The co-created
future of AI in creative
content strategy

A pragmatic vision for how artificial
intelligence will transform the content
creation process for businesses

The co-created future of AI in creative content strategy
Robert Rose
Robert Rose

Chief Strategy Officer
The Content Advisory, Inc

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Introduction: the truth is out there

“The truth is out there. But so are lies.”

– Agent Dana Scully, The X-Files

One of the most popular television shows of the 1990s was The X-Files. The heroes, Fox Mulder and Dana Scully, had paranormal, supernatural, or extraterrestrial experiences that no one could explain. Their job: search for the truth. In fact, the show’s tagline was “the truth is out there.”

At the heart of each week’s tension were the characters’ differing philosophies of science and technology. Scully’s view was that no matter how “unexplainable” any phenomenon was, it could not be beyond any already applied scientific theory. Mulder, on the other hand, was quick to believe phenomena without a plausible explanation and open to using any paranormal tool even if it wasn’t understood. Essentially, Mulder believed in magic and Scully thought it was all a trick.

This tension made for great television. It’s also similar to the tension that exists in today’s usage of artificial intelligence (AI) tools as a source for creating original marketing content.

On one side, you have purveyors and users of AI tools for content creation who say, “it’s magic.” Proponents claim that machines have reached a point where they can replicate human work in ways that we simply cannot comprehend. Detractors worry that artificial intelligence will soon replace humans as content creators.

On the other side, you have those who are more “team Scully.” They look at AI tools that create content as glorified echo chambers and claim that AI is no more than a sophisticated algorithm that simply rearranges the learning it has been fed as a clever parlor trick.

What is the real truth? Well, the truth is out there.

Creators and technology: it’s complicated

We have a long and complicated past when it comes to balancing technology against the human creative process. When the printing press was invented in the 1500s, the Dutch scholar and Humanist Erasmus complained:

Margaret Mann Phillips, Erasmus on His Times

“To what corner of the world do they not fly, these swarms of new books? … the very multitude of them is hurtful to scholarship, because it creates a glut, and even in good things satiety is most harmful. … I do not deny that the new-fangled writers may discover some things which escaped the old. But they fill the world with stupid, ignorant, slanderous, scandalous books, and the number of them is such that even the valuable publications lose their value.”

Erasmus: On His Times

Erasmus was horrified that technology was enabling any old hack writer to publish bad content, and he worried that access to valuable works would be lost in the chaos. Sound familiar?

The ongoing tension between human content creators and technology has continued to evolve rapidly with the advent of the word processor, digital photography, creative software editing suites, music editing software, and computer graphics. There is now a computer program that can simulate entire choirs, enabling anyone who can play basic piano and type words to create the music and lyrics for an entire choral symphony.

“No matter how varied the technologies have been…
the source of tension has
always been the same: fear.”

However, no matter how varied the technologies have been or which part of the creative process has been most affected, the source of this tension has always been the same:

  1. Fear (real or imagined) that humans with no experience or talent will suddenly be granted unearned abilities to create.
  2. Fear (real or imagined) that existing human artisans will be displaced.

Both have one thing in common: Fear.

However, these fears have proven to be mostly unfounded. In every successive digital innovation, the new technology has added new creative capabilities and activities while also either removing or making more efficient the existing ones. Digital photography removed the need for processing film in a dark room. But it also added the capability and need to use photo editing tools. Digital word processing and imaging software removed the need for manual typesetting. But it created the capability and activity of desktop layout for authors. Digital video editing sites removed the need for physically cutting and splicing film but added the capability and activity of making more sophisticated transitions.

So, while the fear of being replaced may not be completely unfounded, it will only be made real if the creators themselves don’t take advantage of evolving their process or using the new capabilities. Put simply: today’s content creator is no more or less talented or equipped to express ideas – it is the activities and efficiency of those activities that change.

Let’s look at how successful business content creators are leveraging AI.

1. The role of AI in business content creation

When I was young and just entering the technology industry in the 1990s, I heard one of the simplest yet most profound descriptions of what software does. A brilliant software engineer told me, “The only thing a computer does is read information and write information. That’s it. My job in code is to tell it what to do in between those two steps.”

