AI in Hollywood: Threat or Storytelling Upgrade?

AI is now part of everyday filmmaking. Some people see opportunity. Others see threat.

So, will AI destroy Hollywood and the film industry. Or will it change how we tell stories, who gets to tell them, and what “craft” even means.

AI is already in how films get made. Whether we admit it or not

The debate often sounds theoretical. Meanwhile, AI is already doing real work in how films get made. From early ideas to post-production: scripting support, concept design, scoring, editing assistance, voice work, and performance modification.

That matters for one simple reason. The question is no longer “Will AI arrive?”. The question is “What kind of AI use becomes normal, and under what rules?”.

If you look closely, the industry is already making that choice in small, easy-to-miss steps. The tools are frequently packaged as “features” inside software people already trust. Auto-transcription. Auto reframing for different screen formats. Tools that automatically cut out subjects from backgrounds. Tools that track motion in a shot. Noise reduction. Dialogue cleanup. Autotagging clips by faces or scenes. Call it machine learning, call it AI. The practical outcome is the same. Decisions that used to require time, specialists, or budget are getting compressed into buttons.

Which means the real question isn’t whether AI belongs in film. It’s how it gets used, and what standards come with it.

In modern media and brand storytelling, AI shifts the cost curve of production while raising the premium on taste, direction, and rights-safe workflows.

AI is a tool. What matters is how you use it

There’s a repeating pattern in creative industries.

A new tool arrives. People fear it will dilute artistry, eliminate jobs, and flood the market with mediocrity. Some jobs do change. Some workflows do get automated. Then the craft adapts, and the best creators use the tool to raise the ceiling, not lower the bar.

Sound did not kill cinema. Digital did not kill cinematography. Non-linear editing did not kill storytelling. CGI did not kill practical effects. What changed was access, speed, and the competitive baseline.

The sober takeaway is this. AI at its core is a tool. Like any tool, it amplifies intent. In the hands of someone without taste, it accelerates slop. In the hands of someone with taste, it accelerates iteration.

AI is leveling the playing field for filmmakers and creators

Here’s where the conversation gets practical.

AI lowers the cost of getting from idea to “something you can show.” It helps smaller teams and individual creators move faster. It also lets bigger studios compress timelines.

That’s the real shift. Capability is becoming less tied to budget, and more tied to taste, direction, and how well you use the tool.

Does AI help you be creative, or does it replace you?

Used well, AI helps you unlock options and enhance what you already made. It is not about creating a film from scratch. You still have to create. You still have to shoot. You still have to film. The difference is access. AI puts capabilities that used to require six-figure VFX budgets within reach, so more of your ideas can make it to the screen.

The line that matters is this: enhancement, not replacement.

The dark side. When “faster and cheaper” wins

The risk is not that AI exists. The risk is that business pressure pushes studios to use it as a shortcut.

When “cheap and fast” replaces craft, the damage shows up quickly: fewer human jobs, weaker trust, and more content that feels engineered instead of made. This is where AI stops being a creative tool and becomes a replacement strategy.

The pragmatic answer. It’s not AI or artists. It’s AI and artists

The realistic future is hybrid.

The best work will blend the organic and the digital. It will use AI to strengthen a filmmaker’s vision, not replace it. In the same way CGI can strengthen practical effects, and editing software can assemble footage but not invent the story, AI can support creation without owning authorship.

So the goal is not “pick a side.” The goal is to learn how to use the machine without losing the magic. Also to make sure the tech does not drown out the heart.

AI is here to stay. Your voice still matters

AI is not going away. Ignoring it will not make it disappear. Using it without understanding it is just as dangerous.

The creators who win are the ones who learn what it can do, what it cannot do, and where it belongs in the craft.

Because the thing that still differentiates film is not gear and not budget. It is being human.

AI can generate a scene. It cannot know why a moment hurts. It can imitate a joke. It cannot understand why you laughed. It can approximate a performance. It cannot live a life.

That’s why your voice still matters. Your perspective matters. Your humanity is the point.


A few fast answers before you act

Will AI destroy Hollywood?

It is more likely to change how work is produced and distributed than to “destroy” storytelling. The biggest shifts tend to be in speed, cost, and versioning. The hardest parts still sit in direction, taste, performance, and trust.

Where is AI already being used in film and TV workflows?

Common uses include ideation support, previs, VFX assistance, localization, trailer and promo variations, and increasingly automated tooling around editing and asset management. The impact is less “one big replacement” and more many smaller accelerations across the pipeline.

What is the real risk for creators?

The risk is not only job displacement. It is also the erosion of creative leverage if rights, compensation models, and crediting norms lag behind capability. Governance, contracts, and provenance become part of the creative stack.

What still differentiates great work if everyone has the same tools?

Clear point of view, human insight, strong craft choices, and the ability to direct a team. Tools compress execution time. They do not automatically create meaning.

What should studios, brands, and agencies do now?

Set explicit rules for data, rights, and provenance. Build repeatable workflows that protect brand and talent. Invest in directing capability and taste. Treat AI as production infrastructure, not as a substitute for creative leadership.

InVideo AI: Future of Ads, or Slop at Scale?

