Few in B2B Tech can fail to have been impressed with the quickening pace of innovation from LLM players. Take Alibaba with its much-feted Qwen, an open source alternative which has spooked US rivals, or Anthropic, whose product team seems to drop new versions of Claude at the speed of the F1 team it just sponsored.
Less impressive was the furore caused by Grok’s nudification, or, ChatGPT’s less offensive, but dumbed down, ‘caricatures”. But behind the massive take-up of these seemingly trivial AI features lies a permanent truth. Distribution matters.
Any new technological breakthrough is ultimately only successful if it achieves widespread adoption. Few can doubt, despite any moral reservations, that X and OpenAI benefitted from the viral publicity of these launches. These meme plays are in truth onramps, sales plays to drive up the users of their underlying LLMs. Consumers are fickle enough to try gimmicky use cases and lazy enough to stay put once they have found an LLM who produces acceptable, or just funny, results at wizard-like speed.
The biggest ‘Crossover Tech’ since the iPhone
For those of us in B2B Tech, the rise of consumer exposure to AI in their everyday lives is encouraging and, for some, threatening. With colleagues, customers and partners all using the tech daily, they are under pressure to figure out how AI can be harnessed for their goals.
So far they have been understandably cautious. Much innovation fails on first contact with reality. Boxing world champion Mike Tyson, nailed it with “Everyone has a plan until they are hit in the mouth’. History, particularly B2B Tech’s history, is littered with technical ‘betters’. Technology offerings loved by engineers, but which never achieved their commercial potential to create or dominate a new tech category.
So what then is the B2B Tech marketing community to make of all this AI? What is the best course of action when your B2B customers, who of course are all also consumers of B2C tech, change their behaviour?
Three questions for B2B Tech marketing
Aside from littering content with references to how exciting technology is now ‘AI-enabled’, a practice known as ‘AI Washing’, what on earth are the Chief Marketing Officers to do? How can they make sure the move to AI-first Search, replacing the Google Search many relied on for a decade or more for lead sourcing, does not leave them behind?
The short and uncomforting answer is; nobody knows. Yet. That said, the questions for those hoping LLMs can help them with their promotion of their products and services are obvious:
- What are my customersactually asking AI?
- Which sources does AI cite when answering?
- What is our AI content strategy?
AI Visibility changes
Research our team has done over the last 12 months, based on live AI Visibility projects and data from industry-leading platforms such as AhRefs and SemRush and based on millions of their prompts, proves the answer changes almost daily. Our own work with four clients over the last year backs this up due to several underlying trends in this first tranche of users. Key findings for marketing professionals to bear in mind include:
1. Baseline data ingested by learning models changes with each revision
Previously all-important sources like Wikipedia, held a dominant share in almost all of the early results, now rival sources, including Reddit and Grokipedia are on the rise.
2. Wild swings in user prompts as they learn and adapt to inference models
The early days of AI are fast receding and users have moved on from “What is the best…?” to more sophisticated long-tail answers to specific needs
3. LLMs are the new intermediaries
This obvious point should revolutionise how marketing professionals communicate and create content. LLMs crawl websites and ‘read’ media articles differently. This should be a priority concern and will for sure change a lot over time.
One definition of stupidity, accredited to Einstein, is to continue performing tasks the same way and expecting different results. Unlike previous generations of consumer tech, AI chatbots, and even more so agentic commerce, are upending the way B2B customers research, shortlist and even vet potential purchases.
Ditch the old playbook
Because of the fundamental ways B2B buyers are behaving thanks to AI, the response from the industry needs to change radically. To win out requires sales and marketing teams to raise their game on three new disciplines; discovering what customers are actually asking of AI, which sources return the most citations from these prompts and how increasingly pressured content budgets are best-deployed to take advantage of the new buyer behaviours.
To do this, a new set of behaviours and skills need to be nurtured. The key is deep understanding of what drives AI Visibility, adaptation to the way market communications are structured as well as where they are targeted. Increased AI Visibility will prevent us from being ‘blind’ to the opportunities of new AI-first buyers and new ways of presenting our content to them should allow us, over time, to be less ‘dumb’ – or at least create exciting new ways to talk about our products.
