The Complete Guide to Adobe Podcast AI

Adobe Podcast AI has created quite a buzz since being unveiled as Project Shasta back in 2021. As creators continue to flock to podcasting in droves, Adobe hopes their new AI-powered editing tools will dominant the space. In my 10+ years building speech recognition and AI products, I‘ve seen my share of hype in this space.

But with impressive capabilities like automatic transcriptions, audio clean-up and built-in distribution, this product seems poised to deliver on its promises. In this comprehensive 2800+ word guide, I‘ll give you an unbiased hands-on look at whether Podcast AI can facilitate end-to-end podcast creation and enrich listener engagement.

Why Podcasting and Why Now?

Before we dig into Podcast AI‘s features, it‘s worth stepping back and looking at tailwinds driving adoption of podcasting itself. Based on Edison Research‘s annual survey, awareness and consumption have trended up significantly since 2017:

Awareness sits around 90% as of 2022, while monthly consumption continues growing at a healthy clip. And as listenership gets mainstream, content creation follows. Per Buzzsprout‘s 2022 industry survey, over half of podcasters now consider themselves either intermediate or advanced:

With broader adoption across all fronts, the appetite for tools that simplify and streamline continues growing. Established creators need solutions to increase output and capabilities while lowering costs. Beginners want guidance and best practices while avoiding technical hurdles.

And this need isn‘t lost on Adobe – a brand trusted by creators across photography, videography and design for decades. Which leads us to their latest creation – Adobe Podcasts AI.

Adobe Podcast AI Overview

Announced in November 2021, Adobe Podcast AI aims to provide an end-to-end workflow for creating, editing and distributing podcasts. And it leans heavily into AI and automation to lift typical burdens off creators‘ shoulders. This starts first and foremost with automatic speech transcription upon upload.

Unlike services such as Otter.ai or Trint that provide transcriptions, Podcast AI interleaves them directly into your editing workflow. It analyzes speech, generates text transcripts, then maps words back to the original audio. This unlocks powerful capabilities down the line around searchability and edits.

From there, studio-quality audio enhancements polish and improve raw recordings. These leverage Adobe‘s proprietary Sensei AI framework that has been battle-tested across other products like Photoshop and Premiere. Results I‘ve heard first-hand are impressive – minimal artifacts or tinniness from noise reduction and volume enhancements.

Finally, built-in podcast distribution helps get your final product in front of listeners quickly. Adobe aims to simplify promoting across all major platforms and directories:

And the interface visualizes consumption metrics from each channel to help optimize promotion efforts.

But Podcast AI goes well beyond editing and distribution alone. Let‘s do a deeper dive across some of its most popular features:

Key Adobe Podcast AI Features

Streamlined Editing Workflow

As hinted at above, Adobe Podcast AI‘s ace up its sleeve is definitely its editing environment. Transcriptions form an integral part of the experience rather than getting bolted on after the fact.

This manifests itself in a few ways:

• Text-based search – easily navigate to any point in conversation across potentially hours of recordings
• Text-based edits – insert, overwrite or format transcribed text, and audio updates to match
• Collaborator annotations – give and receive timecoded feedback on edits directly in the transcript

Advanced features like AI captioning and in-app translations (75+ languages) help open podcasts global audiences and those with disabilities.

And customizable highest quality export presets ship episodes with pristine final audio quality:

Based on demos, this all appears to work seamlessly without ever needing to leave the editing window or toggle between modes. The pairing of text and audio makes for efficient workflows compared to legacy audio-only solutions.

And Adobe Sensei works its magic in the background cleaning up speech between edits. It avoids distracting transitions or anomalies that could otherwise creep in.

Audio Clean-Up & Enhancements

As touched on briefly above, Adobe leans heavily into its Sensei AI and ML expertise to offer one-click audio clean-up. This works like magic to improve overall sound quality and listenability.