InVideo just dropped a campaign that might be one of the sharpest AI ads to date. Or one of the most controversial.

Not because the ad itself is “good” or “bad.” But because of what it demonstrates.

The premise is simple. A local business wants awareness and local footfall. A single prompt arrives. Then a “creative team” appears on screen. A writer, director, producer, and sound designer. They brainstorm, storyboard, pull assets, debate tone, change direction midstream, swap narrators, land a punchline, and ship a finished promo.

The twist is that the “team” is not human. It is AI agents collaborating in real time.

Some people will see this and think: finally, creativity at the speed of thought. Others will see it and think: here comes manufactured content. At industrial scale.

So let’s unpack what’s actually happening here. Not the hype. Not the fear. The shift.

What this campaign is really showing

On the surface, it’s a product story.

Under the surface, it’s a proof-of-concept for a new production model. Prompt-to-video, orchestrated by role-based agents, pulling from your assets, and iterating like a team would.

That matters because we are crossing a line:

  • Yesterday: AI helped you edit.
  • Today: AI can generate components.
  • Now: AI attempts to run the full production loop. Brief to concept to execution to polish.

If that sounds incremental, it isn’t. The bottleneck in content has never been “ideas.” It has been translation. Turning intent into something shippable, on brand, on time, and fit for a channel.

This is what changes. The translation cost collapses.

The “agents” idea. Why it clicks so hard

Most AI video tooling gets described as features: text-to-video, voiceover, stock replacement, templates.

Agents are a different mental model. They mimic how work gets done.

Instead of one tool trying to be everything, you have multiple role-based systems that divide the labor:

  • Writer: Hook, script, narrative beats
  • Director: Framing, pacing, scene intent
  • Producer: Assets, structure, feasibility, assembly
  • Sound designer: Voice, music cues, timing, emphasis

The output is not just “a video.” It’s a workflow that looks like collaboration.

And that’s why the campaign is sticky. It doesn’t just show a capability. It shows an operating model.

Fast definition. What “AI agents” means in this context

AI agents are role-based AI workers that take responsibility for a portion of the task, coordinate with other roles, and iteratively refine toward a shared goal.

In practical terms, this is orchestration. Task decomposition. Decision loops. And multi-step iteration that feels closer to a real production process than a single prompt and a single output.

In enterprise marketing teams, agentic video tools compress production time while making governance, briefing quality, and brand standards the real constraints.

Why the bakery storyline matters. It’s not about video

The reason this lands is the bakery.

A small business is a stand-in for every team that has historically been excluded from “premium” creative production. Not because they lacked ideas, but because they lacked:

  • Budget
  • Time
  • Specialist talent
  • Access to production infrastructure

If AI production becomes cheap and fast, a new baseline emerges.

Customer expectations tend to move in one direction. Up.

In other industries we’ve seen this pattern repeatedly:

  • Shipping went from weeks to days. Then days to “why isn’t it here tomorrow?”
  • Support went from office hours to 24/7 chat.
  • Information went from gatekept to instant.

Content is heading the same way.

When a local business can generate credible, channel-ready creative quickly, the competitive advantage shifts away from “who can produce” and toward “who can differentiate.”

So is this the future of content. Or a shortcut that kills creativity?

Both outcomes are plausible, because the tool is not the strategy.

Here are the three trajectories I think matter.

1) Creativity gets unlocked for more people

AI reduces the friction between an idea and a first draft. That can empower founders, small teams, educators, non-profits, internal comms teams, and marketers who have always had the brief but not the bandwidth.

If you’ve ever had a good concept die in a doc because production was too heavy, you know how big this is.

The upside version of the future looks like:

  • More experimentation
  • More niche creativity
  • More localized storytelling
  • Faster learning cycles

2) The internet floods with “content wallpaper”

When production becomes cheap, volume spikes. When volume spikes, attention gets harder. When attention gets harder, teams chase what performs. When teams chase what performs, sameness creeps in.

The downside version of the future looks like:

  • Infinite mediocre ads
  • Homogenized pacing and tone
  • Interchangeable visual language
  • “Good enough” content dominating feeds

That’s the fear behind “slop at scale.” Not that content exists. That it becomes meaningless.

3) Premium creative becomes more premium

There is a third outcome that’s often missed.

When baseline production becomes abundant, true differentiation becomes rarer.

Human advantages do not disappear. They concentrate around the things AI struggles with reliably:

  • Strategy and intent. What are we trying to change in the market?
  • Cultural nuance. What does this mean here, with these people?
  • Original point of view. What do we stand for that others don’t?
  • Brand taste. What is “on brand” beyond templates?
  • Ethical judgment. What should we not do even if we can?
  • Lived insight. What’s the human truth behind the message?

In that world, AI does not replace creative leaders. It raises the bar on them.

The practical question every marketing leader needs to answer

People debate whether AI can “replace creatives.” That’s not the operational question.

The operational question is: Where do you want humans to be irreplaceable, and where do you want machines to be fast?

