The rise of generative artificial intelligence presents a dichotomy for brand publishers. On one hand, AI threatens the very foundations of modern online publishing as it trains itself on publicly available content, and AI-driven experiences are baked into search results and other major technology platforms.
On the other hand, it promises to add significant efficiency to the content production process – helping with everything from ideation to editing and content distribution. In this Snapshot, we’ll look at how marketers are currently using AI to their advantage, unpack some of the top challenges and obstacles, and explore where brands hope AI-driven content is headed next.
We examine:
- Why brand publishers say the adoption of AI for brand content has been slower than they expected.
- How brand publishers are integrating generative AI into their workflows and processes.
- Why quality, legal, and security concerns persist.
The experimentation phase
Observers say that despite the hype around AI for marketers, its use remains “stuck” in an experimentation phase currently, and that progress has been much slower than they expected just a few months ago. Noah Brier, who runs an AI Marketing conference and advises brands on generative AI, said that he’s been surprised at how slow progress has been. “Most brands seemed to be stuck in talking mode instead of doing mode,” he said.
This is largely down to legal considerations. Although rules and best practices are beginning to emerge around the use of AI for content, the landscape remains murky – prompting marketers to tread carefully. There’s also a question of experience: For marketers to trust generative AI and use it consistently they will need to develop a “finger feel” for the technology.
Despite the slow progress, marketers remain bullish on the use of AI in their daily operations, however.
Content teams within brands appear to be more open-minded about AI and its prospects than “traditional” journalism organizations are. A survey of top brand publishers by the Association of National Advertisers found that in 2024, content marketers and brand publishers expect to rely “heavily” on AI for story ideation, headline optimization, artwork creation, and content and script development over the year – indicating that progress may speed up.
“The closer the generative AI use case is to the brand’s core business, the more cautious the brand will be in using it. For instance, traditional publishers tend to be among the most reluctant to create content with AI because they have high standards for what they produce. But an automotive company looking to create guides for driving in different road conditions is likely to embrace AI writing tools more enthusiastically, precisely because it’s so ancillary to their business,” said David Berkowitz, founder of AI Marketers Guild, a trade group and consultancy.
Meanwhile, platforms are increasingly signaling to marketers that using AI for content creation may not hurt them. Documentation accompanying a new Google search update said its algorithms will no longer attempt to rank content based on who or what it was created by, as long as the content itself is deemed helpful and high-quality. For brand publishers experimenting with AI content generation tools, that could be music to their ears – and an invitation to experiment more. For many, the Google update has meant that one big hurdle to using AI for certain parts of content creation – that it would be dinged in search results – has effectively gone away.
While excitement around AI and AI technology in general is of course a driving force, content marketers are also contending with heightened scrutiny of their operations. As we reported earlier this month, content professionals say they’re increasingly trying to figure out how to get credit for the work they do and link it more directly to their companies’ bottom lines, while becoming more cost-efficient at the same time. Enter a new generation of AI-driven tools and technologies pitched specifically at marketers, which promise to both help them add efficiency and save costs.
“There’s the promise that brands will be able to create effective content with fewer resources especially as some of the leaders among AI tech companies continue to rapidly improve,” said Berkowitz.
Why brand publishers need to focus on short-term opportunities with AI
By Greg Friend, VP Data & Analytics, Nativo
It’s clear artificial intelligence will play an increasingly important role in content production in the years ahead, but most marketers still have little idea how to use it effectively. Half of marketers still aren’t using generative AI at all, and 39% say they have no idea how to use it safely, according to recent research conducted by Salesforce.
What gives? There are two key issues at play:
- There’s an assumption that AI has to be an all-or-nothing replacement for the entire content creation process.
- It remains unclear how consumers and audiences will feel about – and respond to – AI-generated content.
While it’s tempting to imagine a world in which generative AI will produce content at unprecedented scale and speed, preoccupation with hypothetical scenarios and futuristic possibilities risks overlooking the short-term opportunities marketers have in front of them. There are several practical ways marketers can use AI to improve content production today without ceding the entire process. Here at Nativo, for example, we’ve used generative AI to:
- Brainstorm with chatbots when colleagues are unavailable.
- Create rough drafts to help with writer’s block.
- Put together headline, phrase, and paragraph rewrites of human-created rough drafts.
- Help adjust tones and voices to better match client briefs.
- Conduct research and analyze data.