Exact details of formats and bitrates weren‘t published, but their examples spoke for themselves. Background noise gets eliminated from foreign environments without taking main speech along with it. Music and ambient tones get isolated and extracted when beneficial. Volume and clarity get normalized across multiple speakers and formats.

And touch-ups like straightening pronunciation or removing vocal ticks help presenters put their best voice forward without rerecording. These can be applied automatically during transcription or on a manual per edit basis.

Now voice enhancement alone isn‘t groundbreaking innovation in the podcast space. Alternatives like Descript or Riverside offer similar capabilities. However, Adobe‘s proprietary algorithms paired with Sensei‘s ML training give it an advantage.

I can envision them giving creators more granularity and customization over time around exactly how enhancements get applied. As with their legendary photo editing software, presets and styles tailored to common podcast formats could emerge. Audio could get processed differently for long-form interviews vs tightly edited shows for example.

For now though, the automatic clean-up lives up to its promise in the demos I‘ve seen.

Built-In Distribution & Analytics

Too often, creators need to lean on third-party apps and services to publish and analyze podcast performance. Software like Buzzsprout and Libsyn have emerged to fill this niche for distribution and stats.

However, Adobe aims to bring top podcasters‘ entire workflow into one ecosystem. That means building hosting, syndication and listener metrics right into Podcast AI itself.

The product launches with support for all major directories already included:

• Apple Podcasts
• Spotify
• Google Podcasts
• Pandora
• Amazon Music
• Stitcher
• iHeartRadio
• TuneIn

And more niche apps and platforms expected over time. I wouldn‘t be surprised to see YouTube and Vimeo support added soon for video podcasters. As well integrations with leading CMS platforms like WordPress and Ghost.

The in-app analytics provide views and playback metrics from each platform too:

And these sync hourly so creators can assess performance and react in real-time. Expect to see even more granularity and segmentation on listeners over time as well.

Again, third-party distribution platforms already meet many creators‘ needs today (including Adobe). However having an integrated solution lowers friction for getting content out and assessing engagement.

Podcast AI fills an end-to-end experience gap that gives fledgling podcasters a big leg up. And it still offers enough customization for power creators as the platform matures.

How Does Adobe Podcast AI Stack Up to Competitors?

Adobe Podcast AI was announced alongside a wave of new smart podcast tools over the past year. All aim to simplify creation using varying degrees of AI and automation. To best situate Podcast AI then, it‘s worth comparing how some of these alternatives stack up.

Here‘s a high-level look at how Podcast AI fits versus players like Riverside, Descript and Podcastle:

A few interesting conclusions jump out here:

• Adobe brings together transcription, editing and distribution better than any tool
• Descript is the only one allowing fully AI-generated co-hosts
• Podcastle packs a ton of value at a very fair price
• Riverside focuses more on recording than publishing or enhancement

If you want the simplest path to augmenting your raw podcast with AI across production and engagement, Adobe checks the most boxes in a tidy interface. Descript offers crazy futuristic AI if you have wild creative ambitions. And Podcastle gives cost-effective transcription and distribution a la carte.

The feature disparity here shows there‘s still more convergence to happen in the space before any single winner takes all. Expect more shakeups before maturity. But Podcast AI carves out a niche catering to creatives already bought into other Adobe ecosystem products today.

Who is Adobe Podcast AI Good For?

Given its pedigree and positioning, Adobe Podcast AI caters to a few specific creator crowds more than others right now:

Adobe Customers

This is the obvious low-hanging fruit. Those already paying for Creative Cloud plans like Photoshop, Lightroom or Premiere can now tack on podcast production as part of the bundle. Expect lots of customer cross-sell and bundled deal opportunities ahead.

New Podcasters

For all those anxious to dip their toes into podcasting but intimidated by production hurdles, Podcast AI holds your hand. Its templates, clean-up tools and distribution guide first-timers through comfortably. Intermediate creators may still want more advanced third-party tools.

