THE WHOLE AI CATALOG FOR TV AND FILM WRITERS, PRODUCERS AND EXECUTIVES

The Go-To collection of everything AI that will help you do your job better.

THIS IS FOR YOU, IF…

If you’re a writer, producer, or executive working in film and TV, AI is already reshaping your industry—whether you’re ready or not. This post is your comprehensive, plain-English guide to the best AI tools for every stage of the creative process, from brainstorming and scripting to pitching, budgeting, production, and post. It includes use cases, pitfalls, and opportunities you won’t find in most reviews. Bookmark it, share it, and come back often—because this list will only keep growing.

I’m a bit of a broken record on this point: AI software for media is being built by people who understand software language. Software language was designed to tell computers what to do. Human language has been designed over thousands of years to communicate what it is to think, feel and know.

They are NOT the same. Writing code is not writing language.

Only by engaging with the software and giving feedback to engineers will we end up with AI software that serves our goals. If we don’t engage, we’ll get AI software that just tells us what has been thought, felt and known in the past.

Let’s roll up our sleeves and dig in. I’m going to discuss more than 30 pieces of innovative software you can use today.

This is a LONG post. Your email app might cut it short. Head to Substack.com OR the Substack app to read the whole thing.

I’ll keep this practical and clear. Whether you’re a seasoned pro or just curious, you’ll get a quick lay of the land on where AI fits into Hollywood’s creative process. Feel free to skip ahead to your section.

Finally, I’m not here to review or criticize! I’ll be reviewing a lot of these tools in the coming weeks and months. This is your baseline.

THIS IS A LONG POST. Your email app might cut it off. Head to Substack (or the app) to read the whole thing. Each role in the process has a lengthy section that breaks down the tools you need to know about.

That said — I didn’t want to litter the post with comment buttons. There’s one here… and one at the end (with a question for you). AND… I’m SURE I’m missing things. PLEASE let me know, and I’ll add to this list.

If you know a writer, producer, dev exec or senior exec who needs to see this list, please share it.

Finally… if someone shared this with you, subscribe to help define the future of AI in Entertainment.

THE PROMISE OF AI: A COMMON LANGUAGE

The more I dig into the tools of AI, the more I’m convinced that these tools, in total, offer an opportunity to fix the oldest problem in show business: We don’t all speak the same language! Even when we’re using the same words, very often we’re all thinking something different.

Take a word as simple as “Audience.”

• For a writer, it might be actual faces in the seats. I know writers who hear a laugh, gasp, moan. When you’re writing, there’s an “audience” in your head and your gut. (The author Robert Graves famously called this “The readers over your shoulder.”)

• For a producer, the audience might mean the people to whom they hope to sell the project. Or it might be the larger market for the project. Less “faces in the crowd” and more “butts in the seats.”

• For a development executive, the audience might just mean the people in their company who will hopefully fund the project. Or it might mean audience segments and demographics. The best development execs also share the writer’s ability to “imagine” the faces of their audience.

• For executives, audiences are a key element in a larger business plan. If we’re talking about TV, the audience is on one side of a platform designed to connect content to advertisers or subscriber fees. For filmmakers, there might be a larger audience strategy tied to multiple releases of product.

Using AI as a tool can unite everyone in the same understanding of the language we’re using. Let’s say you’re a writer who decides to create an audience segment using AI. You feed your story and script into the segments (maybe even creating a “focus group” of consumers with AI). Using the response of your AI research, you can enter into establish a common ground for talking with producers and executives.

Everyone can start talking the same language. They can even use the same tools. For that one reason alone, AI will become invaluable to the entertainment industry.

THERE’S REALLY ONLY ONE QUESTION:

💡 “Does this tool help me get closer to the idea in my head?”

That’s it. Every bit of AI we use should either help us turn the idea in our heads into media. It should save us time and energy. It shouldn’t “get in the way.” And… maybe… it might help us make the idea better.

WRITERS

Personal bias: I began as a writer. I am still a writer at heart.

Most projects begin with a writer’s idea and vision. (Even if someone brings an idea to a writer, if the writer is worth anything, they will make it their own.)

Writing is a long and lonely slog. There’s research, outlining, rough drafts, first draft, draft after draft. There are dead ends, then wide open spaces. It’s a constant conversation with yourself.

AI can make writing less lonely and isolating. I created a “writers’ room” from Claude, ChatGPT and NotebookLM. (I’ll outline and demo that in a week or so.)

Thanks to my writers’ room, some of my days are spent on my own and other days are spent conversing with AI: brainstorming, asking for research, testing out ideas in my “room.”

The result, for me, is that I spend more time writing, and I write more confidently and quickly.

