Today, I would like to introduce the contents related to the hot topic ai these days. We will look at how businesses are formed in the AI supply chain and successful development cases using the ai agent.
It is organized so that even those who are not familiar with ai can understand it easily, so if you are interested in the recent trend, please stay with us until the end.
Supply Chains of AI Development Companies
AI companies rely on a complex supply chain that includes:
1. Semiconductor & Hardware Providers
- These are the companies that make GPUs and chips needed to train and run AI models.
- Key players:
- NVIDIA: Owns ~92% of data center GPU market.
- AMD, Intel: Competing players.
- These chips power everything from AI training to in-production agents.
2. Software & Tooling Platforms
- These companies provide the AI frameworks and model training environments.
- Examples:
- OpenAI, Google (Gemini), Anthropic (Claude): Provide foundation models.
- Microsoft: Offers model hosting and tooling (via Azure).
- Microsoft holds ~39% share in foundation model and AI tooling market.
3. Cloud Providers
- AI runs on cloud infrastructure for scalability.
- Leaders: Amazon AWS, Google Cloud, Microsoft Azure.
4. Data Providers
- AI agents need lots of training data, often gathered from public sources, web scraping, or partnerships (e.g., Reddit, StackOverflow, etc.).
Market Share Across Industries AI adoption varies by industry:
- Manufacturing: In 2024, the manufacturing sector is expected to account for 23.1% of the AI in supply chain market.
- Retail: The retail sector is projected to register the highest CAGR of 47.8% during the forecast period 2024–2031.
- Supply Chain Management: The AI in supply chain market is projected to grow from USD 9.15 billion in 2024 to USD 40.53 billion by 2030, at a CAGR of 28.2%.
Regional Insights AI market dynamics also vary by region:
- North America: Held a 38.4% share of the AI in supply chain market in 2023, driven by intense competition and the need to reduce costs while maintaining high customer service levels.
- Asia-Pacific: Expected to account for 36.9% of the AI in supply chain market in 2024, with countries like China emphasizing automation and smart manufacturing.
Understanding these supply chains and market shares is crucial for comprehending the AI industry’s structure and its impact across various sectors.
Real Examples of AI Agents Making Money (with Pricing, Users & Revenue Info)
AI agents are smart programs that can think, plan, and act like helpful assistants. They can write code, book meetings, respond to emails, or even research things for you — all with very little human help.
Let’s look at real businesses using AI agents to make money and grow fast:
1. Devin (by Cognition) – The AI Software Developer
- What it does: Devin can build entire software apps, fix bugs, read job requirements, and even submit code to GitHub – like a real junior developer.
- How it’s used: Companies can give it programming tasks and it completes them from start to finish.
- Pricing: $500 per user per month (targeted at businesses).
- Users: Exact number is not public, but it’s being tested by software companies.
- Money raised: Over $215 million in funding, with a company value of around $2 billion.
2. MultiOn – Personal Web Assistant
- What it does: MultiOn can book flights, schedule meetings, send emails, and browse websites for you — just by typing what you want.
- How it’s used: Like a superpowered AI that clicks and types across websites for you.
- Pricing: Not fully public yet, but expected to offer premium plans.
- Users: Thousands of people signed up for early access (waiting list).
- Money raised: Reportedly raising $20 million from investors.
3. Lindy AI – AI Assistant for Professionals
- What it does: Lindy can handle your email inbox, schedule meetings, write summaries, and more — basically acting like a full-time executive assistant.
- How it’s used: Busy professionals and teams use it to save time on daily tasks.
- Pricing: Not officially public, but likely subscription-based (SaaS model).
- Users: Not publicly disclosed.
- Money raised: Backed by major VC firms like Sequoia and a16z with multi-million dollar investments.
4. Fixie – AI That Talks to APIs
- What it does: Fixie lets you create an AI agent that can talk to your company’s tools (like databases, CRMs, calendars) and automate tasks across them.
- How it’s used: Businesses use it to handle repetitive operations or customer support tasks.
- Pricing: Pay-as-you-go based on how much the AI is used.
- Users: Early adoption by tech startups and small companies.
- Revenue: Not publicly shared, but positioned as a B2B product.
5. AutoGPT / AgentGPT – Goal-Oriented AI Agents
- What it does: You give it a goal like “build a blog” or “find 10 suppliers,” and it figures out all the steps — research, planning, writing — and does them.
- How it’s used: Tech-savvy users and developers use it to automate personal projects or test business ideas.
- Pricing: Free to try, with paid plugins and premium tiers for more power.
- Users: Popular on GitHub and social media with thousands of downloads and users.
- Revenue: Monetized through premium tools, add-ons, and pro versions.
6. Elicit (by Ought) – Research Assistant for Scientists & Teams
- What it does: Elicit reads scientific papers, summarizes findings, and helps users find trusted research — all powered by AI.
- How it’s used: Used by researchers, students, and data analysts.
- Pricing: Offers a freemium model, with premium options for teams and businesses.
- Users: Widely adopted by universities and research orgs.
- Revenue: Business subscriptions and partnerships with research institutions.
What’s Next for AI Agents?
The future of AI agents is moving fast. Here’s where it’s heading:
| Trend | What It Means |
| 1. Teamwork between AI agents | Multiple agents will work together like a human team — one plans, one acts, another checks the result. |
| 2. Real-time decisions | Agents will react to live data (finance, delivery, security) and act immediately. |
| 3. Industry expertise | Specialized agents will be built for fields like law, medicine, education, or real estate. |
| 4. Long-term memory | Agents will remember past actions and improve as they go, working toward big goals. |
| 5. Anyone can use them | No coding needed — you’ll just describe what you want in plain English. |
Business Ideas Using AI Agents
Thinking about building something yourself? Here are some ideas:
- For small businesses: An AI agent that handles bookkeeping, customer support, or HR.
- For job seekers: An AI coach that rewrites resumes and applies to jobs for you.
- For e-commerce sellers: An agent that replies to customers and tracks inventory.
- For legal professionals: An AI that reads contracts and highlights important terms.
Key Takeaways
- AI agents are no longer just experimental — they are being sold as real products with clear pricing and customer bases.
- The AI industry depends on a complex supply chain, including GPUs, cloud infrastructure, training data, and model providers.
- Adoption is booming in manufacturing, retail, supply chain, and enterprise productivity tools.
- New startups are emerging rapidly by combining open-source models + SaaS pricing + vertical focus.