AI in media monitoring: Not a choice between tech and people

AI is changing how media monitoring companies track, process, and analyse coverage. Joe Hamman, director at Novus Group, does not believe the choice is between technology and people (Image source: © 123rf 123rf)

In South Africa, the challenge is heightened by the range of languages and accents heard across radio and television, along with names and local expressions that automated systems do not always interpret correctly.

A recent 2026 AfriVox benchmark tested speech models across 20 African languages and more than 100 African English accents.

Performance varied substantially, including among languages the models were intended to support, while unscripted speech proved particularly difficult in some tests.

Why broadcast creates a harder problem

Broadcast does not arrive in neat blocks of searchable text. A presenter may introduce an interview before an ad break, return to the guest several minutes later, and continue for an unpredictable length of time.

An automated system may identify the correct brand or spokesperson but still get the start and end points of the clip wrong.

If it begins too late, an important part of the exchange may be missing. If it runs too long, unrelated discussion can be attached and change the context.

That is when a technical monitoring error becomes a business problem.

A communications team may brief an executive from an incomplete record or misunderstand how an interview landed.

Finding the mention is not enough if the information being used to make a decision is inaccurate.

Why human judgement still matters

Someone listening to the coverage can often recognise when part of an interview is missing or when the surrounding discussion changes what was said.

That is much harder to judge from an automated transcription alone.

A broadcast clip may help a communications team decide whether an issue needs attention or shape how an executive is briefed on a developing story.

If the clip is incomplete or misleading, the team is working from the wrong picture.

This is why I am cautious about treating maximum automation as the goal.

I am strongly in favour of using AI wherever it improves the work, and I expect its role in media monitoring to keep growing. But the level of automation means very little if the end result becomes less reliable.

AI is changing how media monitoring companies track, process, and analyse coverage.

I don't think the choice is between technology and people. AI can take on more of the work involved in collecting and processing media, but there are still points where human judgement determines whether what reaches the client is accurate and useful.