Finally, it’s worth noting: Writers have been a bit wary of AI. Headlines during the 2023 Hollywood writers’ strike screamed about AI replacing creatives, and indeed 60% of entertainment writers/actors said they worry AI will put their jobs at risk .

The approach now is generally augment, not replace. Today’s writers are cautiously testing AI as a tool – using it to beat the blank page or speed up grunt work – while ensuring that the human creative spark stays front and center.

Brainstorming & Concept:

AI built-in?

AI-native platforms like Sudowrite and NovelCrafter are designed specifically to help writers generate entire stories from prompts.

• Sudowrite can help you outline, expand scenes, rewrite text, and even generate full chapters. It offers “Story Engine” features where you input key characters, settings, and themes, and it helps construct scenes and plot arcs.

• NovelCrafter (less focused on screenwriting but used for story development) lets you prompt AI to write entire passages, brainstorm character arcs, and organize large projects chapter by chapter.

• These tools are developed for narrative generation, like novels or treatments, but they can be creatively repurposed by screenwriters for developing backstory, worldbuilding, or even dialogue ideas. Writers use these to kickstart drafts or break through creative blocks.

You can also go straight to the source. Writers can set up projects in Claude, ChatGPT, Gemini, NotebookLM. The project can contain many drafts, lots of notes, half-baked ideas, character breakdowns, etc. etc. AI will “remember” what you’ve talked about, uploaded. You can throw out half-baked ideas (even the act of typing it out one more time will help you see them anew). Even if you hate what Claude or ChatGPT comes back with — you’re discovering what YOU want it to be.

Pitfalls

• AI can really be overly encouraging. I compared Claude to “Kimmy Schmidt with a Computer Science Degree.” Sudowrite’s UI makes you feel like you’re making progress when you might not be. As Ernest Hemingway said, writers need a fool-proof “shit detector.” Even with AI.

• AI is trained on old ideas. Yes, we all “stand on the shoulders of giants”, accessing the great films in our heads. AI has seen every film and read every available script (AND OWES US MONEY… more about that later.) That said, it will do what’s been done before. Not that we haven’t all been asked to do that, time and again.

• AI is sometimes wrong. I’ll write about prompting later. For now, if you’re looking at something that’s “hinky”, just ask AI to rethink it. “Give me a second level response” works great.

Opportunities

These platforms can act like a “first draft machines” – generating a rough version of a scene or concept that the writer can then revise and refine. While they won’t produce a polished screenplay, they’re incredibly helpful for quickly prototyping story ideas or exploring different plot directions. Many writers treat them as brainstorming partners, not replacements, but the speed at which they can produce usable text is a serious advantage for time-crunched creatives.

Drafting the Script & Formatting:

Tools

Final Draft is the industry standard, known for automatic formatting and helpful tools (it remembers character names and scene locations as you type, etc.). Alternatives like Movie Magic Screenwriter, Celtx (cloud-based), WriterDuet, or Arc Studio all help writers focus on writing while the software handles margins and font.

AI built-in?

Mostly no. Final Draft and its peers primarily focus on formatting and collaboration, not AI story generation . They might have simple auto-complete (Final Draft’s “SmartType” just recalls frequently used names/terms) but they’re not “writing” for you. AI-powered writing is still largely done via external apps or plugins. (Notably, a tool called ScriptReader.ai is designed to analyze scripts with AI, but it’s more for feedback than writing .)

Opportunities

There’s big potential for LLM integration here. Imagine a screenwriting app where you hit a button and an AI suggests alternative dialogue based on what you’ve written so far, perhaps rephrasing a clunky line more elegantly. Already, some writers copy-paste scenes into ChatGPT to punch up the dialogue or fix grammar.

To come: We’ll be debating whether AI can have a sense of humor. Frankly, ChatGPT and Claude have both made me laugh, although often not intentionally.

AI could also help with tedious tasks like maintaining a consistent tone or even translating a script to another language for a global audience (AI can assist with script translation and localization too ). In short, the writer writes, but an AI “co-writer” could be on standby for quick suggestions and edits – like an assistant who never gets tired.

Revising & Editing :

Tools

Many still use the same screenwriting software for revisions (with features like track changes or notes). They might also rely on human feedback – writer’s groups, or professional script consultants who provide notes.

There are some AI-driven script analysis tools like ScriptBook, Scry, or ScriptReader.ai that can generate reports on a script’s elements (e.g. “Does this story hit the expected emotional arc for a thriller?”) . Studios and some writers have experimented with these to see if a script is likely to be a hit or needs changes.