Natural language processing (NLP) and natural language generation (NLG) are fields of study that have been around for more than five decades. (For this paper we’ll set aside, but acknowledge, natural language understanding (NLU).) NLP has been AI’s primary focus in business for many years. Put simply, NLP helps a computer create structure from unstructured communication. For example, we might create an NLP software application that “reads” emails and predicts the likelihood they are spam.

Natural language generation is part of natural language processing

NLG is the reverse of NLP. NLG is a software process that produces original natural language (i.e., human language) output based on input it’s given. A simple example of this is a “chat-bot.” If you pose questions, the AI can formulate natural language answers drawing upon a knowledge base that has been fed into it.

From a marketing and advertising perspective, NLP-related software has been integrated into digital content for at least a decade. It’s been useful in handling search engine display, advertising placement in programmatic campaigns, content personalization, and automated analysis to display “related” products or content to entice deeper engagement. However, in those examples AI’s role was to read, rearrange, and/or optimize content that humans had already created.

Only in the last few years have commercial NLG solutions begun to create original content. The reason that most marketers haven’t heard much about NLG until now is that the technology has only recently become good enough for the language to actually sound … well … natural. The result has been an explosion of new solutions offering AI content creation as a service.

Why so many AI tools now?

In 2020, OpenAI, a large, well-funded nonprofit research company, released a version of what it called GPT-3, a language model with the ability to produce written language on a massive scale. Its “secret sauce” is both the size and scope of the information it has to draw upon and the learning models that it developed. With more than eight years of crawling the entire Web, billions of books, and the entire contents of Wikipedia, the development of GPT-3 was a huge undertaking and a kickstart to the thousands of new companies that could access it.

OpenAI made the GPT-3 platform available for other technology companies in the language modeling business to enhance the technology they were working on. This is why we see so many new companies offering much improved AI-driven content creation solutions. They can build their differentiated solutions on top of a solid, starting infrastructure of AI learning that they never could have created themselves.

The advancements made in GPT-3, and other similar platforms, have spurred incredible innovation in the space, and the role of artificial intelligence as a content creation service is now ready for prime time.

“What AI can do is help you be more efficient.”

An extension of human talent, not a replacement

So, what is the role of AI within our content creation teams, and why does there seem to be more resistance to it than to other marketing technologies?

Perhaps the place for marketers to begin is understanding what AI for content creation is not. AI is not wise.

Wisdom is the very human quality of having the experience, knowledge, emotional intelligence, and good judgment to make decisions. AI cannot combine these things. Therefore, it cannot judge the wisdom of, or originate, your next differentiated white paper or eBook. It will not create the most original idea for how you should approach your new podcast. It will not write the next visionary business book.

What artificial intelligence can do is help you be more efficient and write the abstract for your next white paper or eBook. It can help you come up with a novel name or description for your new podcast. It can suggest edits and/or revisions to the various chapters in your new book.

In essence, we can think of it like this: AI is good at helping humans assemble original content, but it is not yet (or maybe ever) going to help you find the deeper emotional connection or concoct a great story.

However, as discussed earlier, if we better understand what parts of our content
creation process AI makes more efficient, we can also better understand
what new capabilities AI amplifies and where the technology can be
extraordinarily helpful.

“Ultimately AI’s role will be to support writers as an extension of talent.”

AI as a co-writer

For years, academics, fiction writers, and business authors have employed research assistants to help assemble written works. Their responsibilities include conducting initial research into a topic and, often, helping to summarize knowledge on a topic, write a first draft, or even summarize the written work for submission to journals or other platforms. In more exceptional cases, research assistants receive a co-writing credit if their contribution is a creative or substantial piece of the finished work.

This is where the role of artificial intelligence within the content creation process immediately starts to provide exceptional value. We are already seeing businesses create enormous benefit by adding AI as a co-writing assistant to their teams.

