I have a confession to make: ChatGPT gave me the idea for this article.
But it couldn’t have done it without me. (And no, I didn’t use it to write the article).
I had wanted to write a foundational piece of sorts for my newly pivoted service website as a B2B content strategist. As I built my services and determined my UVPs, I knew that I needed to address the role of AI and LLMs for B2B content strategy and development.
But I wanted a piece that positioned me correctly along with my services and messaging on my site. I wanted content that stood out (after all, I promise differentiated content for my clients, right?) and wasn’t general for marketers who already know “5 Changes AI brought to B2B Content.” Everyone has that.
Since building my offerings and pivoting my business, I’ve been brainstorming heavily with ChatGPT.
As a result, it now knows (or has even suggested):
- What services I offer that other SEO and B2B marketing companies and content strategists do not
- How I want to position myself now as a B2B content strategist vs a B2B content writer
- The general state of LLMs and AI in the B2B marketplace and the objections clients might have on how/whether I use these tools
So as I continued using it, we came up with the idea of this blog post together.
How You Should Use AI in Your Content Strategy
This is how B2B content strategy should work. Many companies, however, rely on old strategies that haven’t worked in the past (or did work to a certain extent but never optimally). The evolution of AI tools hasn’t changed these companies’ strategies or quality of content.
Instead, AI is amplifying the mistakes many SEO companies and marketers were already making.
Mistakes such as:
1) Publishing top-of-funnel content at scale
AI enables companies to create more generic content at scale that is indistinguishable from your competition.
For example, companies may try to rank for basic industry terms in a glossary, dismissing the fact that it serves no value for their target audience (e.g, Why would a CISO look for a definition of SIEM? Or a RevOP need a definition for a sales funnel?). Or companies may try to write guides or ebooks that are too general for their audience. This strategy may bring traffic, but it’s usually students learning about the subject matter, researchers, and others who are not their ideal customer profile.
Regardless of where this low value content is on your website, B2B buyers aren’t looking to be educated on basic terms in their industry. They’ve spent time doing research on your product and have tried to find various solutions to their pain points on their own before reaching your site.
They need specific content that delivers a solution to their pain point, tied in to exactly how your product will help you.
For example:
- How X (your product) Helped Company Y do Z
- Why [persona] Fail at [pain point]
- Pros and Cons of X vs. Y for [pain point]? (but with in-depth explanations of features and credit to where the competition might be better)
This is where AI can help you:
- Building specific personas
- Research to better understand their pain points
- Brainstorming new angles for blog posts (like I did with this one)
2) SEO as a silo of marketing instead of an integrated part of product, sales and customer services
Since buyers come with specific pain points and expert knowledge of your industry, your SEO strategy, writers, and marketing team must integrate with your product team and SMEs to deliver the type of content your B2B audience wants. Content that delivers real solutions to real problems.
Here AI can help you:
- Take transcripts or interviews from sales/SMEs and formulate the pain points of audiences
- Connect pain points to solutions your product delivers
When you do this, you create high-value content that uncovers hidden risk, handles any objections from prospects, and explain complex stacks or processes and evaluates pricing, cost and ROI. These types of content are highly specific and speak to a B2B SaaS’s expert audience.
Content with titles such as:
- Multi-Entity Accounting Pitfalls for SaaS Companies Expanding Globally
- Revenue Recognition for Companies Using Stripe + NetSuite
- Cost of Revenue Leakage at Scale for Finance Teams
3) Measuring content performance instead of business impact
If you write generic content without input from product teams or SMEs, it may rank effortlessly — but it won’t convert, because it doesn’t reflect real buyer problems. This is the same challenge B2B teams had before: measuring what’s easy (traffic, rankings, impressions) instead of what matters (conversions, demos, signups).
AI engines work the same way. Strong search performance helps, but AI surfaces content that actually helps expert audiences make decisions, not content optimized only for keywords. The good news: if you focus on high-value BOFU content grounded in real expertise and real buying moments, you’re highly likely to win in both search and AI-driven discovery.
Here AI can help you:
- Focus on examples and data that are directly relevant to your buyers, so content addresses real problems.
- Generate the top questions your buyers would have at each stage of the journey.
- Connect questions, examples, and data to different CTAs, creating testable variations for conversion optimization.
B2B Content Strategy: The Long Game
Most companies don’t publish these types of posts because they take time, effort, and cross-team collaboration. It’s easier for marketing to stay in its silo and focus on measuring content performance and top-of-funnel content than it is to focus on leads, signups, and demos.
But AI doesn’t care about vanity metrics – it focuses on what’s useful to your reader. Winning the content game now demands focus on real buyer problems, measurable impact, and cross-functional collaboration.
The difference now is that AI just made it impossible to ignore.
Contact me here so you can start investing in a B2B content strategy aligned with your business goals today.