AI built-in

The main writing programs don’t have built-in script gurus – they won’t tell you “Act Two is dragging”. But those separate AI script analysis tools do use AI models to evaluate a script’s structure and even predict market success . They aren’t widespread in daily use by writers (feedback from a trusted human or one’s own intuition is still king), but they show what’s possible.

Opportunities

This is a ripe area for AI assistance. For example, an LLM like ChatGPT can act as an instant script reader: a writer could ask, “Hey ChatGPT, what do you think the theme of this script is?” and see if the AI picks up what the writer intended. It can catch if a character’s voice is inconsistent or if there are plot holes, by literally asking the script questions. This kind of AI feedback isn’t a replacement for a human reader (it lacks true understanding and taste), but it’s a fast way to spot obvious issues before the writer hands the script to their producer.

Many writers also use grammar and style-checkers (like Grammarly) – that’s AI in a basic form, catching spelling or suggesting clearer phrasing. In the future, we might see an all-in-one writing app that, at the click of a button, gives you a constructive critique of your draft, almost like having an assistant or editor built into the software.

PRODUCERS

A producer will know that it’s essential to the story to have an elephant standing in the middle of 49th street in NYC at the break of dawn as the “host” stands beside it, LIVE, on national TV.

A producer will stand by as the stage manager will begin counting down… “10…9…8…”

A producer will watch as the elephant takes a massive dump next to the host. They will know that this massive dump is about to be seen by the entire nation.

A producer will walk in, pick up the poop — which the producer KNOWS is held together by the massive amounts of hay that the elephant eats — and walk away… “… And we’re live.”

Years later, that producer — Charlie Andrews, the first producer of the Today Show in the 50s — will tell me that story, ending with:

“…and THAT is what a producer does!”

So the question is… Aside from picking up the poop (which I know robots will be doing some day), how does AI help a producer do their job?

For now, we’ll focus on production. Producers also help craft The Pitch and make the tough decisions about whether to support a project in the first place. We’ll talk about those later.

Tools

Producers lean heavily on project management and budgeting software. Movie Magic Budgeting is a long-time staple for breaking down scripts and estimating costs. For scheduling, tools like Movie Magic Scheduling, StudioBinder, or even general platforms like Smartsheet and Excel are common.

These let producers create detailed “production calendars” (what gets shot when, with which actors and crew). There are also specialized apps for call sheets and crew coordination (StudioBinder doubles as a call sheet manager, for instance).

In recent years, AI-powered tools have emerged: Filmustage, for example, can automatically break down a script into a list of scenes, characters, props, and locations using AI – something that used to require hours of a producer or assistant’s time.

Rivet AI and Saturation.io apply AI to budgeting, helping forecast and optimize where money is spent . These tools read through the script and help generate a first-pass budget or schedule, which the producer can then adjust.

AI built-in?

Traditional budgeting and scheduling programs themselves haven’t historically had AI; they’re powerful calculators and organizers, but the producer had to input all the data.

Now, tools like Filmustage are explicitly AI-driven – they scan the script text and identify elements (e.g., “Scene 5: needs 50 extras and a rain machine”) automatically. This is a big jump in efficiency.

Pitfalls

• Errors! Many producers cross-check the AI’s output, as nuance can be lost. The popular tools (Movie Magic, etc.) are starting to explore AI features, but it’s early. So currently, a producer might use a combination: e.g. run a script through Filmustage to get an initial breakdown, then import that into Movie Magic Scheduling to fine-tune the shooting schedule.

Opportunities

We’re heading toward smarter “producer’s assistants.” An AI could feasibly take a script and not only break it down, but also compare it to a database of past productions to warn, “That car chase scene is going to need extra stunt budget”.

ChatGPT or Claude could even be used in a hack-y way today: A producer could paste in a scene description and ask, “What logistics should I consider for filming this?” The AI might respond with helpful pointers (“night shoot will require extra lighting; consider stunt doubles for the fight”).

In the near future, expect more integration – e.g. an AI that automatically generates multiple schedule options (“Option A finishes 5 days faster but requires two units shooting in parallel – here are the cost implications”) which the producer can then evaluate. This kind of scenario planning is a perfect job for AI, crunching numbers and options quickly.

Team Coordination & Casting

Tools

Email and phone are STILL the leaders here. Modern producers use collaboration software: Slack or Microsoft Teams for team communication, Google Drive for sharing schedules and scripts, etc.

For casting, there are databases like Breakdown Services or Casting Networks where casting calls are posted and talent is searched. Some newer casting platforms like Casting Frontier use algorithms to help match actors to roles based on profiles.

Casting Droid, an AI-driven casting tool, can even scan through actor databases and suggest actors that fit a character description, taking into account things like their past roles, look, and even performance style .