Because if AI handles production, your competitive edge moves to:

  • The quality of your briefs
  • The clarity of your brand system
  • The strength of your POV
  • The governance of your outputs
  • The measurement of creative impact
  • The speed of iteration without brand drift

A simple maturity test you can run this week

If AI can produce at scale, the risk is not “bad videos.” It’s unmanaged systems.

Ask this:

Who owns the continuous loop of prompting, testing, learning, scaling, and deprecating AI-driven creative workflows in your organization?

If the answer is “no one,” you don’t have an AI capability. You have scattered experiments.

My take

Production is getting cheaper. Differentiation is getting harder.

So the real decision is not whether you can generate more content. It’s whether you can scale output without losing taste, brand truth, and accountability.

Is this the future of content. Or a shortcut that kills creativity? It depends on who owns the brief, who owns the guardrails, and who is willing to say no.


A few fast answers before you act

Can AI agents replace a creative team?

AI agents can replicate parts of the production workflow and speed up iteration. They do not automatically replace strategy, taste, or cultural judgment. Those still require accountable humans.

What does “prompt-to-video” actually mean?

Prompt-to-video is the ability to turn a single idea into a finished video. Script, scenes, voice, music, edit, and formatting. Without traditional filming or manual timeline editing.

Will this create more generic ads?

It can, especially when teams optimize for speed over differentiation. The antidote is strong briefs, clear brand constraints, and human ownership of taste and intent.

Mirakl Santa Quits

A Christmas campaign built with generative AI

Mirakl, the ecommerce software and marketplace platform provider, has launched a global Christmas campaign built around a 60-second brand film titled “Santa Quits”. The creative twist is not the plot. It is the production method. The film was created with AiCandy Australia, with every character and scene generated via AI, then shaped into a finished narrative through human creative direction and filmmaking craft.

The story. Santa resigns. The world panics. An elf restarts operations

In the film, Santa resigns under modern seasonal pressure, triggering worldwide protests as people demand Christmas be saved. The resolution is deliberately on-theme. An elf restarts the operation using “agentic commerce” powered by Mirakl Nexus, restoring gift delivery in time for Christmas Eve.

Why a #B2B brand film is suddenly the sharpest product demo

This is the part that matters for marketers. Mirakl is using AI to tell a story about AI-powered commerce. The plot is a metaphor for the underlying message. When expectations become impossible, legacy operations break. You need infrastructure designed for the age of AI agents, not just more people and more dashboards.

That is also why the film lands beyond the seasonal punchline. It frames “agentic commerce” as an operating model, not a feature. In a world where agents search, compare, and transact on behalf of customers, brands need systems that keep product data, availability, pricing, and promises coherent at scale.

The production lesson. AI does not replace craft. It changes the economics of craft

AiCandy’s claim is not that AI makes creativity optional. It is that AI filmmaking can deliver cinematic work faster and on tighter budgets, as long as human direction stays in charge of narrative, tone, and finishing. Mirakl, in parallel, positions the campaign as a proof point that it understands the AI shift in commerce deeply enough to build for it, and market it, at the same time.

The takeaway. Do not copy the gimmick. Copy the system

If you are tempted to reduce this to “AI-made ad”, you miss the strategic move. The film works because it connects three things into one coherent story:

  • A familiar cultural moment (Christmas pressure).
  • A clear operational failure mode (the system cannot scale).
  • A product truth (agentic commerce needs infrastructure).

That is the blueprint worth stealing. Make your narrative demonstrate the future you are selling. Then make the medium reinforce the message.


A few fast answers before you act

What is “Mirakl Santa Quits”?

“Santa Quits” is a Mirakl global Christmas campaign built around a 60-second brand film. Mirakl positions it as a story about modern commerce pressure and how agentic commerce can restore operations at scale.

Who created the film and how was it produced?

The film was created by AiCandy Australia. Mirakl states that every character and scene was produced via generative AI, then shaped into a finished narrative through human creative direction and filmmaking craft.

What does “agentic commerce” mean in this context?

In this story, agentic commerce refers to software-driven agents that can execute commerce operations with a degree of autonomy, such as coordinating tasks and workflows to restart and run delivery operations. In the film’s narrative, an elf uses agentic commerce powered by Mirakl Nexus to restore gift delivery.

Why is this campaign notable for marketers?

Mirakl intentionally uses AI to tell a story about AI-powered commerce, aligning message and medium. It is also a concrete example of generative AI being used for a brand film, paired with human creative direction, to reach a cinematic outcome under real constraints.

What’s the real business point behind the “Santa Quits” story?

The plot frames seasonal demand as an operational stress test. The resolution suggests that automation and agentic systems can restart and scale commerce operations quickly, restoring reliability when timelines are non-negotiable.

Does this prove generative AI can replace human filmmaking?

No. The campaign itself argues for a hybrid model. Generative AI produces characters and scenes, while human creative direction and filmmaking craft shape the final narrative and quality. The value is speed and efficiency with maintained editorial control.

What is a practical way to apply this idea without making “AI theatre”?

Start with one high-frequency content format and define clear quality criteria and approval checkpoints. Then measure cycle-time, cost, and consistency. If you cannot show repeatable outcomes, you are experimenting, not building a scalable capability.