AI in Music and Art

Introduction

Many people assume data analysis requires advanced tools like Python, R, SQL, or machine learning. While those tools are valuable, meaningful insights can often be uncovered using nothing more than Excel.

To demonstrate this, I conducted a survey exploring public attitudes toward artificial intelligence in music and art. The survey collected 58 responses from creators and consumers and asked questions about AI-generated content, artistic value, disclosure, and creative authenticity.

The goal wasn't to create a statistically significant research study. The goal was to practice the fundamentals of data analysis:

• Collecting data

• Organizing information

• Segmenting audiences

• Comparing groups

• Identifying trends

• Drawing conclusions

Everything in this analysis was performed using Microsoft Excel.

Step 1: Start with a Question

Every analysis begins with a question.

In this project, the primary question was:

"As AI becomes more prevalent in creative work, does it threaten the value of human-created art or help elevate it?"

This broad question was broken down into several smaller questions:

• How familiar are people with AI creative tools?

• Do people consider AI an artist?

• Would people pay for AI-generated content?

• Do creators view AI as a tool or competition?

• Is disclosure important?

Step 2: Collect the Data

The survey gathered:

• 58 responses

• Consumers and creators

• Quantitative responses

• Qualitative comments

Once collected, the responses were imported into Excel where the data could be sorted, filtered, and analyzed.

Step 3: Segment Your Audience

One of the most useful techniques in data analysis is segmentation.

Rather than treating all respondents as one group, I separated the data into:

• Creators

• Consumers

This immediately made the analysis more meaningful because it allowed direct comparison between groups.

Why It Matters

Averages often hide important differences.

Segmenting data reveals how different audiences think and behave.

Step 4: Look for Patterns

Awareness of AI Content

The first observation was that both groups were highly aware of AI-generated music and art.

• Consumers: 88%

• Creators: 76%

This suggests AI-generated content has already reached mainstream visibility.

Familiarity with AI Tools

Most respondents indicated they were at least somewhat familiar with tools such as:

• ChatGPT

• MidJourney

• Suno

• AIVA

• Consumers: 67%

• Creators: 65%

This tells us that opinions are generally being formed by people who have at least some exposure to AI technology.

Sentiment Toward AI

The data revealed a mixed response toward AI-generated creative work.

• Consumers: 42% negative

• Creators: 41% negative

While acceptance exists, skepticism remains strong.

Step 5: Compare Opinions

Can AI Be Considered an Artist?

This question produced one of the strongest findings.

• Consumers saying "No": 63%

• Creators saying "No": 88%

Creators were particularly resistant to granting AI the status of artist.

This demonstrates how audience segmentation can reveal differences that may otherwise be hidden.

Would People Pay for AI-Generated Content?

The majority of respondents would not.

• Consumers: 63%

• Creators: 71%

This finding suggests that audiences still place greater value on human-created work.

Human-Created vs AI-Created Value

Respondents consistently valued human-created work more highly than fully AI-generated work.

• Consumers: 63%

• Creators: 64%

This trend appeared throughout the survey.

Step 6: Analyze Open-Ended Responses

Numbers tell part of the story.

Comments often explain why people answered the way they did.

Several recurring themes appeared:

Theme 1: AI as a Tool

Many creators saw AI as useful for:

• Brainstorming

• Concept generation

• Productivity

Theme 2: Authenticity Matters

Many respondents felt that human experiences and emotions give art its value.

Theme 3: Transparency is Important

Many respondents wanted disclosure when AI was involved.

This demonstrates a common qualitative analysis technique:

• Read responses

• Identify recurring themes

• Group similar opinions together

Step 7: Draw Conclusions

After reviewing the data, several conclusions emerged:

Finding #1

AI awareness is already widespread.

Finding #2

Most respondents do not view AI as a true artist.

Finding #3

Human-created work continues to hold greater perceived value.

Finding #4

Creators view AI as both a helpful tool and a competitive threat.

Finding #5

Transparency around AI usage is important to most people.

What This Project Demonstrates

This project wasn't just about AI.

It was about practicing data analysis.

Using only Excel, I was able to:

• Organize survey data

• Segment audiences

• Compare groups

• Calculate percentages

• Visualize findings

• Analyze qualitative comments

• Present actionable insights

These same skills are used every day by business analysts, marketing analysts, project managers, and operations teams.

You don't need advanced tools to begin analyzing data.

You simply need a question, a dataset, and the curiosity to explore what the data is trying to tell you.