Use cases of AI in media and entertainment

Philip Tikhanovich

May 12, 2025 20 min å lese

I’ve spent enough time in the industry to see one undeniable truth: media and entertainment are changing faster than most companies can keep up with. The days of manual content production, gut-feeling marketing, and one-size-fits-all distribution? They’re over. AI is now the backbone of how content is created, edited, distributed, and monetized.

I see businesses either embracing AI and scaling like never before… or resisting it and falling behind. Netflix fine-tunes recommendations with machine learning, Disney automates animation with AI-driven tools, and platforms like Spotify don’t just suggest music — they predict what you’ll want before you even realize it yourself.

But let’s temper the hyper. AI isn’t some magical solution that automatically makes content go viral or productions run smoother. But it has very real, practical use cases that are already delivering measurable results. Today I’ll be breaking down the use cases of AI in media & entertainment — what works, what doesn’t, and what businesses need to consider before jumping in.

If you need a spoiler: AI won’t replace creativity, but it will redefine how we create, distribute, and monetize content. The question is — are you ready to adapt?

How is AI used in entertainment and media?

We hear it all the time: “AI is transforming media.” But what does that really mean? Automated video editing? Personalized recommendations? AI-powered scripts? I’ll try to go beyond the headlines to explore real examples of AI in the entertainment industry and where I think AI genuinely moves the needle.

1. AI-driven content creation

AI is already at the center of how content is being generated, reshaping workflows and challenging traditional creative processes. But as with any new technology, there’s a healthy amount of debate about its role. So, what are the ways AI is making an impact?

First, it’s a time-saver for creators. From a practical standpoint, AI helps creators focus on the high-level, value-adding aspects of their work. Instead of spending hours drafting basic content, a marketer or a journalist can use AI to generate initial drafts that they can refine and customize.

I’ve seen companies in media, like The Associated Press, implement AI to streamline news production.

While the AI doesn’t replace the journalist, it dramatically speeds up the routine process so that humans can focus on deeper stories or more nuanced writing.

For det andre, AI is a decent co-creator. I’ve been particularly impressed by AI’s potential in music and filmmaking, where tools like Amper Music and Aiva Technologies are enabling creators to compose music and generate soundtracks. These tools are far from simply spitting out generic, pre-programmed tunes; they offer customization based on mood, tempo, and style. Nowadays, creators can experiment in ways they might not have otherwise.

I particularly admire how David Cope, a well-known composer who has collaborated with AI, put it: “The programs are just extensions of me. And why would I want to spend six months or a year to get to a solution that I can find in a morning? I have spent nearly 60 years of my life composing, half of it in traditional ways and half of it using technology. To go back would be like trying to dig a hole with your fingers after the shovel has been made.”

And I couldn’t agree more. AI might not have the emotional depth of a human composer, but it can certainly open up new doors in the creative process.

“AI isn’t here to write the next Oscar-winning script, but it can help storytellers break creative blocks, predict audience trends, and work smarter. The winners will be those who embrace it as a collaborator, not a competitor.”

Dmitry Nazarevich

CTO

2. AI in video editing and post-production

Editing has always been one of the most time-consuming parts of video production. Anyone who’s spent hours fine-tuning cuts, adjusting colors, or fixing audio knows how tedious it can get. But AI is stepping in to take a lot of the grunt work off editors’ shoulders.

Take Adobe Sensei, for example. Adobe has been a go-to for video professionals for years, and their AI-powered tech is making editing way more efficient. It automates tasks like color correction, scene detection, and audio cleanup — things that used to eat up a ton of time.

And then there’s Deepdub, which is shaking up dubbing in a big way. Traditional dubbing takes a ridiculous amount of effort: finding the right voice actors, syncing speech perfectly, and keeping the performance natural. Deepdub’s AI analyzes an actor’s voice and recreates it in multiple languages, keeping their tone, emotion, and even subtle vocal quirks. That means international releases don’t just sound translated — they actually feel authentic. If you’ve ever cringed at an awkwardly dubbed movie, you’ll get why this is such a big deal.

AI is also handling things like motion tracking, object removal, and even face recognition to help organize massive amounts of footage. It’s making post-production not just faster but smarter.

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3. Personalization & recommendation algorithms (the secret behind addictive streaming)

Ever wondered why Netflix always seems to know what you’ll love next or why Spotify’s Discover Weekly feels eerily on point? That’s AI working behind the scenes, analyzing your habits, predicting your preferences, and keeping you engaged.

