What is it like to edit videos with AI? Real efficiency doubles!

"This video project will take you a week to edit." When I received this YouTube travel Vlog project, the client's expectations made me secretly worried. 4 hours of raw footage, requiring a 15-minute final product, also requiring subtitles, background music, and basic color grading. According to my past workflow, it would indeed take 5-7 days to complete.

But this time, I decided to try a new method - introducing AI-assisted tools. Frankly, I was skeptical about this. As a video editor with 8 years of experience, I have witnessed too many technological innovations being overhyped and then fizzling out.

The result was surprising: I finally delivered the final product in less than 3 days, and the client feedback was better than before. This aroused my curiosity: What changes has AI brought to video editing? Can it really double efficiency?

So in the next two months, I systematically tested the mainstream AI video editing tools on the market and applied them to 7 real projects. This article shares my personal experience, hoping to provide a reference for colleagues and unveil the mystery of AI video editing for ordinary creators.

Panorama of Contemporary AI Video Editing Tools

Before delving into personal experience, let's sort out the types of AI video editing tools currently on the market:

1. Full-process AI Editing Platform

This type of tool provides a complete solution from material import to finished product export, focusing on a "one-stop" experience.

2. Plug-in AI Tools

This type of tool serves as an extension of traditional editing software, enhancing the existing workflow rather than replacing it.

3. Special Function AI Tools

This type of tool focuses on solving specific pain points in the editing process.

The market is developing rapidly. In the first quarter of 2024 alone, 23 new AI video tools were released, with an investment of 420 million US dollars, showing the explosive growth of the industry. However, quantity does not mean high quality. Below I will share my actual user experience.

Real Project Experience: From Material to Finished Product

In order to objectively evaluate the actual effect of AI tools, I chose a typical YouTube video project for comparative testing: a 15-minute product review video, including character explanation, product close-ups, and demonstration clips.

Traditional Workflow

I first completed the editing using traditional methods:

1. Material Sorting: Manually browse 2 hours of material and mark the shots (approximately 45 minutes)
2. Rough Cut: Splice the main paragraphs in the order of the script (approximately 2 hours)
3. Fine Cut: Adjust the rhythm and add transitions (approximately 2.5 hours)
4. Add Subtitles: Manually transcribe and align the timeline (approximately 3 hours)
5. Color Grading and Special Effects: Basic color grading and graphic animation (approximately 2 hours)
6. Audio Processing: Balance volume, background music, and sound effects (approximately 1.5 hours)
7. Export and Modification: Render, check, modify, and re-render (approximately 1 hour)

Total Time: Approximately 12.5 hours

AI-assisted Workflow

Next, I used AI tools to assist in completing the same project:

1. Intelligent Transcription Analysis: Use Descript to automatically transcribe and analyze the material (approximately 10 minutes of operation + 20 minutes of AI processing)
2. Text-based Rough Cut: Edit directly on the transcribed text, and AI automatically corresponds to video editing (approximately 1 hour)
3. AI-assisted Fine Cut: Use Adobe Premiere Pro's AI rhythm analysis tool to adjust the editing points (approximately 1.5 hours)
4. Automatic Subtitle Generation: AI transcription generates subtitles, only need to proofread (approximately 45 minutes)
5. AI Color Grading Template: Use Colourlab AI to analyze and match reference colors (approximately 30 minutes)
6. Intelligent Audio Processing: Adobe Podcast enhances human voice and automatically balances volume (approximately 40 minutes)
7. Export and Modification: Same as traditional process (approximately 1 hour)

Total Time: Approximately 5.5 hours

This is an amazing result: the same project, AI-assisted workflow saves about 56% of the time compared to traditional methods. But time data alone is not enough. Let me analyze the experience differences in each link in detail.

Efficiency Comparison: AI vs Traditional Workflow

1. Material Sorting and Analysis

Traditional Method: Need to manually watch all the material, record time codes and content, which takes a lot of effort.

AI Method: After uploading the material, AI will perform transcription and content analysis in the background. Descript and Premiere Pro's transcription accuracy has reached more than 94%, and even professional terms can be basically recognized. Even more surprising is that some tools (such as Opus Clip) can even recognize the content of the picture and automatically mark paragraphs such as character close-ups, scenery, and product displays.

Experience Difference: AI greatly reduces the most tedious preliminary work, allowing me to focus on creative thinking. But it is worth noting that AI analysis requires uploading material, which may be limited by network speed for large projects.