At TCA we have begun to see enterprise marketing teams integrate a role for artificial intelligence across three major areas of the content creation process:

Extending scale
AI can help automate some of the elements of content creation, editing, rewriting, and content organization necessary when creating a new work. For example, AI can create descriptions of webinars and provide multiple variations of headlines, product descriptions, or other original abstracts.

Increasing speed-to-market for content
AI can help organize thoughts and provide basic drafts or fuller outlines of entire sections of informational content. For example, AI can help put together help center articles, job descriptions, or meta descriptions of blog posts. This transforms writers into strategists and editors of more informational or process-focused content that would otherwise be created by a human writer first.

Creating better consistency across platforms
AI can help enable a team to always take on the role of creating a certain type of content, thus ensuring it is always created in a specific and consistent manner. This can eliminate the need for the “who’s available?” question and inevitable style inconsistencies when these select content pieces are needed.

Ultimately, AI’s role will be to support writers as an extension of talent. It will enable writers to spend more time on the formulation of strategic ideas and the deeper story they want to tell. In fact, AI will help to both uncover and fill gaps in writing talent across the teams. It will help writers who have wonderful ideas but are weaker on structure to create better abstracts or outlines of those ideas. It will help others who have a tough time putting the initial words together by suggesting how to assemble the first draft.

Ranjan Roy

Ranjan Roy
VP of Strategy
Adore Me

Adore Me

Adore Me adds AI as an extension
to their writing team

Adore Me is a startup fashion company offering hundreds of styles across lingerie, sleepwear, loungewear, swimwear, and more. The company has a small marketing team that needs to create a huge amount of content frequently. From product descriptions to ad copy to social media posts and website copy, new conten is constantly needed for repetitive platforms.

The Adore Me team implemented an artificial intelligence solution with the goal of extending the marketers’ ability to create multiple versions of content in a consistent way. Each platform (social, search, ecommerce) has particular needs, and by using AI, marketers can automate content creation across multiple platforms.

The initial resistance was what AI would mean for marketers’ jobs. But Adore Me discovered that the system can automate the creation of content that complies with their style and brand guide, and that it worked best when rewriting content from the original creator or creating new content based on a human’s original. So it became truly an extension of the team – and not a replacement for it.

As Ranjan Roy, Adore Me’s VP of Strategy, said about their artificial intelligence tool: “you have a sidekick, an assistant, that is there to help you in any kind of communication you can make.”

2. Emergent AI writing tool trends

AI writing tools for professional writers are a new catalyst for a digital content strategy. Because they are multifaceted and impact different parts of the content creation process, they will almost assuredly be integrated into every kind of technology where written content plays a role. This includes content management systems, digital asset management systems, blogging tools, and marketing automation, and just about every other enterprise content technology.

This means that teams will successfully interact with AI tools in many different ways across the content creation process. To help provide a pragmatic view on exactly where we see the writing process most impacted, we’ve developed the following framework to help teams understand where there may be a HIGH degree of interaction with AI tools that assist with content creation, and where there may be LOW degrees of interaction.

AI as a co-writer

1. Pre-writing – medium/low
Pre-writing is sometimes called “free writing.” This stage is often where writers will go off on tangents, where no idea is too “off topic.” This ideation stage is a place where AI won’t be a great help (as it shouldn’t). However, even here there are some applications for it. AI can act as a “sounding board” to provide for non-judgmental feedback.

2. Research – low
The research process is where we begin to assemble our arguments, our core story, and the details of our written piece. AI tools for content creation are not very good at fact-based research yet. You still need a human eye to understand reputable sources, separate fact from opinion, and understand some of the more complex relationships between what might have been true in the past but is no longer true today.

1. Pre-writing, 2. Research, 3. Drafting, 4. Revisions, 5. Editing, 6. Activation, 7. Publishing
AI as part of the writing process

3. Drafting – high
This may be one of the most important parts of the process where AI will earn its place as a valuable business asset. From a simple outline of the major points of a piece, to the title and one line about an event, AI can instantly create draft pieces.

