12 Generative AI Examples Businesses Use Today

What is generative AI?

Generative AI is software that produces new content, such as text, code, images, audio, or summaries, in response to a prompt. It is built on large models trained on very large sets of existing material. A prompt is the instruction you give it, for example “summarize this support ticket in two sentences and suggest a reply.” Non-generative AI examples are systems that sort, score, or predict rather than create: a spam filter, a credit risk score, or a demand forecast.

What are 12 examples of generative AI in business?

These generative AI examples are grouped by the job they do. Where a company published a result, it is attributed to the company.

Customer service

1. Klarna AI assistant

On February 27, 2024, Klarna announced that its AI assistant had handled 2.3 million conversations in its first month, two-thirds of its customer service chats. Klarna said that was the equivalent work of 700 full-time agents, that it worked in more than 35 languages across 23 markets, and that resolution time fell to under two minutes from 11. It also reported a 25% drop in repeat inquiries and estimated a $40 million profit improvement for the year. All of these are Klarna’s claims. The lesson is the scope: a narrow, high-volume job with clear policies.

2. Intercom Fin

Fin answers customer questions from your help content and can hand off to a person. Its notable feature is the price: $0.99 per outcome, so you pay when the issue is resolved rather than per seat. That makes it easy to compare with the cost of a human-handled ticket. See our AI chatbot examples for more support bots.

3. Salesforce Agentforce

Agentforce puts autonomous agents inside Salesforce for sales and service work. Salesforce says more than 18,000 companies use it, which is a vendor claim. Pricing comes in several forms: Flex Credits, per-resolution, and per-user. If you run Salesforce already, the data access is the advantage; if not, it is a large commitment for one use case. Our best AI agents for business guide compares the options.

Software and e-commerce

4. GitHub Copilot

Copilot suggests code, explains it, and answers questions in the editor. The free tier includes 2,000 completions. GitHub says developers using it can be up to 55% more productive, based on its own research, so test it on your own codebase before you believe the number.

5. Shopify Sidekick

Sidekick is the assistant inside Shopify admin. It answers questions about your store and helps with tasks such as drafting content and setting up reports. It is included with the Shopify plan, though usage limits vary. For store owners, it is the lowest-risk way to try generative AI because it works on data you already own. Our guide to AI in ecommerce covers the rest of the store.

Creative and learning

6. Adobe Firefly

Firefly generates images and design assets. Adobe says it trains on licensed Adobe Stock and public domain content, which matters if your legal team worries about copyright. Paid plans are listed at $9.99, $19.99, and $49.99.

7. Duolingo Max

Announced on March 14, 2023, Duolingo Max uses GPT-4 to power Roleplay conversations and, later, Video Call practice with feedback. It shows a consumer product where the model is a feature inside a larger product, not the product itself.

Productivity and research

8. Notion AI

Notion AI writes, summarizes, and searches inside a workspace. It is included in the Business plan, which lists at $20 per seat. It works because the content already lives in Notion.

9. Microsoft 365 Copilot

Copilot drafts documents, summarizes meetings, and analyzes spreadsheets across Microsoft 365. It is listed at $21 per user per month, with a promotional $18 price through December 31, 2026. Bundles are listed at $23.50 and $32.

10. Gemini in Workspace

Google’s equivalent adds Gemini to Docs, Gmail, Sheets, and Meet. The choice between this and Copilot usually follows the suite you already use, not the model.

11. Perplexity

Perplexity answers questions with cited sources, which makes it useful for research where you need to check the origin. Enterprise plans add team controls.

12. ChatGPT Business

ChatGPT is itself an example of generative AI, and the Business plan is the team version, with admin controls and workspace management. If you want to compare it with other assistants, see our Claude alternatives roundup.

