Probabilistic determination of the next best possible word – that’s certainly the essence of AI writing tools powered by the famous language models GPT-3 and now GPT-3.5.
It’s all computation, and it’s reasonable when people point out – well, where’s the personality in writing? Where’s the technical nuance? These questions reflect legit objections. In fact, our months-long research outlined how:
- AI writers contributed less than 30% (in terms of text used for the final write-up) for highly technical B2B articles.
- The articles where AI writers contributed more than 70% were extremely basic, definition-oriented, and moderately or non-technical.
But why these questions in the first place?
Possibly because people are being led to believe that AI writers are the be-all and end-all. But if we closely monitor the LLM (large language model) space over the last three years, even the most prominent AI writing tools out there recommend refining content using human expertise.
Truth be told, AI writers aren’t exactly a replacement for humans. They are, instead, immensely viable for augmenting a writer’s capabilities. When we look at them from that perspective, we can outline the many benefits they can accrue for long-form content creation in the B2B space. And that’s what we’re going to do here.
For ease of illustration, we’ll use outputs from ChatGPT for this article.
1. Providing Writing Inspiration That Isn’t “Time” Bound
If there’s one thing that’s constant in the B2B space – it’s “change.” Technologies constantly evolve, vendors accommodate such evolutions, businesses invest in the new roll-outs, and the entire vertical goes through a metamorphosis.
The same is reflected in writing. Even the most generic of narratives want to weave in innovations and recent trends. It’s through those that they can truly reflect upon the “value” being added in the “present” context – via a service or a product.
But this doesn’t detract from the fact that AI can lower the entry barrier to basic business or technology-related ideas or perhaps add to the ideas that you’ve already laid out.
Let’s say you are creating a guide titled – “Best Practices to Create a Fintech Mobile App.” ChatGPT can come in handy to get the gist of the potential user pain points that must be considered.
For example, let’s ask ChatGPT to give us three user personas for a fintech mobile app.
The response is not bad. It provides potentially useful information that could fit our narrative. But since we aim to outline the pain points, let’s probe the response further to understand each persona’s challenges.
Not bad at all! We could now use these to substantiate what we already know and develop an example-laden, all-encompassing article around the best practices.
2. Helping Write Templatized Content Elements
Meta descriptions, SEO titles, email subject lines, image captions, confirmation messages – a host of content elements fall within the purview of frameworks. SEO titles and meta descriptions, for example, must adhere to a certain character limit, and it bodes well if they include the targeted keyword.
Let’s ask ChatGPT to create a title and meta description for the aforementioned article – “Best Practices to Create a Fintech Mobile App.”
Not the best, but it lays the groundwork. It can be refined more based on the article’s content.
Likewise, let’s use ChatGPT to create a catchy headline for this article.
Not bad! Can these be improved? Certainly! But again, these preliminary recommendations provide much to go about and save time.
Note: Understanding what you want to write about, what’s your business focus, and how you want to tell the story is critical before using AI to generate recommendations. Because this knowledge is what’s going to help discern if what you’re looking at is worthy of including in your process. Don’t be blindsided by the guise of immaculate articulation. It’s not that ideal – not more than your experience-led story.
3. Creating Lo-Fi Article Outlines
AI writers aren’t well-suited for consumer-facing B2B content. For one, the output can be factually and conceptually incorrect. Second, the content is exceptionally standardized – lacking personality, vision, and the ability to emulate a brand’s voice and tone.
But this utter standardization, i.e., lexical and structural exactness of GPT-powered textual output, makes AI writers well-suited for a basic content flow.
Let us call this flow a “low-fidelity content outline” or “lo-fi” outline.
Let us ask ChatGPT to create an outline for one of the blog titles that it previously suggested.
“5 Proven Strategies for Creating a Top-Performing Fintech Mobile App in 2023”
The response is basic at best. Perhaps more probing would result in a more profound outcome. But we can still outline a few key things. For example:
- Personalization and customization can create an opportunity to discuss SaaS capabilities like data analytics, business intelligence, rewards and loyalty programs, and more.
- The content can be segregated across two major themes – design and technology. Design can cover UX/UI design and content design. Technology can cover security, integrations, analytics, and more.
All in all, a comprehensive content brief can come to life in relatively less time.
4. Taking Good to Excellent
All these capabilities suggest one thing – that AI writers can help human writers. And this can be realized in terms of:
- Speeding up research
- Speeding up writing
- Including analogies and examples
- Reducing cognitive fatigue
This can speed up the entire content generation workflow and open opportunities for scalability.
But the “quality” of the output would still depend on human competence.
More to come in this series around:
- Things that AI’s Bad at
- How can you detect AI content?
- Why AI fails at writing thought leadership content? (and why you shouldn’t opt for it in the first place)
- Why AI fails at writing good listicles
- Why AI is making us mentally obese
Besides the above, what more would you like to know? Let us know your thoughts and opinions in the comments below.