How AI can remove friction but not remove craft

There’s a lot of noise around AI in broadcast right now. The framing tends to swing between two extremes: it’s either the future of everything or the end of jobs as we know them. Neither position is particularly helpful.

The truth is much less dramatic. AI isn’t arriving in our industry. It has been embedded in it for years. From automated audio clean-up to intelligent asset management, from metadata tagging to colour matching tools, machine-assisted processes are already part of the workflows we rely on daily. What’s changed isn’t the existence of AI it’s its visibility of it.

That visibility has understandably triggered fear. We are in a period of financial contraction across production and post. Freelancers are feeling exposed. Budgets are tight. In that context, any tool that promises “efficiency” can sound like a threat.

But the real risk isn’t AI itself. It’s unstructured adoption under financial pressure.

Every major technological shift in broadcast has triggered resistance. The move from SD to HD raised concerns about cost and workflow upheaval. The transition from tape-based acquisition to tapeless systems was met with scepticism and, at times, outright hostility. In each case, the industry adapted not by standing in the way of progress, but by shaping how that progress was implemented.

AI is no different. Take a simple example from post-production. On a low-budget factual series shot across multiple camera types, it’s not unusual for a significant portion of a grading session to be spent balancing cameras before creative work even begins. That technical alignment is essential, but it isn’t where a colourist’s real value lies.

If AI-assisted tools can pre-standardise or intelligently balance those inputs before the creative grade starts, that doesn’t remove the colourist. It elevates them. Instead of spending hours matching cameras, the focus shifts to mood, tone and storytelling. Efficiency gains are redirected toward craft.

That redirection doesn’t happen automatically. It requires intention.

The question isn’t whether AI should be used. It already is. The question is how the value created by automation is distributed. If efficiency gains are used purely to compress budgets and reduce human input, creative quality will suffer. If they are used to protect and enhance the time spent on genuinely creative decisions, the industry benefits.

AI should remove friction, not remove craft. Standing in the way of progress doesn’t protect the industry. Shaping how progress happens does. That means networks, production companies and post facilities need clear frameworks around AI usage not to restrict innovation, but to ensure it serves the craft rather than undermines it. Technology is neutral. Implementation is not.

Chloe Dean is senior post production manager at Click Post Production