Generative AI prompt examples

A good prompt names the task, the audience, the source, and the format. These examples work in most tools:

• Support: “Using only the refund policy below, draft a reply to this customer. Keep it under 120 words and offer one next step.”
• Sales: “Summarize this call transcript into three objections and one follow-up question for each.”
• Operations: “Turn these meeting notes into a table of owner, task, and due date.”
• Code: “Explain what this function does, then write two unit tests for the edge cases.”

How do businesses use generative AI?

The use cases of generative AI in business fall into four groups: answering questions (support and internal help), drafting content (marketing, proposals, emails), working with code (completion, review, tests), and summarizing information (meetings, documents, research). Each of the examples above is one of these. Pick the group where your team spends the most repeated time.

How do you choose a generative AI tool?

1. Name the job. One task with a clear before and after.
2. Check where the data lives. A tool inside the system that holds your data beats one that needs exports.
3. Compare the pricing model to the work. Per-outcome suits support, per-seat suits individual productivity.
4. Keep a human on exceptions. Review anything customer-facing until error rates are known.
5. Run a pilot against a baseline before you roll it out.

When off-the-shelf tools do not fit, you can build your own. Our guides on building an AI agent, AI agent builders, AI agent examples, and AI tools for small business go deeper.

If you want a team to design and build it, see our generative AI development services, agentic AI development services, and AI development services.

Frequently Asked Questions

What are examples of generative AI?

Common examples are ChatGPT, Microsoft 365 Copilot, Gemini, GitHub Copilot, Adobe Firefly, Notion AI, Intercom Fin, and Klarna’s customer service assistant. Each creates text, code, images, or answers from a prompt.

Is ChatGPT an example of generative AI?

Yes. ChatGPT generates text in response to prompts, which is the definition of generative AI. It runs on large language models trained on large amounts of text.

Which companies use generative AI?

Klarna, Duolingo, Shopify, Salesforce, Microsoft, Google, Adobe, and GitHub all ship generative AI features. Many other companies use them through tools such as Copilot, Notion AI, or Fin.

What are non-generative AI examples?

Non-generative AI classifies, scores, or predicts instead of creating content. Examples are a spam filter, a fraud score, a recommendation ranking, and a demand forecast.

What are the use cases of generative AI?

Customer support answers, marketing and sales drafts, code completion and review, meeting and document summaries, and research with cited sources. Pick the one where your team repeats the most work.

What are good generative AI prompt examples?

A good prompt states the task, audience, source material, length, and format. For example: “Using only the policy below, draft a reply under 120 words and offer one next step.”

How much does generative AI cost for a business?

It depends on the model. Intercom Fin charges $0.99 per outcome, Microsoft 365 Copilot lists at $21 per user per month, and Notion AI is included in the $20 Business plan. Compare the pricing model to the work you want done.

Are the results companies report reliable?

Treat them as company-reported. Klarna, GitHub, and Salesforce published their own figures, and none of them is an independent audit. Run a pilot on your own data before you rely on them.

Do I need to build my own generative AI tool?

Not usually at first. Start with a tool that fits one job. Build custom when your data, workflow, or privacy needs are unusual, or when you need to connect the model to several internal systems.

Bottom Line

The generative AI examples that work are narrow, connected to the company’s own data, and reviewed by a person. Start with one job such as support replies, code review, or document drafting, compare the pricing model to the work, and measure against a baseline. To build something tailored to your systems, talk to us about generative AI development services.

Hardik Surana

Customer Success Manager

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As a Customer Success Manager, I specialize in bridging the gap between structured execution and long-term strategic growth. Drawing on my extensive background in traditional project management and account oversight, I ensure our clients don't just hit milestones, but achieve measurable business outcomes. My approach is rooted in providing a seamless transition from implementation to partnership, leveraging my technical discipline to anticipate challenges before they arise. I am committed to acting as a dedicated advocate for my customers, turning complex requirements into streamlined paths for success. By blending operational rigor with a relationship-first mindset, I focus on driving the continuous value that keeps our partners thriving.