Written by Benjamin Pius (Publisher @ BMA) as part of the forthcoming Radio Broadcasting Convention – Africa 2026, 1–2 July 2026, The Venue Green Park, Johannesburg, South Africa. Register and view the full programme →
Picture this: it is 6.47 am in Lagos. A 28-year-old marketing manager unlocks her phone, and before she has boiled the kettle, her favourite radio app has already queued a Yoruba-language news bulletin, a mid-tempo Afrobeats mix curated for her commute, and a short business podcast segment flagged because she paused on a similar episode last Tuesday. No human producer assembled that sequence. An AI did — in milliseconds, from patterns it has been learning about her for months, which is not a vision of radio’s future. It is happening now, and the gap between broadcasters building these capabilities and those not doing so is widening by the quarter.
“The gap between the broadcasters who are building AI capabilities and those who are not is widening by the quarter.”
Globally, the blueprint is clear. Spotify’s Discover Weekly — built entirely on machine-learning analysis of over 600 million listener profiles — is credited with transforming passive users into deeply loyal subscribers. iHeart Radio in the United States uses AI to dynamically adjust playlist sequencing based on real-time engagement signals.
African broadcasters are beginning to follow suit: South Africa’s digital radio ecosystem and platforms such as Boomplay are gathering the kind of listener data that, properly analysed, can power genuinely personalised audio experiences.
The business case is straightforward: personalisation drives dwell time, dwell time drives advertising yield, and advertising yield funds better content. The virtuous circle is there to be entered.
Yet the same AI revolution that enables personalisation also creates an urgent new liability. In 2024, a major West African broadcaster inadvertently aired a synthetically generated music track that embedded a copyrighted melody without licence — triggering a regulatory complaint and a costly settlement.
It was not an isolated case. As tools like Suno and Udio make it trivially easy to generate studio-quality audio that may contain elements from copyrighted training data, the compliance risk for broadcasters is real and growing.
The response is also AI-driven: audio fingerprinting platforms such as ACRCloud and Audible Magic can scan broadcast output in real time, matching audio against databases of tens of millions of licensed works and flagging potential infringements before they become regulatory problems.
Kenya’s Communications Authority and Nigeria’s NBC are already signalling that digital content rights enforcement will intensify — broadcasters who are not investing in automated rights monitoring are building exposure they may not yet fully see.
“Personalisation drives dwell time, dwell time drives advertising yield, and advertising yields better content — the virtuous circle is there to be entered.”
At the Radio Broadcasting Convention – Africa 2026 in Johannesburg this July, these twin imperatives — personalisation and protection — will sit at the heart of the agenda.
The broadcasters in that room will not be debating whether AI matters to their industry. They will be working together to figure out how to lead with it.
The organisations that leave with a clear AI strategy — one that is as rigorous about rights compliance as it is ambitious about listener experience — will be the ones defining African radio for the decade ahead.
Written by Benjamin Pius (Publisher @ BMA) as part of the forthcoming Radio Broadcasting Convention – Africa 2026, 1–2 July 2026, The Venue Green Park, Johannesburg, South Africa. Register and view the full programme →
RADIO BROADCASTING CONVENTION – AFRICA 2026
● Dates: 1–2 July 2026
● Venue: The Venue, Green Park – Johannesburg, South Africa
● Theme: Intelligent Radio and Audio for the Next Generation of Listeners
● Register: radio.broadcastingandmedia.net
