcopy within product interface, it’s all of it.

Colleen:
We’ve been really pushing a more end-to-end view of content, which is where a lot of those systems ideas in the book are coming from. And it’s been really fun and exciting and interesting to push organizations to get more aligned and integrated and use digital transformation as the lever to get more serious about it. I know it’s not necessarily a new idea that, hey, an organization should have the right hand knowing what the left hand is doing when it comes to content. I know silos, it’s not a new problem, but what I’m seeing is a new way to make progress on addressing that kind of problem, and also more serious consequences for letting silos continue and not having an end-to-end approach to content.

Larry:
I got to ask, I’m curious, this is industry insiders, which is what this podcast is all about, but that language of end-to-end, because some of the other ways of describing that kind of scenario, like omnichannel, or there’s people who talk about information layers and semantic layers to connect silos and stuff like that, but that notion, that end-to-end, I want to just help everybody market their content consultancies better, but I think there’s fear of words like ontology and omnichannel and other things like that, but end-to-end, that sounds slightly simpler. Was that part of the rationale for that labeling?

Colleen:
Yes. Yeah, absolutely. We do work a lot with leadership and they have responsibility over content at some level, but they’re not the content experts. I’m excited for the day where we have more content experts at leadership levels if they want to be. But the reality is that we work with a lot of different types of leaders who have some stake in content, responsibility for content. It’s been a lot of work to figure out how to talk about these things that we know are important and 100% agree, the value of content modeling, of getting serious about ontology and all the engineering aspects of content, how important that is to implementing end-to-end approach to content. But yeah, can’t necessarily lead with that. We have been seeing some good success with this. It’s also an idea that is used to some extent in information technology and some other product type solutions.

Colleen:
So it’s not necessarily an entirely foreign phrase to leaders, but obviously with any kind of phrase like that, what really makes the difference is if you give it meaning and you make it clear when you’re actually talking to someone about it. We use end-to-end as a great frame for, there are a few layers to what needs to be end-to-end. There’s the experience, thinking about that from beginning to end or for the full life cycle of the experience. There’s the content life cycle. That’s where we weave in a lot of the modeling, the engineering, the really tying that into operations and so on. And then intelligence, which we’ve already talked a bit about, but having a system of content intelligence that is working end-to-end as well, that really is key to getting mature in a content approach. And usually today, AI as well, that’s sort of going hand-in-hand, content maturity and AI maturity.

Larry:
That’s right. I was just going to ask about that because you’ve talked a long time about, and you have a well-developed maturity model. How does AI track to that? Generally, is it just sort of another criterion at each of those levels? I forget, you have chaotic piloting, scaling, sustaining, thriving, I think.

Colleen:
Yes.

Larry:
Does AI look different at each of those stages?

Colleen:
Yeah. We definitely see a correlation between, the organizations that report being more mature are more likely to report using AI. And it’s a correlation, so can’t necessarily conclude that AI makes an organization more mature from an operations perspective. But just coupling that with our experience, the more mature an organization is, especially from a content operations perspective, the better position they’re in to leverage AI and do so more efficiently and quickly because they’ve already figured out their vision, their strategy, what it is they want to accomplish, They’ve likely got standards in place, some level of modeling in place and all of that that everyone should have been doing all along, is a really critical to setting up, training, implementing, governing AI. So yeah, we are definitely seeing a connection there.

Larry:
Interesting. And that just makes perfect sense, that they would track to one another. Also, you mentioned the fact that you call your work intelligence. It just occurred to me, are you worried about artificial intelligence taking over? You’ve mentioned humans a number of times, the importance, this is all for humans and there’s humans at every step in this end-to-end systems of yours. But I guess, is there any part of your intelligent content scheme that might be amenable or adaptable to AI?

Colleen:
Yeah, I think in terms of assessing, measuring content impact, and coupling that with other data and insight to make decisions about content without as much human intervention, I think that’s very achievable, doable. I could definitely see that happening. For example, with optimizing content, being able to assess to variations of a content asset and leveraging AI to assess which one is the winner, which one is more impactful? And maybe come up with an idea for optimizing it further and improving performance further, and testing that whole optimization direction. I think AI can and will be doing more and more of, without necessarily needing as much input from a human, more just some supervision, as opposed to a team of people coming up with what that next asset to test might be or what every single variation might be. That’s just one example.

Larry:
Yeah, it kind of rings to other things that people have said about, that’s the exact kind of thing when you need to test a bunch of variants of something, it’s like, “Hey, ChatGPT, make me 10 of these.” It’s like-

Colleen:
Yeah, exactly. For sure.

Larry:
Hey, Colleen, I can’t believe it, we’re coming up on time already, but before we wrap up, is there anything last, anything you’d like to revisit from the conversation, or just make sure we share before we wrap up?

Colleen:
I really appreciate the opportunity to chat with you here. And I think I’d just like to reiterate what an exciting opportunity content leaders and professionals have right now. I know in some ways, it’s been a nutty year or a couple of years with AI coming on the scene so quickly for so many non-content people, and just a lot going on in the market and a lot going on in politics. It’s just been all kinds of change and a lot to deal with. But at the end of the day, I think anyone with fantastic modern content skills, strategy, engineering, analysis, content design is in a really great position to add a tremendous amount of value to the AI and content world. And organizations might not have fully realized it yet, but I’m optimistic that they’ll catch up. And one goal that I have for this book is to help raise awareness of just how important these roles and these people and the content-related profession in general is to being successful with AI.

Larry:
Great. Well, I hope we can drop a copy of your book on the desk of each executive right next to that big pile of PR stuff from the AI companies. But one very last thing, Colleen, if folks want to connect with you online, what’s the best place to follow you or connect?

Colleen:
Yeah, absolutely. One place is the Content Science website, content-science.com. We’ve got a monthly newsletter, a big button about how to sign up for that. And I contribute personally to that every month. And then also LinkedIn, my tag, I guess on LinkedIn is leenjones, L-E-E-N-J-O-N-E-S.

Larry:
Great. I’ll put that in the show notes as well. Well, thank you so much, Colleen. It’s really good to catch up again.

Colleen:
Thanks so much, Larry. A pleasure, and really enjoying your podcasts. Keep it up, they’re fantastic.