Artificial Intelligence (AI) has become a key topic in all business sectors over the past few years. This advanced technology has revolutionized how industries operate and connect with their audiences, including the video and filmmaking world.

AI is undeniably making processes faster and more efficient. In video production, AI-powered tools have helped editors, directors, animators, and content creators effectively manage everything from pre-production to post-production.

If you haven't understood the role of AI in video production, this article will shed some light on it. We've compiled seven ways Artificial Intelligence (AI) has changed the creative industry. Let's dive into the details!

Suggest Plots in Script writing

Script writing is a crucial part of video pre-production. In this stage, writers, along with clients or stakeholders, decide on plots and storylines. If you've done script writing before, you know how challenging it can be to develop an idea.

While creative blocks can occur at any time, AI writing tools act as writing assistants by suggesting ideas for storylines and plot developments. ScriptBook, for example, can analyze thousands of successful scripts and suggest exciting twists and turns for a story.

Free generative AI tools like ChatGPT and Gemini can also develop a story. However, these tools may produce biases and misconceptions, so manual checking and editing are necessary to ensure your story is unique, authentic, and relevant.

Create Realistic Footage with Virtual Production

Virtual production uses AI to create stunning, lifelike backgrounds and environments that appear real on screen. The benefit? Of course, this technology obviously reduces the need for on-location shoots, meaning fewer travel costs. 

Technologies like Unreal Engine use AI to render real-time, photorealistic backgrounds. Disney+ is reported to use this tool when producing "The Mandalorian," avoiding filming in various real-world locations. This tool also supports 3D modeling.

According to the Unreal Engine forum, the best way to generate realistic footage is to input a real photo as a reference. Moreover, 3D modeling can be done in any 3D application or inside the Engine itself. 

Automated Editing

Manually editing video can be time-consuming and energy-draining. AI comes to the rescue to automatically handle many of the tedious tasks. The famous Adobe Premiere Pro is an example of an editing tool that offers automated editing with AI.

The Auto Reframe feature uses AI to analyze footage and automatically adjust the framing. It ensures the main subjects are always in focus, regardless of the aspect ratio. This feature is particularly useful for adjusting videos for different screen sizes.

Moreover, AI can identify and remove unwanted elements, such as background noise or accidental camera shakes. These automations help editors focus more on the creative aspects, such as storytelling and visual effects, leading to higher-quality productions in less time.

Automate Complex Visual Effects Tasks 

Still in the production process, AI helps create visual effects (VFX) for movies and motion graphics effects for animated videos. Processes like rotoscoping, which involves tracing over motion picture footage to create realistic and integrated effects, can be extremely labor-intensive.

AI tools like Adobe and Blackmagic Design can automatically track and isolate objects or people in a video. In addition, these tools can enhance other processes, such as simulating realistic weather conditions, explosions, or fantasy creatures.

Editors can use this technology as an initial step and further improve the process with their skill and creativity. By automating some of the visual effect processes, editors can enhance their workflow to be faster and more efficient.

AI-Generated Video Content 

Generative AI has gone beyond writing assistants like ChatGPT and Gemini. Now, this technology has also been implemented in video production. Some examples of video tools with generative AI are Runway ML and DeepBrain AI.

The way these tools work is quite simple. You can input simple text descriptions to describe video visuals. The machine proceeds with your prompt to create a video output. Not only text prompts, you can transform static images into dynamic animations.

Text-to-video technology is mainly used for creating content at scale, such as social media videos, advertisements, and educational materials. However, visuals may appear robotic or lack creativity, so further manual enhancement may still be necessary.

Content Delivery Optimization

Content delivery means ensuring smooth, high-quality viewing experiences for audiences with various screen sizes. YouTube, the largest video platform, also uses AI to adjust video quality in real-time based on the user's internet connection and device.

Many refer to this process as adaptive bitrate streaming. In simple words, this process ensures videos play without long buffering, even on slower connections. AI analyzes users' network conditions, so higher internet speed results in high-quality videos, while devices with poor internet connections may result in lower pixelates. 

This enhancement in video platforms doesn't directly impact creators or video production companies. However, it helps video platforms like YouTube and Netflix to provide a better viewing experience to audiences across devices.

Analyze Video Performance on Online Platforms

Besides helping with video production, AI is mainly implemented in data analysis. It excels at analyzing large datasets, identifying patterns, and even suggesting further improvements. 

Analytics tools are powered by AI. They analyze essential metrics, such as engagement, watch time, drop-off rates, and interaction patterns. You can learn how analytics work on YouTube Analytics, Instagram Insights, or other social media.

Beyond basic metrics, AI can analyze sentiment by examining comments, likes, dislikes, and shares. This capability is typically offered by paid analytics tools like IBM Watson and HubSpot. They provide insights into how audiences feel about the content and give data-based recommendations.

AI analytics still offers more, including audience segmentation and predictive analytics. These features are crucial for businesses as they give insights into targeted marketing and content customization.

Possible Challenges when Using AI for Video Production

Now we understand why AI in video production can bring many benefits. However, along with those, AI also comes with several challenges. If you use AI tools to produce videos, consider the following possible challenges.

High-Cost 

Some AI tools require a significant upfront investment in hardware and software. In filmmaking and video production, some AI-driven software needs compatible hardware, so building a compatible environment can be costly.

Moreover, the development cost for integrating AI into existing workflows can be high and time-consuming. Not to forget the cost of training employees, especially if you need to invite experts.

Technology Complexity and Learning Curve

Some AI tools are easy to use, but others may require specific skills and complex understanding. Overcoming the learning curve without expert guidance can take time and is particularly difficult for independent creators.

Lack Creativity

AI may be good at handling repetitive tasks. However, it may struggle to add in-depth creativity and personalized touches. 

Typically, nuanced aspects of video production are best driven by human intuition. Moreover, AI can lead to formulaic and less innovative content. 

Data Privacy

AI tools like analytics need to access large amounts of data. If you're not careful , this can raise concerns about privacy and security of sensitive information.

In addition, ensuring compliance with data protection regulations can be challenging when using AI. So, make sure the AI tools you use don't cause any data breaches.

Takeaway

AI for video production goes beyond editing and automating tasks. Its capabilities have helped with pre- and post-production. With a well-integrated ecosystem, AI ensures work efficiency and accuracy.

Businesses of all sizes have leveraged AI tools to support their workflow. However, using AI for video production still requires manual checking and review to ensure originality and avoid robotic results. After all, nothing can beat human creativity and capability! 

Author Bio

Andre Oentoro is the founder of Breadnbeyond, an award-winning animation video company. He helps businesses increase conversion rates, close more sales, and get positive ROI from explainer videos (in that order).