2. Rough Cut Stage

Traditional Method: Need to repeatedly refer to the script and material, manually locate and drag and drop clips.

AI Method: Descript's "text-based video editing" function has completely changed this link. I only need to delete the unwanted parts in the text, and the software will automatically cut the corresponding video clips. What's even more surprising is that when deleting interjections ("um", "this"), AI can intelligently smooth the transition, and the audience cannot detect the editing marks at all.

Experience Difference: This is the most revolutionary part of my experience, especially suitable for dialogue-based content. However, this method is relatively weak for music videos or content without dialogue.

3. Subtitle Generation

Traditional Method: A lot of adjustments are required after manual transcription or using primary transcription tools.

AI Method: Whisper and Premiere Pro's transcription tools have reached the level of close to professional transcribers. More importantly, they can intelligently identify speakers, understand tone pauses, and accurately place punctuation marks. In multilingual projects, AI subtitle tools can even provide real-time translation.

Real Data: In a 40-minute interview video, traditional transcription takes about 3 hours, while using WhisperX only takes 12 minutes, and the errors that need to be corrected do not exceed 5% of the total number of words.

4. Color Grading and Visual Effects

Traditional Method: Need to manually adjust color wheels, curves, and other parameters, and then apply them to similar clips.

AI Method: Colourlab AI can analyze the color distribution of the entire project and then match the reference style. More useful is that it can intelligently identify human skin tones and maintain consistency. And Topaz Video AI can enhance 1080p material to 4K, the effect is far better than traditional scaling algorithms.

Experience Difference: AI color grading saves a lot of repetitive work, but manual guidance is still required in creative color grading. Topaz's picture quality enhancement is amazing in low light conditions, but the processing speed is slow.

5. Audio Processing

Traditional Method: Manually adjust the volume curve and add effects such as equalizers and compressors.

AI Method: Adobe Podcast's enhancement function can eliminate background noise and enhance human voice clarity with one click. Tools such as MatchAudio can automatically balance the volume of the entire project to ensure a consistent viewing experience.

Experience Difference: AI audio tools greatly simplify basic audio processing, but complex audio design and mixing still require professional skills.

Limitations and Challenges of AI Editing

Despite the obvious efficiency improvement, AI video editing still faces some practical challenges:

1. Limited Creative Judgment

AI can perform technical tasks, but it is difficult to make artistic decisions. For example, when to use a specific transition and how to set the rhythm to cause an emotional response still require human judgment. In a music video project, I asked AI to try to edit according to the rhythm of the music, but the result was mechanical and lacked emotional levels.

2. Difficulty in Processing Non-linear Narrative

AI tools perform poorly when videos require complex narrative structures (such as flashbacks, parallel plots). They are good at simple organization based on time order or dialogue content, but it is difficult to understand abstract narrative concepts.

3. Software Ecosystem is Scattered

Currently, no tool can complete all AI-assisted tasks. It is necessary to switch between multiple platforms, which increases the learning cost and workflow complexity. I need to use at least 3-4 different tools at the same time in the project, and data migration is also a pain point.

4. Computing Resource Requirements

High-quality AI video processing requires powerful computing power. AI tools running locally (such as Topaz) have high hardware requirements, while cloud services rely on stable network connections and high subscription fees.

5. Lack of Fine Control

Many AI tools use "black box" algorithms, and users cannot precisely control the processing process. For example, when using RunwayML's video frame interpolation function, you cannot accurately specify key frames or transition styles, you can only accept AI's judgment.

Cost Analysis: Save Money or More Expensive?

AI video editing tools improve efficiency, but also bring a new cost structure. The following is a cost comparison based on a medium-sized creator (producing 8-10 videos per month):

Traditional Editing Cost

• Adobe Creative Cloud Subscription: $54/month
• Material library subscription (music, special effects, etc.): $30/month
• Outsourcing transcription service (if needed): $80/month
• Total Monthly Cost: Approximately $164

AI-assisted Editing Cost

• Adobe Creative Cloud Subscription: $54/month
• AI editing tool portfolio (Descript Pro + Runway, etc.): $70/month
• High computing power cloud processing fee: $25/month
• Material library subscription: $30/month
• Total Monthly Cost: Approximately $179

On the surface, the AI workflow costs an extra $15 per month, an increase of 9%. But considering the efficiency improvement of more than 50%, the cost per project is actually reduced by about 27%. More importantly, this frees up time resources, allowing creators to produce more content or improve quality.