At this point, personalization is the backbone of streaming platforms. Without it, users would be drowning in endless content libraries, unsure of what to watch or listen to next. AI changes that by understanding individual tastes and making sure there’s always something relevant to keep you hooked.

Take Netflix’s recommendation engine. It’s not just looking at what you watched last. It breaks down watch history, viewing patterns, and even metadata like scene composition, pacing, and genre trends. That’s how it decides whether to push a slow-burn drama your way or suggest a fast-paced thriller.

Spotify does something similar with music curation. It doesn’t just track what songs you play, it learns from how long you listen, what you skip, and what you add to playlists.

AI models like OpenAI’s Jukebox even analyze musical structures to predict what kind of sound you might enjoy next.

From my perspective, AI-powered recommendations are a double-edged sword. On one hand, they enhance user experience — nobody wants to sift through thousands of options aimlessly. But on the other hand, they can create content bubbles, where people only see what aligns with their past choices, limiting discovery. Some platforms try to counteract this by introducing “exploration” algorithms that intentionally throw in diverse picks.

At the end of the day, personalization is crucial for engagement and retention. The better AI and media platforms get at understanding users, the more time they’ll spend streaming — and that’s exactly what platforms want.

4. Artificial intelligence in entertainment marketing & ad targeting

Marketing in media and entertainment has always been about reaching the right audience at the right time. And AI has made it easier. Instead of throwing ads out there and hoping for the best, companies now have data-driven precision that makes every marketing dollar count.

Take Google Ads. It’s no longer just about setting keywords and budgets. The AI behind it constantly analyzes user engagement data, browsing behavior, and past interactions to fine-tune which ads people see. It automatically adjusts headlines, images, and calls-to-action based on what performs best.

But AI in the entertainment industry marketing isn’t just about digital ads. It’s also transforming big-picture decisions, like predicting which movies will succeed before they even hit theaters. Cinelytic, for example, uses AI to analyze casting choices, budget allocations, and marketing strategies to estimate box office performance. Studios use this data to refine their promotional efforts and even adjust release strategies.

From where I stand, this kind of AI-driven marketing is both a huge opportunity and a challenge. On one hand, it’s making advertising far more efficient, helping studios and platforms allocate budgets where they’ll have the most impact. But on the other hand, it can lead to formulaic decision-making, where creativity takes a backseat to what AI predicts will be “safe bets.”

5. Automated content moderation & deepfake detection

With the sheer amount of content uploaded every second, human moderators just can’t keep up. Plus, dealing with disturbing material takes a real toll on their mental health. AI is now what keeps platforms safe, filters out harmful content, and tackles deepfakes before they spread.

Take YouTube’s AI moderation system. It scans and removes harmful, misleading, or inappropriate content before it gains traction. The system is trained on massive datasets to recognize patterns of hate speech, copyright violations, and even subtle misinformation tactics. It doesn’t just look at the video itself but also analyzes captions, comments, and engagement metrics to catch violations. And while AI does most of the heavy lifting, human reviewers step in when things get complicated, because AI isn’t perfect.

Deepfake technology is another major challenge. It’s getting so advanced that distinguishing real from fake is harder than ever. This is where AI-driven detection tools like Deepware, Sessity AI, and Deeptrace come in. They analyze facial inconsistencies, unnatural blinking patterns, and pixel distortions to flag manipulated videos. Platforms, news outlets, and even law enforcement rely on these tools to prevent the spread of deceptive content and AI-generated misinformation.

6. AI in gaming & virtual worlds

If there’s one media & entertainment area where AI’s impact excites me the most, it’s gaming. Unlike passive media, games are interactive by nature, and AI has the power to make them feel more alive, more unpredictable, and more personal than ever before.

One of the most fascinating developments is how NPCs (non-playable characters) are evolving. I’ve always found it frustrating when game characters feel like glorified signposts, repeating the same canned dialogue no matter what you do. But AI is changing that. Now, NPCs can remember interactions, adjust their behavior based on player choices, and even generate natural dialogue on the fly. This means every player can have a slightly different experience, even in the same game. To me, that’s a game-changer (pun intended).