AI built-in?

Traditional casting is very human-driven (and relationship-driven – agents pitching their clients, etc.). However, tools like Casting Frontier and Casting Droid show early AI usage: the software might say “these 10 actors have played similar roles and might be a good fit” . It’s like a recommendation engine for actors. Still, final decisions involve auditions and human judgment. For team coordination, most chat or project management apps don’t use AI in any significant way yet (aside from maybe an AI transcription for meetings or smart scheduling assistants).

Pitfalls

• Creators today have learned that AI scans text, images, and videos using very different settings than traditional SEO. I imagine that actors, writers, technicians and crew members will discover that their qualifications are being scanned by AI. They’ll adjust their bios, headshots, resumes, etc. to fit that. The problem is the same problem we’re discussing over and over: The people building the software don’t completely understand what humans need. Casting directors and producers have a wealth of knowledge about what they need — we need them to be part of the development of this software.

Opportunities

AI could supercharge casting searches. Think of an AI that you could feed a character bio (“late 30s, comedic timing, action experience, big on TikTok”) and it scours talent databases and social media to find emerging actors who match, including those a producer might not have known. It could even generate a “shortlist” video by pulling clips of those actors in past roles for a quick preview.

For team coordination, AI assistants could handle routine updates – for example, auto-generating a daily report: “5 of 8 scenes filmed today, we are 30 minutes behind schedule, tomorrow’s weather looks clear.”

In fact, producers have started using AI in daily production reports and data crunching: one study found 85% of producers have used some form of AI in their projects, primarily in pre-production planning and editing . This suggests that producers are finding value in these tools to save time and keep everyone informed.

On-Set Problem Solving & Production Management:

Tools

On set, information is king. Producers use daily call sheets (usually PDFs generated by tools like StudioBinder or Gorilla Scheduling) to track what’s happening each day.

They might use real-time dashboards if available – some production management software can show, for example, how many scenes are done versus how many are left. Good old spreadsheets often fill gaps. Walkie-talkies (”Go for Stephen!”) and messaging apps keep communication instant.

There’s also increasing use of tech like video village iPads where producers can watch live camera feeds and note any issues. Advanced productions employ smart cameras and sensors; for example, cameras that auto-track actors or drones that self-stabilize – these involve AI under the hood (facial recognition, object tracking) and help get shots faster .

AI built-in?

In the thick of production, AI is present but behind the scenes. For instance, some camera systems now have AI that can adjust settings on the fly for optimal exposure or focus on the main subject automatically – which can save retakes. Motion capture suits might use AI to render digital characters in real time for the director to review .

However, the tools a producer personally uses day-to-day (schedules, budgets, communications) typically don’t have AI actively assisting. The decision-making and troubleshooting – “do we move that scene to tomorrow because it’s raining?” – is still largely human.

Opportunities

This is an area where AI could act like a real-time analyst. Picture an AI that monitors the production: it knows the schedule, it gets live info from the camera takes, it’s aware of weather forecasts and maybe even the mood (via sentiment analysis of crew feedback). It could then alert the producer, “We won’t make our day unless we pick up the pace – consider cutting Scene 7 or moving it to tomorrow when an extra camera is available.” This kind of insight would come from crunching lots of data (past production performance, etc.), something AI is great at. We’re not quite there yet, but pieces exist.

For example, if you feed an AI the script and the current progress, it could predict if you’re on track or if certain scenes historically tend to cause delays (night scenes, stunts, etc.). Also, AI could help with risk management: flagging that a particular set piece is high-risk (maybe based on insurance claim data from similar projects) and recommending contingency plans. These ideas are just rolling out, but they could significantly reduce costly overruns.

Post-Production & Marketing Prep

After filming, producers oversee editing, visual effects, music, and eventually marketing/distribution plans. They liaise with editors and VFX supervisors and ensure the final product matches the vision (and stays on budget). They might also coordinate test screenings and tweak the film based on audience feedback.

Tools

Editing software (Adobe Premiere Pro, Avid Media Composer, DaVinci Resolve) is used by editors, but producers review cuts through tools like Frame.io (for giving edit feedback remotely) or just by attending edit sessions. For tracking post-production tasks (like VFX shots or music licensing), producers might use spreadsheets or project management tools. On the marketing side, producers often work with marketing teams who use their own analytics tools (social media analytics, test screening surveys via platforms like Qualtrics, etc.).

It seems like every day I see new AI features for editing. Recently, Edgar was launched: It does the “first pass / rough edit” from hundreds of hours of footage on its own. (The pitch is: “While you sleep.” Which is tempting but also… weird?

