Words matter. Today, NLP is being applied to written and verbal text as a means of extracting specific details and flags about a given piece of content

Communications is often viewed as a largely human-driven art form, but language represents a structured and highly calculable phenomenon. As such, NLP has existed as a sub-field of computer science and AI since the 1950s. It’s only been in recent years—thanks to the rise of digital media and the subsequent information overload bestowed upon society—that this branch of computer science has made tangible inroads in the communications realm. Today, companies are putting NLP to work in a number of practical applications designed to ease the burden of our information-drenched society.

Communications professionals are intimately familiar with the concept of information overload. They experience it themselves, yes, but more importantly, they are tasked with communicating with people whose jobs are defined by it—journalists, analysts and busy executives across industries. In the past, “breaking through the clutter” has been about making personal connections, finding compelling angles within a news story, and writing eye-catching subject lines and press release headlines. They’ve done so with the assumption that those news angles, subject lines and headlines were being screened by humans. And that’s precisely the assumption that they can no longer afford to make.

Increasingly, journalists, analysts and executives of all sorts will begin relying on AI and NLP to parse their incoming information streams for them.

Social news feeds, content recommendations from publishers, and search results are all based on AI-powered algorithms that suggest content that is relevant. NLP software and solutions are a necessary remedy to the completely overwhelming flow of information that has consumed people these days, and they have very real implications for the tactics that communications professionals use going forward. Consider the below NLP applications, as well as their broad implications for communications professionals:

Clarity of Message

One of the most basic but useful functions NLP serves is to distill lengthy documents into short, simple descriptions. Most communications professionals pride themselves on being clear, but in the age of NLP, there’s no such thing as being too obvious. Crafting brief summaries (and labeling them) for all documents and scripts as a matter, of course, can help ensure NLP software sees what we want it to see. And structuring paragraphs and sentences in straightforward ways, with the most important information up top and without hyperbole, can also assist software that is looking to wisely parse your text.

Extracting the Pertinent Details:

Words matter. Today, NLP is being applied to written and verbal text as a means of extracting specific details and flags about a given piece of content. Again, words and phrases matter here more than you might realize. For example, if a CEO opens an earnings calls by claiming, “I simply can’t recall a more robust time for sales,” it’s very possible that the word an NLP program will seize on is “recall.” As in a product recall. In extracting pertinent details for an analyst and characterizing the call, the program very well might assign a negative connotation to an earnings call that was quite positive. One such company, Amenity Analytics, can even detect deception or deflections from transcribed documents such as an analyst Q&A.

Communications professionals have long understood the importance of Search Engine Optimization (SEO) when it comes to creating content. NLP represents a massive extension of the SEO concept. NLP is being used today to do so much more than taxonomize across the Internet. It’s being applied not only to written text but also to the increasing volume of audio and video content online—earnings reports, company explainer videos, webinars, you name it.

As communications professionals, the dawning of the NLP age reminds us that our words matter more than ever. The ability to ingest massive amounts of content, derive meaning from it, and filter for relevant and irrelevant news is becoming a key differentiator within a number of disciplines, including journalism and communications. NLP is what’s delivering this differentiator. As communicators, we need to be thinking about how we leverage these tools and adjust our tactics to ensure we’re communicating what we hope to communicate, not just to our human audiences, but to our AI readers and listeners as well.