Zahnow Library guides/Applied AI literacy
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Applied AI lessons

10 lessons and six hands-on experiments. Work through them in order, at your own pace.

Lesson 7 of 10

The creative explosion and how creators work

In plain termsBeyond the big chatbots, thousands of smaller companies build AI tools for specific creative jobs: music, video, voice, design, websites. You don’t need to know them all. Knowing they exist means that when you have an idea, there is probably a tool that can help you make a first version.

The creative explosion

Thousands of AI startups, not a handful of labs

The frontier labs set the pace, but thousands of companies launched in the same wave as ChatGPT and build on their advances across every vertical and creative field. Tracxn counts 4,511 generative AI companies — 1,026 funded and 62 unicorns — with 1,532 in the US, 426 in India, and 242 in the UK.

9,889Generative AI organizations on CrunchbaseAverage founding date: Aug 2021
6,343Funding roundsWorth $557.4B total across generative AI
$122BOf $211B in 2025 AI venture funding went beyond the foundational labsThe labs took $88.9B across 66 deals

Frontier AI didn’t just make chatbots. It made creators of all of us.

Suno

Full songs from a prompt

ElevenLabs

Cloned voices, characters

Riverside

Podcasts and studio video

Canva

AI-assisted design tools

Lovable

Web apps, no code needed

NotebookLM

Documents to podcasts and study guides

Takeaway: What once required a team, a budget, and training now requires a prompt and a vision. (Crunchbase and Tracxn define the category differently, so their totals differ. Both point to thousands.)

Sources: Crunchbase generative AI hub (full-year 2025 data); Tracxn (as of Oct 2026).

An explosion of creative tools: cameras, brushes, instruments, and laptops

In plain termsTools like Lovable (apps), Riverside (podcasts and video), and Suno (music) let one person do work that once took a team. Notice the pattern: the creator brings the idea and the editing judgment, and the tool handles the heavy production work.

Creator toolkit spotlights

Lovable, Riverside, and Suno

Three tools that show how one person can now do the work of a full team.

The builder: Lovable — a plain-language idea into shipping software

Plain-language building

Describe it, and it builds with you.

Real apps, not prototypes

Screens, data, logic, and authentication.

Hosting included

Hosting, SSL, and backend infrastructure handled.

Payments worldwide

Handled in 200+ countries and territories.

Connects to your stack

Integrations with no integration code.

Secure by default

Security scanning and audit logs built in.

Riverside: one person, a full production crew

  1. 1
    Recording engineer

    Studio-quality 4K video

  2. 2
    Editor

    Edit video like a document

  3. 3
    Sound engineer

    One-click audio cleanup

  4. 4
    Translator

    Transcripts in 100+ languages

  5. 5
    Distributor

    Stream and publish anywhere

Suno: a plain-language idea into a finished song

Describe your song

Pick a genre, mood, or theme, or bring your own lyrics.

A full song in one prompt

Vocals, instrumentation, and production in under a minute, in every genre.

Clearer, more immersive audio

Model v5 brings natural vocals and better mixing.

Regenerate, extend, refine

Iterate from any take until the song feels right.

Beats and instrumentals

Works as a beat maker and instrumental generator too.

Control every element

Tune tempo, key, dynamics, and arrangement, or remaster old tracks.

Takeaway: Why it matters: anyone who can describe an idea can ship software or a song — imagination, not technical training, becomes the requirement.

Sources: Lovable (works for web, desktop, and mobile; used by teams at Adidas, Asana, ElevenLabs, Zendesk, Workday, and Nvidia; your code and data stay yours); Riverside; Suno (web and a top-10 music app on iOS and Android, featured in Rolling Stone, Billboard, Wired, and Variety).

Check your understanding

1. You need music, images, and a short video for a project. What’s realistic now?
2. What do skilled AI creators’ workflows have in common?