AI built-in?

Editing tools increasingly have AI features. Adobe’s Premiere Pro, for example, has AI-driven editing aids – like automatically reformatting a widescreen trailer into a vertical Instagram video, or using AI to cut out silences and tighten up interviews .

DaVinci Resolve has AI for things like instant color matching between shots . These help post-production move faster.

For producers, an interesting AI use is in quality control: tools like Interra Systems’ AI can scan a video for technical errors (glitches, out-of-sync audio) and fix them – ensuring the final export is broadcast-ready.

When it comes to marketing, AIs are used for tasks like analyzing trailer engagement or even editing trailer drafts (there are AI trailer editors that suggest which scenes to include based on excitement or sentiment).

Still, many of these aren’t fully integrated into a producer’s everyday dashboard – they’re specialized tools used by the post or marketing teams, with the producer overseeing.

Opportunities

AI can assist producers in making sense of audience feedback. For instance, after a test screening, there might be hundreds of comment cards or survey responses. AI sentiment analysis can quickly summarize that: “80% of viewers loved the lead character, but many found the ending confusing” . That helps the producer and director decide if re-edits or reshoots are needed.

AI could also help in distribution decisions – for example, analyzing market data to suggest, “This film might perform better on streaming than a limited theatrical release,” based on comparable titles.

While final decisions include gut feeling and conversations with distributors, having that data-driven angle (courtesy of AI) is increasingly valuable. It’s no wonder that 73% of studio executives and producers see AI as a worthwhile investment for growth , eyeing its potential in everything from cutting costs to predicting audiences.

In short, while the creative side of post-production remains human-led, AI can handle a lot of the number-crunching and repetitive tweaking, freeing producers to focus on the big picture.

THE PITCH

It’s all coming together here, RIGHT NOW.

Currently, AI is being widely used by writers, producers and development executives to visualize the pitch. This seems to be the area where AI has made the greatest headway. (Which leads me to think we’re just one step away from writers and producers creating content and selling it directly to consumers, rather than pitching for funding from some media company.)

Tools like Midjourney, Runway and others have revolutionized this process, enabling the creation of compelling visual pitches that bring concepts to life with unprecedented ease and creativity.

Midjourney and Runway

Using natural language, writers and producers can create detailed images and videos that capture the essence of their projects. They can walk in with vivid concept art, mood boards, and scene visualizations that effectively communicate their ideas.

Runway’s generative AI systems, such as Gen-1 and Gen-2, enable users to synthesize new videos by applying the composition and style of an image or text prompt to the structure of source footage.

This allows for the creation of dynamic video content that can serve as teasers, trailers, or animated storyboards, enhancing the persuasiveness of a pitch.

Filmmakers have employed Runway to create AI-generated short films, demonstrating the potential of their concepts in a visually engaging manner.

Dream Machine by Luma AI

Launched in 2024, Dream Machine is an advanced AI video generator that converts text prompts into realistic 10-second videos. Utilizing their proprietary AI model, Dream Machine produces clips with natural motion and accurate physics, making it accessible for creators without filmmaking expertise. Users can customize clip length, resolution, and aspect ratios. It’s currently limited to short clips with a maximum resolution of 1080p.

Sora by OpenAI

Sora enables users to create and modify short video clips (up to 20 seconds) from text prompts. Filmmakers have utilized Sora for tasks such as creating sizzle reels and previsualizations, allowing for experimentation with visual ideas. While the technology faces limitations like handling multiple characters and image quality, it holds potential for democratizing filmmaking by reducing development costs.

Movie Gen by Meta

Meta’s Movie Gen AI models can generate realistic videos up to 16 seconds long from text instructions. These models allow for personalization with specific images and sound alignment. Meta plans to offer these tools to filmmakers, artists, and influencers, with potential integration into platforms like Instagram for Reels creation and editing. Availability to users is anticipated in the near future.

Firefly Video by Adobe

Adobe’s Firefly Video is a generative AI video model that allows users to create videos using text prompts or images, specifying elements like camera angles and atmospheric effects. It integrates with Adobe’s Creative Cloud tools and aims to respect intellectual property rights, making it suitable for brands and creative professionals. Notable brands like Gatorade, IBM, and Mattel have adopted Firefly for content production.

Perhaps the biggest selling point for Firefly is that its images and video are NOT based on existing copyrighted images and video, which is why many big brands and media companies prefer Firefly for its ethical stance.

Katalist

Katalist is a storyboard AI tool designed for filmmakers, advertisers, and content creators. It enables users to create compelling storyboards and visualize ideas effortlessly, streamlining the preproduction process. By describing a story or concept, Katalist’s AI brings it to life visually, aiding in pitches and project development.