For example, a writer might want to create a customer case study. The writer may simply identify/input the customer, the problem, the solution, and the benefits of that solution, and the AI engine can look to previous case studies and other company-specific learning and draft a complete case study. Additionally, with many of the AI tools, this draft can also reflect the company’s style, brand guidelines, and terminology, so it provides an immediate starting point for moving to the editing phase.

4. Revisions to content – high
In this phase, writers look at the cohesion and overall flow of the content to make sure it matches the original thesis, is structured properly, and tells the story the writer wants to tell. There is an opportunity here for AI to help “rewrite” elements of content to better comply with existing guidelines or to try different ways of rearranging the content for clarity. This will be especially helpful when processing content that originates outside the organization. The AI can act as an interim “editor” to get external content into shape before a human reviews it.

5. Editing content – medium to high
The second-to-final stage in business writing is a complete review for content grammar, spelling, punctuation, or other brand compliance standards that may be necessary as part of a final review. Applications for AI in content editing definitely exist, including replacing words or phrases, checking for compliance against custom brand standards, verifying terminology, or tackling other consistency challenges.

6. Activating content – high
Typically, once content is finished and being prepped for publication, “meta content” that describes the content needs to be created. This is another incredibly valuable spot for AI in the content creation process. AI can help generate meta descriptions of articles for SEO, multiple titles for articles that can be A/B tested, email subject lines, or abstracts of the article. One of the biggest challenges for brands today is that by the time content is ready to be published, it’s already woefully late to market. With the rush to publish, meaningful meta content falls by the wayside, and this is one of the biggest gaps in a content strategy. AI can help immediately meet this challenge.

7. Publishing – low
Publishing means moving the content to the audience, wherever that may be. Writers may realize many of the benefits of AI here such as multiple meta content items, dynamic headlines for A/B testing, and even multiple versions of the same article for different kinds of interfaces, but the role of content creation is low at this stage.

Conclusion: an evolved content creation process

Author’s Note: as you read this paper, you may have noted that there are a few segments of content highlighted in purple. I wanted to note the areas where an artificial intelligence served to help me create elements of this work. I would also note that AI generated the title of this paper (after some – well – collaboration). My addition was to add the word “co-created”.

In describing the inevitability of disruptive innovation, business professor and author Clayton Christensen said, “you may hate gravity, but gravity doesn’t care.”

The truth about artificial intelligence is that it’s here already. Arguing whether it will or won’t be utilized is a bit like politely asking digital photographers to put their SD cards down. AI is here. We already use AI to research things on Google, check our grammar, and search for just the right hero image for our blog. Now it will help us construct the written word.

The only remaining question is how to harness it as professionals.

Many purveyors of new technology are doing themselves no favors by positioning AI in content creation as taking the “drudgery” or “grunt work” out of the creation process, or by positioning it as “magical.” This is a critical point: Creators don’t view the activities or capabilities that are changing as drudgery, wasteful, or especially mysterious. Digital film editing didn’t take the artistry out of cutting and splicing film together. It added an extension for the content creator to do things they couldn’t do prior. Digital imaging software didn’t remove drudgery from opening and mixing paints together in a creative way. It added capacity to that process to give the artist an entire rainbow of color palettes to work from.

We are in the early days of artificial intelligence as an innovation in written content creation. It is beginning to open new doors and serve as a new extension for writers and other content creators, and it will transform the process of written content creation in business. But it will only threaten those who choose to see it as a replacement rather than an extension of their own creative capabilities.

AI will be a powerful new tool. But it is just that: a tool.

The Content Advisory, Inc.

About The Content Advisory, Inc.

Founded in 2010, TCA is the leading content strategy consulting, research, advisory and education company. Our clients rely on us for valuable insights on the topics of content strategy, content marketing, digital transformation, data privacy and customer experience. Since our launch, we’ve worked with more than 500 organizations, including 15 of the Fortune 100. We’ve consulted directly with organizations such as Adidas, Anthem Insurance, Capital One, NASA, Microsoft, LinkedIn, Facebook, CVS Health, 3M and The Bill & Melinda Gates Foundation.

TCA provides these business insights, advice and tools through our on-demand subscription platform, and customized, consulting and training assignments.

More information can be found at TCA’s website at

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