Another area I can’t ignore is AI-driven graphics enhancements. Take Nvidia’s DLSS, for example. Instead of brute-force rendering, AI predicts and fills in details, making games look stunning without tanking performance. I see this as one of the smartest applications of AI in gaming. Rather than just making games more demanding, AI is helping them run better, even on older hardware.

And let’s talk about AI-generated storytelling. I find projects like AI Dungeon fascinating because they hint at the future of interactive narratives. Instead of scripted stories with limited choices, AI can craft dynamic, player-driven narratives that feel limitless. But I’ll be honest — I don’t think AI storytelling is quite there yet. While it can generate text in real-time, it still struggles with cohesion, pacing, and deeper emotional arcs. Right now, I see it as a powerful creative tool, but not a replacement for great writing.

7. AI in AR/VR & interactive experiences

While the tech has made incredible leaps, many VR experiences still feel like gimmicks rather than truly immersive worlds. This is where AI acts as the missing piece that transforms AR/VR from “cool” to truly convincing.

One of the most exciting areas, in my opinion, is AI-driven avatars and digital humans. We’ve all seen robotic, lifeless virtual characters that break immersion the moment they speak. But now, AI-powered systems of facial animation and voice synthesis are making digital humans more expressive, more responsive, and — dare I say — almost believable. Meta’s AI avatars, for instance, use deep learning to map a user’s facial expressions onto a virtual character in real time. This means your digital self actually reacts like you, making social interactions in VR feel far more natural.

Then there’s AI-enhanced AR experiences. For example, at Innowise, we develop AI-powered AR apps that are doing something I find particularly interesting: they let users create realistic digital avatars that can move, react, and even respond dynamically to the real world. Instead of static AR filters, we’re moving toward AI-powered interactive layers that blend seamlessly with reality. I see a huge opportunity here for brands, entertainment, and even education. Imagine a history lesson where a historical figure walks up to you and starts a conversation — that’s where AI is taking AR.

That said, I think there’s still a fine line between realism and the uncanny valley. AI can make avatars and AR characters look and move realistically, but can it make them feel truly human? That’s another challenge entirely. Right now, AI mimics human-like responses, but there’s still a gap between an AI-driven interaction and a conversation that feels genuinely natural.

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Artificial intelligence in media: what’s coming next (and why it’s exciting)

We’re only scratching the surface of what entertainment AI can do. As the technology matures, the future of media and entertainment will be marked by increased personalization, greater interactivity, and more seamless integration between AI and creative professionals.

Imagine AI-driven storytelling engines that dynamically adjust narratives based on audience input in real time. Streaming platforms could offer interactive storytelling, where viewers influence plot twists, character decisions, or even alternative endings.

In music and film, emotionally adaptive AI could create soundtracks that change based on your mood or even the weather outside. AI-generated dialogue, perfected with real-time dubbing, may blur the line between localization and performance, allowing actors to star in global productions without ever stepping into a recording booth.

Gaming will likely see AI-powered NPCs with memory and evolving personalities, creating characters that learn from players over multiple interactions. Meanwhile, AI-enhanced virtual influencers and digital humans may replace traditional brand ambassadors, delivering hyper-personalized engagement that feels indistinguishable from human interaction.

For businesses, the key to staying ahead will be to not just use AI in entertainment for efficiency, but to leverage it for innovation. Media companies that focus on interactivity and engagement, not just content production, will define the next wave of the industry.

The question is no longer whether AI will transform media — it’s how soon and how deeply it will reshape the way we create and experience entertainment.

My take on AI in media & entertainment

AI is transforming how we create, distribute, and experience content. From streamlining video editing and content creation to improving recommendation algorithms, AI and entertainment are becoming more intertwined. It’s also fascinating to watch AI push the boundaries of gaming, AR/VR, and interactive storytelling. And let’s not forget its crucial role in content moderation and deepfake detection, which helps us maintain trust in digital media.

På Innowise, we don’t just follow these trends — we actively shape them. Our AI solutions for media and entertainment help companies personalize content, automate workflows, and unlock new creative possibilities. Whether it’s AI-powered video analytics, virtual character animation, or intelligent ad targeting, we help businesses stay ahead in an industry that never stops evolving.

And if you’re looking for custom AI development, that’s where we really shine. From deep learning models to NLP and computer vision, we build AI-powered tools that turn ambitious ideas into reality. The way I see it, AI isn’t just the future of media — it’s the present. And if you’re not leveraging it yet, you’re already behind. Let’s change that.

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