NolanAI

NolanAI offers an all-in-one suite of AI tools tailored for filmmaking and video creation. It assists in crafting pitch decks with ready-made templates, suggesting casts, and visualizing stories. NolanAI streamlines the pitching process by extracting crucial details and providing visual representations of concepts.

LTX Studio’s Pitch Deck Generator

LTX Studio provides an AI-powered pitch deck generator that aids creators in crafting detailed presentations, including storyboards, mood boards, and synopses. This tool is designed to effectively convey creative visions and engage potential investors or partners by automating and enhancing the presentation creation process.

Development Executives

Development executives stand at the intersection of art and commerce. They need a finger on the pulse of audience tastes and a keen eye for quality content. AI can feed them a firehose of insights – from audience sentiment to predictive success metrics – but one must filter that through human experience and intuition. As one entertainment study highlighted, producers and execs are far more optimistic about AI’s role than creatives, with many already using AI in their workflow.

The key is using AI to inform decisions, not make them outright. A savvy exec might use all the AI reports in the world to bolster their case, but they’ll also trust their gut when championing a project they love. In the end, AI is another tool in the toolbox – a very powerful spreadsheet and crystal ball rolled into one – but it works best in the hands of a human who knows which questions to ask it.

Development executives are the people who shepherd a project through a production or media company. They have a personal stake in the projects they back — at the proverbial “end of the day,” their value is determined by which of their projects get made and which are successful.

It’s a tough job. When I was writing and producing, the old joke was that Development Execs were actually paid to say “no” and avoid costly mistakes. That said, every Dev exec had at least one “Yeah, we turned down ‘Anora’…” on their card.

It’s a job of relationships — you want to know who’s out there, who’s creating, who they’re represented by. THEN… you have to sift through countless pitches and scripts, identify promising projects, develop those ideas with writers/producers, and ultimately build a slate of content that fits their studio or platform’s strategy. It’s equal parts creative judgment and business acumen.

Dev execs are on a constant hunt for the next great story – this could be an original screenplay, a novel to adapt, a format to remake, etc. Once they have material in hand, they evaluate its quality and potential: Is this story good? Does it fit our audience? Can it attract top talent?

Tools

The search can be as low-tech as reading piles of scripts (often as PDFs on an iPad) and scribbling notes. Most execs rely on script coverage – summary and analysis documents usually written by story analysts or assistants. They might use internal databases to track submissions and coverage (something as simple as an Excel sheet or as fancy as a custom tracking system).

To aid decisions, execs also consult data: for instance, checking past performance of similar movies (via databases like Box Office Mojo or The Numbers), or seeing what’s trending on streaming (via services like Nielsen’s streaming ratings or Luminate for online viewership stats).

Some studios have begun using AI-driven script analysis tools. An exec might run a script through ScriptBook or ScriptIQ to get a scored report predicting its audience appeal or financial prospects . And let’s not forget the old-fashioned tool: knowledge and instinct – a lot of this job is reading a script and just feeling whether it works.

AI built-in

In the evaluation phase, AI tools exist but aren’t one-size-fits-all. Many development departments still operate with humans reading scripts and writing coverage. However, the presence of AI analysis is growing. Those script analysis services are essentially AI “built-outside” tools – a script is uploaded, and the AI model (trained on a trove of screenplays and performance data) outputs feedback.

For example, the software might flag that the script’s pacing dips in the middle, or compare the story to past hits to project box office results. Some execs use these as a supplement to human coverage.

There are also AI systems that analyze audience data (from social media, etc.) to predict if a concept will excite the public . But as of now, there’s no integrated AI in a dev exec’s everyday script reader app – it’s more piecemeal. The exec’s email and Microsoft Word (for notes) don’t have AI whispering which script to pick – not yet.

Pitfalls:

• AI doesn’t know “the lingo.” (As we used to say.) SO… that sci-fi western that it recommends passing on? It’s Star Wars.

• AI doesn’t know people. I don’t know of any AI software that understands the “provenance” of writers and producers. Development execs and producers can recognize talent by career path — who you’ve worked with, what you did (even if it failed), and how you think. There’s nothing close to that now.

Opportunities:

Here’s where an AI like ChatGPT or Claude could act as a script assistant. Imagine an exec has 50 scripts to get through (not uncommon). They could use an AI to generate quick summaries of each script: “Give me a one-page summary and highlight potential red flags.” This isn’t hypothetical – people are already doing this with LLMs. It helps triage material: maybe 30 scripts can be eliminated based on the summary, allowing the exec to focus on the most promising 20.

