The rise of AI – What does it mean for PR analysis?

The emergence of Big Data and Artificial Intelligence as factors in public relations work is exciting, as the promise each holds is substantial.

The idea that we will soon be able to process and assess large data sets with minimum human involvement is an attractive one. Analysis work is so important and yet so time consuming—and the pace of input data continues to accelerate. It often feels as though we’re barely keeping our heads above the deluge of data.

Big Data

The term “big data” is used frequently, and quite often it is used incorrectly. Big Data as it is understood to be defined by those who work with large data sets must meet certain criteria. Back in 2001 Gartner analyst Doug Laney defined Big Data (PDF) as having three contributing characteristics: it must have high velocity, high variety, and high volume. Distilled down to its essence, “Big Data” accumulates quickly, in a variety of types, and there is a lot of it.

Most PR professionals and communicators aren’t routinely working with what could truly be defined as “Big Data”—yet. This is beginning to change as communicators become more aware of how corporate data are being used to inform everything from sales strategies to logistical planning. The volume of news and information being created globally does qualify as Big Data, but the amount of that news that is relevant to a specific company or institution is a subset of that—so, in most cases it is not technically Big Data even if there is high volume.

Artificial Intelligence

That said, there is still a place for the adoption of Artificial Intelligence (AI) in the processing of news volume. The most basic definition of AI is that it asks machines to perform tasks that require intelligence. This includes language intelligence (asking Alexa a question), and visual intelligence (such as a self-driving car “understanding” traffic signs).

The issue is that we are not quite there yet in terms of the accuracy of natural language processing capabilities. Neuro-linguistic Programming is used to determine automated sentiment analysis, and although it has improved over the years it remains incapable of correctly assessing idiomatic expressions, sarcasm and other linguistic nuances.

It is likely that in the future, AI will be able to process large volumes of media data and provide us with results that are actionable. However, we aren’t there yet.

Public relations analysis

AI and NLP improve efficiency, freeing up time for humans. This reduction of the repetitive tasks and those that can be affected by biases allows communications professionals to use their time better, so they can perform the higher-level analysis work.

We now have the computing power and storage capacity to process high volumes of data faster than ever before, which is an asset. Creative thinking and accurately analyzing information through the specific lens of client needs remains a job for humans, particularly when conducting analysis for global interests that span a variety of languages and cultures.

Chip Griffin

Chip Griffin is the Chief Operating Officer of CARMA, a global media intelligence company delivering insights to multinational companies, leading nonprofits, and government agencies. For more than two decades, he has helped organizations understand how media coverage impacts reputation and results.