Media Technical Directors/Managers

Other duties are still done by people. Scheduling studio time or equipment usually relies on ordinary calendars or planning software, with no major AI yet, since it requires human coordination. Creative decisions – such as choosing camera filters or setting up visual effects – remain human-led.

Experts point out that AI is most often used for routine work, freeing people to handle the creative side. As one industry roundtable put it, AI today handles “captioning, metadata tagging, [and] content indexing” so “staff [can] focus on creative work” ^[2]. Tasks involving policy-making or training new staff are complex and interpersonal, and we found no signs AI has taken over these jobs.

In short, technical checking, captioning and switching tasks can be augmented by software, but guiding creative choices and teaching remain human strengths.

However, adoption is careful and uneven. Broadcasting equipment is expensive and often custom, so adding AI usually means big investment. Experts warn that “high implementation costs [and] technical infrastructure requirements” can be barriers ^[2].

Stations need new software, faster networks or the cloud – and must train staff to use it – which slows rollout. On top of that, TV and radio follow strict rules. For instance, the FCC is already moving to require TV ads to disclose any AI-generated content ^[3], reflecting regulators’ caution.

Industry sources also note that many professionals are “still figuring out which tools to use” and have even created new “AI specialist” roles to guide this change ^[4]. In other words, AI in broadcasting is real but still young – most stations are moving step-by-step. Where it’s useful (like camera quality checks or automated captioning), adoption is growing, but anything that needs human judgment or touches sensitive content will likely stay human-led for a while.