Video Podcasters

Creators already producing YouTube and social content can easily recycle efforts into audio. Podcast AI‘s editing workflow mirrors what video creators already know in Premiere. And Expect tight integrations with these other Adobe apps soon for seamless transfers between.

Notice a common thread here? Adobe knows its core audiences inside and out. And it‘s optimizing Podcast AI today to slot right into existing creative workflows.

But the product‘s current limitations likely make it less enticing for other significant podcasting niches. Specifically, Podcast AI likely falls short for:

• Advanced podcast producers – working across multiple shows with teams of editors, sound engineers and writers
• Enterprise podcasters – companies publishing internal audio newsletters and communications
• Audiobook creators – producing and publishing longform audio books solo

Expect to see Adobe cater more to these creator segments over time. But its initial focus stays squarely on leveraging its brand strength with digital creatives.

Tips for Getting Started With Adobe Podcast AI

If you want to be among the first to try Adobe‘s new AI-powered podcast editor, the closed beta has already begun. As a veteran technology tester, here are my top 5 tips for getting started on the right foot:

1. Prepare Interesting Conversation

No intelligent editor can save boring source material. Think carefully about co-hosts, talking points and formats that will spark lively dialogue. This gives Adobe‘s algorithms more vocal range and personality to work with.

2. Use Recommended Gear

High-quality recording equipment ensures you get clean input audio so enhancements can shine. Adobe lists Blackmagic Design and Zoom as top partners so far. Keep your setup simple until you get the hang of things.

3. Learn With The Audio Pilot

Adobe‘s Audio Pilot creation guide walks first-timers through planning, recording, enhancing audio and publishing step-by-step. Lean on its tutorials to avoid initial missteps and build confidence.

4. Share With The Community

The official Adobe Community forums connect new users to ask questions and leverage tips from early adopters. Chime in as you run into hurdles or surprises to benefit from shared wisdom.

5. Provide Product Feedback

Remember that Podcast AI remains in closed beta for now. Providing detailed feedback on its testing portal guides the team to refine the product before public launch. Point out gaps from existing tools or confusing flows to influence positive change.

And above all, have fun! Playing podcast pioneer during these early days means shaping an exciting new creator tool for the future.

The Future of AI-Assisted Podcasting

It‘s an exciting time in podcasting all around. Consumption continues soaring globally as more listeners integrate on-demand audio into their routines. And creation tools continue maturing to meet rising demand from both pro outlets and indie voices.

Adobe Podcast AI sits at the intersection of these trends – providing efficient editing and reach to aspirational creators. It demystifies the production process through AI guidance and enhancement. And it lowers publishing barriers to turn passion projects into real listener numbers.

As covered earlier, competitors like Descript, Riverside and Podcastle take varying approaches to the same mission. Simplification through AI to empower podcasters. But Adobe‘s legacy creative brand and audience provides an advantage out of the gates that can‘t be discounted.

Looking ahead, it‘s clear automated editing and enhancement will become table stakes for any leading tool. The future battles will come down to customization and depth of control offered to satisfy power creators. Not to mention behind-the-scenes technical aspects like video support, storage formats and collaboration.

And podcast ad monetization can‘t be ignored – expect to see tools like Podcast AI build in ways for creators to easily insert, deliver and report on custom ad placements. Analysts already predict podcasting revenue near $2 billion in 2021, ballooning to over $3 billion by 2024.

But for now, Adobe Podcast AI checks all the boxes that early mainstream podcast adoption requires. It makes the process friendlier, distribution easier and results more reliable out of the box. And Adobe will surely be paying close attention to user feedback for clues where innovation needs to happen next across audio, video and beyond.

So whether you‘re an aspiring new podcaster or established pro scoping out the latest crop of tools, carve out time for a test drive. Adobe Podcast AI could just become your creative catalyst for transforming side projects into chart-topping productions. The time is now to start honing your unique voice andperfecting your formula. Because more receptive ears await than ever before.