This list is far from comprehensive, but we’re on the right track in terms of finding the immediate value AI can deliver to marketers and understanding how it can help reduce busy work and free up time.
Consumers appear to be on board. Nativo recently conducted a survey pitting human-generated and AI-generated content head-to-head. Seven hundred consumers in the U.S. were presented with an article at random, asked to rate its quality and reliability, and then asked to guess whether it was human or AI-written. The results:
- Consumers are bad at guessing whether content is produced by humans or AI. Over half (53%) were wrong when asked if they were served content written by a human or AI
- AI-generated content performs on par with human content across key characteristics. It is seen as equally attention-grabbing, engaging, and authentic as human-created content, and even outperformed human content when it comes to personability and relatableness.
- Only a third of consumers said they find generative AI intimidating or confusing.
So what does all of these mean for marketers? Well, hate it or love it, AI isn’t going anywhere anytime soon. Rather than sit on the sidelines or adopt a wait-and-see approach, it would behoove marketers to take an active role and leveraging AI to make their content better, easier to produce, and more impactful.
The good news is Nativo is here to help. We’d love to chat more about the right role for AI to play in your content strategy, whether you’re just starting out or consider yourselves on the cutting edge already.
How brand publishers are leveraging AI today
Across companies, content teams are experimenting to figure out how they may be able to incorporate artificial intelligence into their processes and steer clear of potential legal or security concerns.
Taking on jobs people “hate to do”
The resounding message from content marketers and brand marketing executives is that no modern brand can afford to use AI to create content in its entirety. In its raw state, it’s likely to be riddled with errors, factually inaccurate – and crucially, feel unoriginal. Instead, say marketers, the goal is to use AI to do tasks that humans’ time is wasted on.
“There’s so much focus on creative output writing AI etc. but the place to look at is the jobs you have to do where people hate to do. As a rule: don’t have this write your content,” said Brier.
For example, at Surescripts, a health information company, the content team has been experimenting with various uses for AI. The team has found some success in using AI tools to help with basic cropping and resizing of images for their brand content, said Kelly Jeffers, VP of content and brand marketing.
Jeffers said the company also has a plethora of content that used to have to be tagged manually with keywords. It has since moved to using generative AI tools to do that, to be able to search content internally for backlinking and research purposes.
“What we say to our team is this is actually going to make what you do more important,” said Jeffers, who added that in experimentation, the team hasn’t found tools that replaced functionality or resources, but has focused on how tools can enhance productivity.
Brier said that among brands he’s advised, similar types of “jobs people hate” include adding metadata for accessibility purposes and normalizing reporting data to find patterns.
Adding efficiency
Content teams inside brands are under tremendous pressure right now to prove their worth. The economic climate of the past two years made it clear that to stave off cuts and ensure their survival, content and brand publishing executives would need to connect their work to the bottom line and find efficiencies where possible.
AI can help. One of the most common uses of generative AI for publishing teams has been to supercharge processes. While many are not ready or willing to completely turn over their content ideation process to AI, many are open to using generative AI to get them started. Some call this “force multiplication”: using AI as a way to get the creative juices flowing, get a long list of ideas for stories, headlines or angles, or simply to move past the empty whiteboard problem.
At Alloy, which itself uses AI to help retailers manage inventories, content teams are using generative AI tools to create what head of marketing Franklin Morris calls “derivative content,” such as metadata and copy for newsletters and social media. “That used to be done by a 25-year-old out of school, now we have AI doing a lot of it,” he said.
AI is now being used by content teams to create explainer and service content as well as e-commerce copy and product descriptions. “AI is also great at headline writing and as a thought starter for product names, taglines, mission statements, and other brand voice documents,” said Chandra Turner, founder of recruiting firm The Talent Fairy, who has seen first-hand how the job market has changed in response to the advent of AI. “The editors and marketers who know how to use it well will save time and money for their brands and their clients.”
Surescripts uses an AI tool to record episodes and scrub the audio files of background noise, for a podcast, saving it money on production costs. And at ZoomInfo, the content team is experimenting with using AI to free time for the content execs to focus on more creative tasks. “It’s turning us into superheroes, making us smarter and more efficient,” Meghan Barr, who runs brand and content at ZoomInfo, wrote.
