AI as a Creative Amplifier: Lessons from 35 Years of Production Evolution

After three and a half decades in this business, I’ve watched our industry reinvent itself more times than I can count. From the early days of paper call sheets and fax confirmations to the digital revolution that changed everything about how we coordinate productions, the constant has always been change itself. Now we’re in the middle of another shift, this time with AI as a Creative Amplifier, and I’m seeing some familiar patterns alongside some genuinely new possibilities.

At Legend, we’ve always believed that technology should serve the story, not the other way around. That philosophy has guided how we’ve approached AI integration over the past couple of years, and what we’ve discovered might surprise you.

The Unglamorous Revolution

The AI implementations that are moving the needle aren’t the flashy ones making headlines. They’re happening in the production trenches, in those moment-to-moment workflows that can make or break a show.

Take our run of show documents. Anyone who’s been in this business knows that feeling when the client calls at 10:47 PM with a speaker change that cascades through your entire timeline. We started experimenting with AI tools that could handle these updates dynamically, not just changing the one line item, but automatically adjusting all the downstream timing, flagging potential conflicts, even suggesting buffer adjustments based on historical data from similar shows.

Is it perfect? No. But it’s gotten us out of more than a few late-night scrambles, and more importantly, it’s freed up our production managers to focus on the human elements, managing client anxiety, coordinating with venues, thinking three moves ahead instead of just trying to keep the spreadsheet accurate.

We’ve seen similar gains in our show documents and on-site scheduling. The AI doesn’t build our schedules for us. Still, it’s incredibly good at generating the complex formulas that tie everything together, especially when we’re dealing with multi-day events or simultaneous productions. What used to take hours of formula-building and cross-referencing now happens in minutes, which means our teams can iterate faster and test different scenarios without losing days to spreadsheet mechanics.

Making Sense of the Information Flood

One of the biggest operational challenges we face is information management. Client calls where requirements evolve in real-time. Stakeholder meetings where everyone has a different vision. Technical briefings packed with details that matter, but only if you can surface them when decisions need to be made.

We started using AI transcription and content extraction tools about eighteen months ago, initially just for client calls. The game-changer wasn’t the transcription itself; It was having searchable, tagged content that our team could query. “Find every mention of lighting requirements from the Johnson event calls.” “Pull all the budget discussions from last month’s check-ins.” Suddenly, institutional knowledge became instantly accessible instead of being buried in someone’s notes.

The real test came during a particularly complex corporate event last fall. Three months of planning calls, constant requirement changes, and multiple stakeholders with competing priorities. When we hit crunch time, being able to instantly surface specific client preferences and decision points from weeks of conversations, that’s when I realized we weren’t just saving time, we were delivering better client service.

Post-Production Acceleration

Our video team has been experimenting with AI-powered time coding and content highlighting for quick turnaround projects. The technology pre-identifies key moments, emotional beats, specific content markers, basically giving our editors a roadmap through hours of footage before they even start cutting.

Here’s what surprised me: our editors were initially skeptical, worried about AI making creative decisions for them. What they found was the opposite. Having those markers meant they could spend their time on actual creative assembly instead of the mechanical work of content review. One editor told me it was like having a really good assistant who could pre-sort everything but never tried to tell you what the story should be.

We used this approach on a recent conference recap video, eight hours of keynotes and breakout sessions that needed to be turned around in 48 hours. The AI helped us identify the key moments and quotable content, but the creative decisions about pacing, emotional arc, and which moments served the client’s objectives that was all human. The technology just made it possible to find those moments without manually scrubbing through eight hours of footage.

Expanding Creative Possibilities

Music supervision has always been a time sink. You know the drill, client wants something “energetic but not overwhelming, contemporary but timeless.” We started using AI-powered music search tools that can understand those kinds of creative briefs. Feed it mood descriptions, instrumentation preferences, even lyrical themes, and it surfaces options that our music supervisors might never have found through traditional catalog browsing.

The key insight is that it’s not replacing our creative judgment; it’s expanding our creative palette. We’re finding tracks from artists and labels we’d never encountered, discovering music that perfectly fits the brief but comes from completely unexpected directions.

Similarly, captioning used to be a budget line item that smaller clients often had to skip. AI-powered captioning and transcription services have changed that equation completely. The quality has improved dramatically while costs have dropped to the point where accessibility is now standard on virtually every project. That’s not just good business, it’s the right thing to do.

Why Human Judgment Still Rules

Here’s what I’ve learned about AI integration: the technology works best when you’re clear about what problems you’re trying to solve. We don’t implement AI tools because they’re trendy. We implement them when they address specific friction points that are preventing our team from doing its best work.

The creative vision that transforms a client brief into something memorable, that’s still human. The relationship management that turns a crisis into a collaborative problem-solving session is human. The real-time intuitive decisions that come from years of reading rooms and understanding audiences.

AI amplifies these capabilities by handling the mechanical work that used to consume so much of our bandwidth.

The Long Game

We’re still early in this AI evolution, and I suspect we’ll look back on today’s tools the way we now look back on those early digital production systems, primitive but essential stepping stones. What I’m confident about is that the production companies thriving five years from now will be the ones that learned to thoughtfully integrate these capabilities while maintaining focus on what clients care about: compelling content, flawless execution, and experiences that achieve their objectives.

The question isn’t whether AI will continue to change our industry, but rather whether we’ll harness that change to become better at the fundamentally human work of bringing creative visions to life. Based on what we’ve seen so far, I’m optimistic about the possibilities.