This doesn’t replace reading the script. Beware passing on that sci-fi western.

Another use: ask the AI, “What movies or shows is this script similar to?” If it says, “This story has a vibe like Stranger Things meets E.T.,” that gives a ballpark of tone and audience.

Of course, AI won’t replace the nuanced judgment. Still, AI can streamline the grunt work: summarizing scripts, extracting character lists, even checking for things like Bechdel Test pass/fail.

By catching obvious issues (say the AI notes “there are 5 separate flashback sequences, which is unusual”), it allows the development team to ask the writer targeted questions. It’s like having a junior assistant who reads incredibly fast (but maybe doesn’t understand subtext well – so you still double-check its conclusions).

Market and Audience Analysis:

Tools

Data, data, data. Execs use reports from companies like Nielsen (for TV ratings and streaming numbers) and Comscore (for box office trends). They subscribe to newsletters or analytics platforms (e.g., Parrot Analytics for streaming demand, or The Ankler’s data insights). There’s also internal research: studios have teams that conduct surveys or build models. For instance, they might look at social media hashtags to gauge fan excitement for a genre – a form of social listening. Gracenote and Luminate are tools that provide audience preference data and content trend analysis, which some execs use to inform decisions.

In short, an exec often has a dashboard of key metrics: recent box office numbers, streaming top 10 trends, demographic breakdowns of who’s watching what. Increasingly, there are predictive analytics platforms (like the startup Cinelytic made headlines for offering AI-driven film forecasting) that attempt to simulate a film’s revenue based on genre, cast, release date, etc.

AI built-in?

A lot of this analysis is exactly where AI shines – and indeed studios and streamers use AI-powered recommendation algorithms and analytics on the audience side. (Netflix, for example, famously uses AI to recommend content and even to decide which content to produce, based on viewing patterns.)

But on the development exec’s personal toolkit, you might be surprised: it can still be quite manual. They might get a PowerPoint from the research team, or an Excel sheet of numbers. Some forward-thinking execs do use AI models to predict audience interest – e.g., feeding a logline into a model to see predicted appeal scores. But these models are typically proprietary or experimental.

One study noted that producers and execs are much more open to AI than creators are – 73% of producers/studio execs said AI would be a worthwhile investment for growth – so the intent to use AI for market forecasting is there. Implementation is catching up.

Opportunities

Here, an AI like ChatGPT can act as a super research assistant. An exec could ask: “What were the global box office trends for horror films in the last 5 years?” or “Summarize how teen dramas have performed on streaming vs theaters.” If connected to the right data, the AI could spit out a quick analysis. Even without direct data access, an AI can help make sense of reports. For example, paste in a dense Nielsen report and ask for the key takeaways – voila, instant summary.

Another angle is scenario modeling: using AI to ask, “If we made a movie with X star for Y budget, releasing in October, what does the model think the ROI would be?” Some tools do this already, but an accessible AI interface could make it much more user-friendly. There’s also room for AI in spotting emerging trends. It could analyze millions of social media posts and tell an exec, “Interest in vampire shows is spiking among 18-24 year-olds this quarter.”

That kind of insight could directly influence development priorities (maybe dust off that vampire script). Essentially, AI can process far more data than any human, and present a digestible insight – which is gold for an exec trying to stay ahead of the curve. (Of course, it’s then up to the human exec to decide if that vampire trend is a fad or the next big thing – judgment still required!)

Creative Development & Notes:

Tools

Mainly, documents and meetings are the leading tools. Execs write notes in Word or Google Docs, track script drafts (often via email threads or a document management system), and have lots of meetings/calls with writers and producers to discuss changes. Some use annotation tools (like PDF annotators) to mark up scripts directly.

A few companies have story development software that multiple stakeholders can log into – but those are more like shared repositories than AI-driven tools. Since development can span months or years, keeping track of versions and feedback is itself a task – version control software or even just careful use of filenames (Draft_v7_final_FINAL2.docx, anyone?) are the norm.

AI built-in

AI hasn’t been widely embedded in the process yet. There’s potential (imagine an AI that could compare two script drafts and highlight exactly what changed – saving an exec time), but traditionally it’s been a manual read-and-note exercise.

An exec could use AI in unofficial ways: for instance, use ChatGPT to rephrase a note politely (“How do I tell the writer to trim the dialogue without offending them?”) – a bit of a soft skill hack.

Or use AI to check consistency: e.g., have the AI read the script and verify a character’s eye color didn’t magically change (continuity errors). These uses aren’t industry standard, but they’re possible with current tech.

I’ve gone deeper into the “consistency” thing… I will send descriptions of several scenes featuring the same character and ask AI to tell me what emotional changes the character is going through. If AI doesn’t “get” what I’m trying to do, I need to check that the audience will.