Content optimization
Search engine optimization is increasingly a popular way to integrate AI into publishing and content operations. At Surescripts, the team has been using AI tools for keyword research to help with search engine optimization. The key, according to Jeffers, is to have extensive and in-depth user personas so that the AI tool can come back with very specific content. “Without them, we’d get fairly generic content back,” she said.
Keyword identification is a top and common use case for many brand content marketers. A study by Beantown Media Ventures in 2023 found that keywords are the No. 1 way content teams are using generative AI.
Other common ways brand content leaders said they’re using AI for SEO is to help with site-wide optimizations to help content rank higher on search results pages, keyword A/B testing, and real-time reporting and results for rankings.
Relatedly, AI tools are also being tested for tone and voice to maximize optimization. AI tools can be used to audit existing content and “fed” brand guidelines, so they can come back with suggestions for improvement. Brier said that he’s also advised brands on using AI to test various content voice and tone variations to see which results in more engagement or conversions, for example.
Challenges and considerations
The adoption of AI-powered content tools has been slower than some predicted in part because of outstanding questions and concerns around quality, legality, and security.
Rules are emerging around AI use in some corners: The White House announced its attempt to govern the fast-moving world of AI – including, chiefly, plans for guidance for watermarking AI-generated content. Several bills are in play in Washington that will decide how and when AI-generated content will be regulated. However, marketers say that this will be the year when marketers will finally wrap their arms around how exactly AI will play a role in their content operations.
“In 2023 there has been a lot of hesitation about usage, quality, and legality, but I think 2024 will see brands taking a stand on how they want to use AI for publishing, and why. And I hope we see brands be upfront and honest about which of their content is AI-generated — even if published with a human hand — said Natalie Mendes, who runs content for Atlassian.
Quality & security concerns
Quality has become a watchword for anyone creating content on the Internet. Algorithms now reward quality as a key metric, consumers look for and trust information that is suited to their needs and desires, and amid a plethora of forgettable content, well-written, factual, accurate and entertaining brand content is likeliest to succeed.
Brand publishers who are trying to figure out if and how to use generative AI for content production and ideation are rightly concerned that while it may make life easier for them, it may also result in low-quality content. “Our concern is the potential rise of “forgettable” branded content, meaning that it neither challenges nor adds value to the existing discourse. We believe content creators must tread carefully with AI and double down on improving the quality and efficacy of their work,” said Ken Beaulieu, ANA Executive Vice President, Content, and Center for Brand Purpose.
Issues of bias and discrimination are rife. Brand publishers are also worried about safety and ethics issues as they seek to navigate this new era. “The big challenge, of course, is using AI safely and ethically and ensuring the content fits the brand,” said Beaulieu.
Accuracy is also a concern: While always improving, generative AI models run the risk of inaccurate information being presented. Usually, this is due to limited training data or algorithm issues. These “hallucinations” can be a problem. AI also struggles with certain tonal patterns like sarcasm or irony, and generative AI tools may have a hard time detecting content inaccuracies.
Legal questions mount
Some posit that the reason generative AI has been slightly slower to hit mainstream use among brands has been security concerns when it comes to data. Legal teams are conservative, and big brands are particularly rise-averse. Brier said that brands are especially careful to vet AI tools to prevent data breaches or model poisoning – which can slow progress.
Brands are considering how to move forward with generative AI but ensure their exposure remains limited. There are sensitivities on how data – particularly consumer data – is being used, and brands are rightly extra careful and want to avoid extensive delays. “Do you really want to get every last document approved?” is a common refrain.
The issues of originality and copyright cannot be overstated. AI content cannot be copyrighted unless a human author is involved. Brands using AI tools to generate content or aid in content production may themselves be in breach of copyright laws. At question is generative AI’s tendency to be trained on available information – which means that those using certain tools may be reproducing other people’s work (and passing it off as their own.)
A related issue is disclosure. If brand publishers are using generative AI tools to create content, they will eventually need to decide if – and to what extent – they will disclose how that content was produced.
What’s next
AI is improving faster than perhaps any other technology before it. Generative AI is now an inevitable part of modern content creation. What comes next is the AI as copilot era: Brand publishers and content marketers now plan to use AI as a helping hand to free them up for more creative tasks. But before they do so, they will look for reassurance from AI tools on issues like security, quality, and accuracy.
In the coming years, this may change rapidly. Brand marketers expect soon that humans will be the copilots, with AI taking over the majority of content creation tasks, depending on human input to solve problems, ahead of a perhaps not-too-distant future where AI will go on autopilot.