If there’s one phrase that nearly every marketer has heard, it’s ‘do more with less’.
The release of ChatGPT and the many, many AI-powered writing tools that followed, it actually seemed possible to abide by that adage.
As the best marketing teams know, good content is expensive and time consuming.
This is likely why immediately following the launch of ChatGPT release, marketers leapt at the ability to create content using these tools. With AI at their fingertips, even the leanest marketing team could create content at scale in a fraction of the time.
Nearly two years later we’re seeing a different, albeit clearer picture of the reality. Yes, generative AI is a powerful tool. Yes, brands and marketers should use it to create content. However, it has to be used carefully.
In this post, we’re going to dig into the era of AI-generated content saturation, its negative effects on buyers, and how brands can still harness the power of AI tools at their disposal to create content their buyers actually want.
The AI-generated content boom and bust
The November 2022 release of ChatGPT was the start of a content creation frenzy across the B2B landscape.
According to data from PathFactory’s 2024 Benchmark Report on content consumption, brand’s content libraries saw a surge in blog posts in particular. This format represented a much bigger part of overall content libraries, representing 15% of brands overall content ecosystem.
Over time, the cracks in this approach began to show.
Content volume may have increased but with even at a glance at some content out there, depth and originality have clearly suffered. Since the large language models (LLMs) that power ChatGPT and similar platforms are analyzing huge volumes of text in aggregate, any output is going to trend toward the middle.
Buyers have picked up on this and become more adept at recognizing AI-generated content, leading to decreased trust in surface-level information and eventually, decreased engagement. To put it simply, blogs have fallen out of favor. Our data shows that blogs fell out of the top 10 content formats in 2023, and time spent with them dropped to 2 minutes and 37 seconds in 2023 (down from over 3 minutes in 2021).
Now what? Rethinking AI’s Role in Content Strategy
These shifts signal a clear message: B2B buyers are looking for value, not volume. Brands, in turn, must reevaluate their approach to not just how they create content but their overall content strategy.
This includes considering AI as an enhancer, not a replacer. AI tools should be just that: tools that augment human creativity, not substitute it—and like any tool, ensure you understand how to use it to its fullest capabilities. Instead of using AI to generate a piece of content wholesale, lean on it for crafting in-depth creative briefs for your writers or topic generation.
Moreover, think about AI like you would an intern. Trust it to act on clear, explicit instructions and then count on rigorous quality control processes to ensure it meets your standards for depth and originality.
As for which types of content your team should be creating, our data showed a couple of trends worth paying attention to.
Despite the drop in blog consumption, ebooks and similar long-form assets accounted for 25% of all content traffic in 2023 which shows that buyers still value in-depth content. It’s just a matter of creating the correct kind which we’ll get to in a moment.
Case studies are another potential area for growth. In 2021, case studies made up 6.5% of content libraries, and in 2023 this decreased to 5.5%. In spite of this decrease, buyers spent 7% more time reading case studies in 2023.
Now let’s talk about what that looks like in action.
How to craft high-value content in the post-AI boom era
Here are a few tactical approaches to crafting high-value content that resonates with B2B buyers.
Enhance your approach to research and ideation
Effective use for AI tools goes beyond simply producing words. Other parts of your content workflow can be made far more efficient and effective. This might include using AI for things like generating complete outlines from a bunch of rough ideas, brainstorming related topics, producing creative briefs for another writer to work on, and more.
A word of warning though: just like you shouldn’t publish a first draft by a bot, don’t rely solely on AI output. Instead, use it as a springboard for your team’s creativity. Have your subject matter experts review AI-generated outlines and add their insights. This way you’re not losing the value of human expertise and creativity.
Put your data to work
Your data is your most valuable asset to leverage. Every company has data on customers and prospects and in many cases it’s more than they even know what to do with. An extremely small fraction of these companies are actually putting it to good use. Huge amounts of unstructured data is where AI shines. Use AI-powered tools to analyze your customer data, product usage statistics, content consumption trends. Then have your team interpret what’s significant and what’s not.
From there, create data-driven content pieces that showcase your company’s unique perspective on industry trends. Consider developing an annual or quarterly report that can be revised and updated as trends change, giving you no end of things to talk about.
Focus on “how I…” or “how we…” stories
The answer to boring, generic storytelling? Producing authentic, experience-based stories. As we already discussed, most people than ever are searching for case studies and similar pieces of content but fewer are being produced.
The likeliest reason why is that these are difficult pieces to produce as they rely on relationships and connections. It needs to become a part of your process to encourage your customers and employees to share their personal experiences and lessons learned. These “how I…” or “how we…” stories provide the real-world context and emotional resonance that B2B buyers are clearly searching for.
Shift focus to the content types that are working
Content analytics are where it pays to be able to leverage your own proprietary data. Pay close attention to engagement metrics and shift your resources towards the content types that are resonating with your audience.
If ebooks are maintaining strong engagement, invest in creating more comprehensive, visually appealing ebooks that offer deep dives into complex topics. If your blog is doing just fine with engagement compared to the overall trend in buyers, then keep on that track.
Prioritize Depth and Originality in Long-Form Content
AI excels at generating short-form content. If you need a few sentences or a paragraph, you’re more likely to get a solid response within a draft or two. Where it often falls short in creating the depth and nuance that your buyers want to see in long-form pieces.
For ebooks, whitepapers, and in-depth articles, use AI as a starting point, but invest heavily in human expertise to elevate the content. Implement a “two-layer” writing process: use AI to create a foundational draft, then have experienced writers and subject matter experts add depth, nuance, and original perspectives. Incorporate industry-specific insights, expert interviews, and detailed analysis that goes beyond surface-level information.
Conclusion:
The AI content boom has reshaped the B2B marketing landscape, but perhaps not in ways we anticipated. Buyers are more discerning than ever and fatigue has demonstrably set in with AI-generated content.
As a result, the future of B2B content is clearly not about producing more. It’s about producing better and there’s massive opportunities for marketing teams that create thoughtful, high-value experiences.
That all starts by treating AI not as a replacement for human insight, but as an amplifier of human expertise and ingenuity.
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ABOUT THE AUTHOR
Pete Lorenco ,Vice President of Marketing at PathFactory
Pete Lorenco is the Vice President of Marketing at PathFactory, the leading B2B content intelligence and personalization platform. With over 15 years of experience across startups and enterprise B2B organizations, Pete has a strong track record of driving growth through data-driven, customer-focused marketing strategies. Previously, he served as VP of Demand Generation at HYCU and Head of Marketing at Alyce, where he led teams to scale marketing efficiency, increase content engagement, and grow demand. Pete has also held various marketing roles at Avid Technology, Iron Mountain, and EMC.