For creators of different sizes, the return on investment point is also different:

• Amateur Creators (1-2 videos per month): AI tools may increase the financial burden, it is recommended to selectively use free or low-cost options
• Medium Creators (5-15 videos per month): Efficiency improvement can offset additional costs, and the overall return is positive
• Professional Studios (15+ videos per month): AI tools bring significant net benefits, and the return is higher as the scale increases

How to Get Started: Introduction to AI Video Editing

Based on my experience, here are AI editing entry suggestions for different levels of users:

Beginner Path (Limited Budget)

1. First Step: Use WhisperX (open source) to achieve automatic transcription and subtitles
2. Second Step: Try the free version of Opus Clip for automatic editing of social media short videos
3. Third Step: Use Adobe Premiere Rush's built-in basic AI functions (such as automatic composition)
4. Investment Focus: First master basic editing skills and use AI as an auxiliary tool

Intermediate User Path (With a Certain Budget)

1. Core Tool: Subscribe to Descript Pro ($12/month) for text-based video editing
2. Auxiliary Tool: Add Topaz Video AI ($199 one-time) to improve video quality
3. Workflow Integration: Combine AI tools with existing editing software to establish a hybrid workflow
4. Investment Focus: Choose special tools that can solve personal workflow pain points

Professional User Path (Seeking Maximum Efficiency)

1. Tool Combination: Descript + Runway + Premiere Pro's AI extension function
2. Workflow Automation: Use API to connect different tools and establish automated processing processes
3. Team Collaboration: Use cloud-based AI tools to achieve remote collaboration and parallel work
4. Investment Focus: Build a complete AI-assisted pipeline that can handle everything from material management to finished product release

No matter which path you take, I suggest starting with one or two tools, testing their effects in actual projects, and then gradually expanding the tool set. The most valuable entry-level tools are automatic transcription and text-based editing, which are applicable to almost all types of video projects.

Future Outlook: The Development Direction of AI Editing

According to industry trends and technology roadmaps, AI video editing may have the following developments in the next 12-24 months:

1. Progress in Multi-modal Understanding

Future AI will not only understand voice content, but also deeply interpret visual narratives, emotional tones, and cultural backgrounds. For example, identify key emotional moments and suggest appropriate music or transitions.

2. Rise of One-Stop Solutions

As competition intensifies, we will see more platforms that integrate complete workflows, reducing the need to switch between multiple tools. Traditional manufacturers such as Adobe and Blackmagic Design are also rapidly integrating AI capabilities.

3. Personalized Creation Assistant

Future AI tools will learn users' style preferences and work habits, providing suggestions that are more in line with personal aesthetics, rather than general solutions. This may completely change the creative relationship and make AI a true creative partner.

4. Reduce the Technical Threshold

AI will continue to simplify the technical complexity of video creation, allowing more people to produce professional-level content. This may reshape the talent structure and workflow of the entire creative industry.

Conclusion: AI Will Not Replace Editors, But Will Change the Way They Work

After two months of in-depth practice, I came to a few conclusions:

1. AI can indeed significantly improve efficiency, and even double efficiency in some workflows
2. Creative judgment is still a human field, AI is more like a powerful collaboration tool than a substitute
3. The learning curve is worth it, although it takes time to adapt to new tools, the long-term benefits are significant
4. The focus of work will shift from repetitive technical tasks to more advanced creative decisions

For professional video producers, the question is no longer "whether to use AI", but "how to most effectively integrate AI". Like the early non-linear editing system revolution, AI tools are redefining this industry.

Finally, I would like to share an interesting observation: In projects using AI tools, I found that I spent more time on actual creative thinking. No longer consumed by tedious technical tasks, I can focus more on exploring narrative structure and visual style. Perhaps this is the greatest value of AI video editing - not only improving efficiency, but also releasing creativity.

For any video creator, now is the best time to explore these tools. They may not immediately integrate perfectly into your workflow, but the potential is huge and the development is rapid. As a senior editor told me: "Instead of waiting for the perfect AI tool to appear, it is better to start learning how to work with AI now."

Author's Note: This article is based on AI video editing tools available in April 2025. Technology is developing rapidly, and some specific functions and prices may vary.