What the data is telling us about breaking through the AI noise.
Earlier this year, we launched our first Inksights: Media Intelligence Report, which analyzed media trends around IPO stories. This next installment of Inksights dives into what is likely the hottest topic of the moment — artificial intelligence (AI). What did we learn? AI’s dominance of media coverage is growing, but there are still some best practices for breaking through the noise to ensure your company’s story is seen and heard.
The following looks at AI media coverage volume trends, including the drivers behind recent spikes and how communications professionals can use this insight to time their company’s AI news. We also dive into the popular terms in AI articles, like machine learning (ML), data, and large language models (LLMs), and how they evolve. Lastly, we share what we learned about writing in AI shorthand, such as properly abbreviating generative AI.
AI Media Coverage Drivers
There are three main drivers of AI news cycles:
- Industry conferences
- Government regulations
- AI-related news from large technology companies
For instance, the largest AI news spike in 2024 (to date) was on March 19. What happened on or around that day? Microsoft hired Google DeepMind co-founder Mustafa Suleyman as the new CEO of Microsoft AI, Nvidia held its GTC developer conference, Databricks acquired Lilac, and the Department of Homeland Security unveiled its first AI roadmap. If you’re curious about the most widely covered AI story of 2023, it was Meta’s debut of its new AI-focused products, including the “Meta AI” chatbot assistant.
Want to take advantage of these types of AI news drivers?
- Execute proactive communications campaigns around industry events. While you should likely avoid the noise of the actual conference dates, releasing your own AI news in the weeks leading up to events like the Databricks Data + AI Summit increases your chances for media coverage while still giving you something fresh to talk about at the show.
- Prime your rapid response engine for new AI regulations. Most regulations are at least teased or rumored beforehand, so learn what you can and draft a comment from one of your spokespeople. Once the news hits, you can update the statement based on the specifics of the regulation and hit the ground running with timely media outreach.
- Day two stories can keep you in the news cycle. Some AI news tends to have a longer tail, so identify a surprising or fresh insight and offer it to journalists who may not have had a chance to cover the story yet.
- AI news is rarely a differentiator for B2B technology providers. The days of introducing a truly novel AI advancement for most companies not named OpenAI or Anthropic are behind us. Consider the factors we discussed before picking a launch day for that AI announcement.
How Popular AI Topics/Terms are Evolving
Term: Machine Learning
First Half of 2024
FY 2023
FY 2022
ML and AI are no longer as synonymous as the two terms once were. The clear trend over time shows that AI has no problem driving headlines on its own, but in 2024, ML is barely covered unless it is mentioned alongside its big brother.
This means one of two things: If you’re keen on telling a story around your ML technology, ensure it clearly aligns with the current crop of AI articles and themes. And if your company doesn’t have an ML story, it’s a good idea to avoid the term and find a more popular AI theme to attach to your point of view.
Term: LLM
First half of 2024
FY 2023
FY 2022
In 2023, you can really see AI stretch its legs and separate a bit from the LLM term. What is also clear is that LLM is still a significant part of AI coverage. If your company has an LLM story, there are a good number of journalists who already understand the term and will likely be willing to connect with your experts as long as it provides a new twist on the existing conversation.
Term: Data
First half of 2024
FY 2023
FY 2022
This analysis really shows how AI has taken over media mindshare in just 2.5 years. However, data remains one of the most popular terms in almost all AI articles. This means that even if you’re not a data company, you should be ready to answer data-related questions, specifically around what specific data powers your AI strategy (and where it comes from). On the bright side, your proprietary data is often the differentiator for your AI offering, so be ready to tell that story.
Term: Jobs
First half of 2024
FY 2023
FY 2022
AI is now written about a lot more than just centering around the jobs term. This means the conversation around AI stealing jobs has dissipated over time. While there may still be some jobs and workforce angles floating around the AI conversation, you may have a harder time convincing a journalist to care, so be really thoughtful about your story.
Write Like an Expert
AP Style Corner
In August 2023, AP Stylebook added a new AI chapter with guidance for journalists on how to cover AI and key terms like generative AI. According to AP Style, the writing and editing reference guide for journalism and newsrooms, the term is written as “generative AI” (with “generative” lowercase).
But how do we write the shorthand for generative AI? The AP Stylebook has yet to provide guidance. Is it “GenAI” or “genAI” or “Gen AI” or “gen AI”?
What do we, as communications professionals, do when AP Style guidance hasn’t caught up with the technology and terminology used in the field (or by the media)?
We look to the data for guidance.
The media has spoken: Based on our analysis of AI media coverage, the majority of journalists write the shorthand for generative AI as “GenAI” – with a capital “G” and no space.
The experts agree: Companies including OpenAI, Microsoft, and Databricks, etc. all write “GenAI” as the shorthand for generative AI.
Don’t take our word for it; take it from ChatGPT!
The final verdict: generative AI (GenAI)
Missed our last Inksights post? Check it out here: Inksights: Media Intelligence Report | IPO Trends
Methodology: To keep the results-focused and accurate, we analyzed AI media coverage at top-tier national business and technology press, including Axios, Bloomberg, Business Insider, CIO.com, CNBC, eWEEK, Fast Company, Financial Times, Fortune, InformationWeek, InfoWorld, Network World, SiliconANGLE, TechCrunch, TechRepublic, VentureBeat, The Verge, The Wall Street Journal, WIRED, and ZDNet. We used several tools to conduct this analysis, including Cision and Meltwater.
