AI Isn’t Out of Reach: From Graduation to My First Real-World AI Project

In 2024, I walked across the stage and accepted my degree excited, relieved, and full of questions about what would come next. Like many new graduates, I knew the technology world was moving fast, especially in artificial intelligence. What I didn’t realize was how quickly AI would become part of my everyday work, or how accessible it would feel once I finally stepped into a real-world environment.

My First Real-World AI Project

My first major assignment at RBA was ambitious: helping build an AI-powered chatbot entirely within the Microsoft ecosystem. Using tools like Power Apps, Power Automate, Copilot Studio, and Azure AI Foundry, our goal was to create something that would genuinely help RBA employees in their day-to-day work.

We envisioned a single intelligent assistant capable of:

• Logging work summaries naturally through text or voice
• Extracting key details such as client, technology, goals, and outcomes
• Identifying who across the organization has experience with specific tools or projects
• Supporting resume and experience generation
• Sending reminders to keep work logs updated
• Acting as a centralized knowledge hub for the entire organization

This wasn’t just another internal application. It was a step toward a smarter, more connected workplace. 

Learning Through Building

This project was my first true opportunity to apply what I learned in school to real business problems, and I loved every second of it.

Each challenge introduced something new, whether it was a quirk in how Power Automate handled data, a limitation in an AI model that forced us to rethink our approach, or a breakthrough moment when something finally worked after hours of testing.

Seeing ideas turn into features, and features turn into a functioning system, was incredibly motivating. Presenting my work, collaborating with my team, and watching the solution come together reminded me exactly why I wanted to work in technology.

Navigating Costs, Change, and Constant Reinvention

One of the biggest surprises during this project was realizing just how dynamic the AI landscape really is. Tools evolved quickly, features shifted, and interfaces changed sometimes weekly. Capabilities in Copilot Studio could appear or behave differently almost overnight. This forced me to stay flexible, challenge assumptions, and continuously rethink parts of the solution as the ecosystem matured.

Another key learning was understanding the cost side of AI development. Experimenting with different models in Azure AI Foundry was exciting, but it also introduced real pricing considerations. I learned how to evaluate which models were necessary, which were overkill, and where we could balance performance with budget. That experience showed me that responsible AI development requires both creativity and cost awareness.

I also gained a deeper appreciation for the value of licensing within the Microsoft stack. With a single license, I could work across Power Apps, Power Automate, Copilot Studio, and more. Instead of juggling multiple vendors or disconnected tools, the unified ecosystem made it easier to build a cohesive, end-to-end solution without unnecessary overhead.

AI Is Here, and It’s Accessible

The biggest lesson I took away from this experience is simple: AI is not out of reach.

You don’t need to be a machine learning expert to get started. You don’t need to build everything from scratch. Today’s AI tools, especially within the Microsoft ecosystem, significantly lower the barrier to entry. Anyone with curiosity and creativity can begin building meaningful, real-world solutions.

AI isn’t the future. It’s the present. And it’s something anyone can learn, experiment with, and contribute to.

That realization shaped my entire first year out of college, and it continues to influence how I approach every new problem. If you’re willing to learn, experiment, and get your hands dirty, AI becomes a playground, not a gatekeeper.