Opportunities

An intriguing use of AI here is as a script consultant. We touched on AI giving writers feedback; similarly, an exec could use AI to double-check their own notes. For example, if an exec feels the second act is slow, they could ask the AI, “Is the pacing slow in the middle of this script? Why or why not?” If the AI independently points out a similar issue (say, “Two lengthy dialogue scenes in a row reduce momentum”), it validates the note.

AI could also help generate alternatives: “The ending isn’t working – AI, can you suggest 3 alternate endings for this story?” Those ideas might be off-the-wall, but they could inspire the team to find a better solution.

Another area is IP mining: development execs often have to find intellectual property (books, comics, etc.) to adapt. An AI could quickly read through hundreds of short stories and flag those with themes or plots that match what the studio is looking for. Instead of relying purely on what agents submit, an exec armed with AI could proactively discover gems. This is like having a researcher who’s read everything on the internet and can say, “You want a heartwarming holiday story with a twist? Here are two published short stories from the 1980s that got great reader responses and could be adapted.” It’s a new way to tackle an old task – leveraging AI’s encyclopedic memory.

(AND YES… I’ll say it again… AI COMPANIES NEED TO PAY THE CREATORS OF THE WORK THEY’VE USED TO TRAIN THEIR AI!!)

SENIOR EXECUTIVES

All of the tools outlined above are available to senior executives. But … there really is no tool for executives that helps them do their main job:

💡 Executives determine and guide the culture of their companies.

I was involved with MTV Networks, in various capacities (including as an executive) from the 80s through the 2000s. The executives that started MTV and then guided it through those 30 years or so succeeded because they built a culture of experimentation, innovation, excitement and… yes, FUN.

They worked with state-of-the-art marketng research. They juggled multiple stakeholders (Cable owners, advertisers). Most of all, they loved their audience.

Aside from “love,” AI can help your teams do their jobs better. All you need to do is:

Don’t. Say. No.

Create a culture that embraces experimenting with AI.

Say “Yes, let’s try that.” The AI you’re looking at is the worst AI you’ll ever see — it’s only going to get better. The people in your company who want to make their jobs better by using AI are doing it for their careers and for you. Respect them, listen to them, create a culture that rewards experimentation and … FUN!

Be prepared for failure but, in the long run, be prepared for everything to change.

Conclusion: Bringing It All Together

Across writers, producers, and development executives, we see that current tools range from old faithful software to cutting-edge AI assistants. Some existing tools have started to bake in AI (like editing software doing auto-color correction, or script analyzers offering feedback), but many workflows are still waiting for that AI boost.

There are clear gaps and inefficiencies – writers slogging through rewrites that an AI could help outline, producers manually updating schedules that an AI could adjust in seconds, execs drowning in data that an AI could summarize.

The good news is that Hollywood is not shying away from experimenting. We’re already seeing AI in use: script breakdowns automated, casting suggestions generated, box office forecasts predicted.

What’s missing often is integration – these are point solutions. Imagine a future “creative cockpit” where a writer, producer or exec has a single platform that integrates all these AI capabilities seamlessly. In fact, reports have pointed out the industry lacks a unified hub for these AI tools, which is a major opportunity .

For now, using external AI tools like ChatGPT and Claude alongside traditional software can significantly augment workflows. They serve as tireless assistants: a writer’s brainstorming buddy, a producer’s data analyst, an exec’s research intern. And they do it on demand, in natural language – you just ask, and they answer. That’s a game-changer for busy creatives and execs who don’t have time to wade through every document or reinvent every wheel.

The tone in the industry is turning from fear to curiosity: how can AI make our work better without replacing the human touch? The examples above show a lot of practical answers to that question.

Ultimately, filmmaking and TV production will always be a creative, human endeavor – AI is not writing Oscar-winning scripts by itself anytime soon. But as a tool, it’s like giving our best people a superpower: the writer with an endless idea machine at their side, the producer with omniscient oversight of planning, the exec with instant insight into audience trends.

Used wisely, these AI enhancements can cut drudgery, illuminate tough decisions with data, and even spark new creative ideas. And that means storytellers can spend more time doing what they do best – crafting the stories and experiences that the world loves – while letting the robots handle the boring bits. In the modern media production landscape, the teams that figure out this human-AI collaboration are poised to work smarter, faster…

and maybe even have a little more fun in the process!

YOUR TURN:

Very simply, what is the one reason you have for using AI in your role and what is the one thing that keeps you from using it?

Bonus question: Would you like this catalog as a PDF?

Thanks for digging in!