Here's how you can incorporate artificial intelligence and machine learning into your podcasting content.

AI editing for podcasts makes the editing process easier and better. It can clean up audio by removing background noise and adjust volume levels automatically. AI also turns spoken words into text, making it easier to find and fix mistakes or organize content. It helps suggest edits based on past editing choices and ensures audio quality meets standards. AI can even add music or sound effects to enhance the listening experience. With AI, podcasters can collaborate more efficiently and save time, creating polished episodes that sound great without as much manual effort.

DAWs like Adobe Audition have been handling post production needs for a long time. In the last 18 months, Adobe has been integrating Vocal Enhance, featured in their Adobe Podcast page, into their products. This incredible tool takes subpar audio and enhances it to a studio quality sound using machine learning. While not native to audition, the feature is currently embedded into the Premiere platform. Of course, garbage in will result in garbage out - especially if there are multiple voices being pickled up by a microphone.

AI and machine learning are revolutionizing podcasting by automating labor-intensive tasks and offering new insights into listener behavior. However, for those seeking the highest audio quality and precision, SaaS like Audyllic partnered withOrban Optimod remain unmatched. The future of podcasting will likely see a blend of both, leveraging the strengths of AI while maintaining the superior capabilities of established audio technologies.

What used to take hours now takes minutes, with AI editing tools. For example, tools like Descript can handle a multitude of podcasting post-production tasks like transcriptions, creating audio and video clips, and text-based captions, in less than a minute! This will help you save time and money you can apply elsewhere.

Most podcasters don't have access to complex machine-learning algorithms and large language models (LLM) for content analysis but do have access to YouTube Studio. YouTube Studio provides useful analytics on a metric called "Audience Retention." Audience retention includes a watch time graph over your video duration that indicates the percentage of the audience that sticks throughout the entire video. In addition, YouTube Studio provides analytics for average view duration (example 9:56) and average percentage viewed (example 16.9%) to help inform your content. Even audio-format-only podcasts can be modified with AI editing tools for YouTube easily, so you can take advantage of their built-in content analysis tools - free to use!

In my experience, using platforms consistently will streamline your process. Some of my go-to systems are Riverside.FM and Descript. These platforms are robust and continuously evolving. If you stick with certain platforms and grow with them, your content will stay consistent, which in turn helps your show grow.

One thing that I have found helpful recently is the use of CastMagic. This AI tool integrates seamlessly into all of our systems and processes, allowing you to automate nearly every piece of copy you need. However, I must emphasize: please don't rely solely on AI. Always have a human review to ensure that the content is tailored to your specific tone and voice.

AI tools for podcasting are being constantly developed. Be open to experimenting with different tools and technologies because in my experience, there is yet to be an all-in-one AI tool that does everything. As your show evolves, your preferences around pre and post production will change. Make sure you’re subscribed to an AI Newsletter to keep apprised of new releases.