Beyond the Hype: 4 Areas Where AI Writers Fall Short for B2B Tech Content Writing
Google Is Freaking Out About ChatGPT (The Verge, Jan 2023) The ChatGPT AI Hype Cycle Is Peaking, but Even Tech Skeptics Don’t Expect a Bust (CNBC, Feb 2023) The Inside Story of How ChatGPT Was Built From the People Who Made It (MIT Review, March 2023) All these are headlines reflecting upon the fact that ChatGPT has had the best Public Beta of all time. Every nook and corner of search engines and social media has been flooded with narratives – some hyping it even more, others talking about the possible improvements, and a few informing how it has taken human jobs already. But while a lot of ChatGPT text-generation use cases and applications have surfaced over the past few months (thanks to excellent prompt engineering), there are big question marks around AI’s viability to create long-form content – especially for a B2B audience. Is AI Any Good for Long-form B2B Tech Content? (Our Research Attempted to Answer This) The argument for writing articles and blogs using AI goes back to Q1 2021 when GPT-3 AI tools were being rolled out one after another. In October 2022 (before the launch of ChatGPT), we started testing the top GPT-3 tools to understand how well they do for B2B articles. We tested them across major technology themes (like cloud, data analytics, cybersecurity, etc.), and here’s what we observed: Here’s the full research report. Of course, these results can be a bit biased in a sense that: But that’s the thing. When we’re talking about consumer-facing content, there’s no room or excuse for compromising the quality. And so, the question pops up – Why exactly are we using AI writers? Is it because human writers aren’t adept? (Surely, that isn’t the case) Is it to increase the frequency of publishing content? Is it to lower the costs of content creation? Is it to increase productivity? The reasons could be manifold. But they often get obscure when riding the hype train. So, almost every answer will include the umbrella terms “productivity” and “cost.” And that’s understandable since these are integral to a business’s bottom line. But then, what exactly does productivity entail here? How is it being defined? And how are the cost advantages being realized? One explanation could be amping up a writer’s workflow – equipping them with an AI tool that reduces their cognitive load. So, with relatively lesser cognitive input, they would be able to create a similar-sounding output. In fact, AI writers accrue several benefits for inspiring ideas, removing writer’s block, and helping with lo-fi content outlines. We’ve compiled the good things here. But a lot of the presumable capabilities fall flat when it comes to creating long-form B2B tech content. Why’s that the case? Let’s discuss. 1. Original Content Before getting into the granularities of B2B-esque content creation, let’s address the elephant in the room, shall we? Although duplicate content (or plagiarism as it’s called in academic circles) isn’t always penalized by Google, it’s still an aspect of content creation that must be avoided. At the end of the day, search engines (especially Google) want original, helpful content to come up. However, often, AI is very standardized in pushing out answers to your queries. Here’s an example. I asked ChatGPT – what is low-code development? But I did that three times – at different times. The answers, albeit quite relevant, overlap both structurally and linguistically. All these explanations start with a definition, transition into the goals, approach the benefits, and outline the applications. From the looks of it, that’s an ideal, all-encompassing explanation – but only for the purpose of learning and not creating original content. Notice the repeated keyphrases across definitions and the astonishingly similar sentence structure accommodating them. Even if you change the prompt to, let’s say – “explain” or “define” low-code development, the language used is similar. These are just three queries from a single account. Imagine how many people will be asking the same questions. So, even if you structurally refine the content, you’re still leaving much to be desired when it comes to originality. A possible and reasonable refutation to the same can be put forth in the name of prompt engineering. What if you give highly-specific, example-laden prompts and probe the AI until it gives you a quality output? Well, that’s surely opportune. However, that will also involve structural overlap in how the prompts are created. Why? Because the entire field is based on formulaic frameworks – much like you keep seeing on LinkedIn these days. So, it’s highly likely that the most relevant prompts are exceptionally similar. 2. Service/Capability-Oriented Writing A good B2B content strategy supports a mix of informational and promotional content. The latter is concerned with reflecting upon a business’s capabilities to potential leads. This can be realized via: Besides, a host of B2B businesses help implement products from global vendors. For example, IBM, ServiceNow, Salesforce, Microsoft, Amazon, SAP, and Google have product and service implementation partners (the B2B businesses) helping spread the word about their products and lowering the entry barrier to their adoption. Such businesses center their content around the capabilities of these vendors, and understandably so. Why isn’t AI a good fit here? For one, GPT-3 powered tools cannot scrape data from the web as per a business’s specific preferences. In general, they can control the subject-related output from a technical standpoint using certain parameters like temperature, top p, frequency penalty, presence penalty, and more. These parameters work to increase the creativity, originality, and recency of the outputs. As such, a lot of AI writing tools allow users to tweak the creativity levels of the text. However, stringently controlling the output to talk accurately in terms of business offerings is a whole different ball game and certainly something that hasn’t been accomplished – at least until now. It’s even more challenging when we consider unique offerings from small businesses – a capability that the B2B SaaS landscape thrives on. And this is also where the problem of