Blink once, and artificial intelligence has already taken another leap forward. We sat down with Oleksandr Myroshnychenko—Manager of Training & Research and head of AMC Bridge’s AI Center of Excellence—to explore how the Center tracks those rapid advances, turns buzz into practical tools, and invites every team to use AI safely and responsibly. Whether you’re already experimenting with AI tools or just curious about what’s next—this is your inside look at how AMC Bridge is navigating the fast-moving world of AI.

AI Moves Fast—Blink and You’ll Miss It

AI is everywhere. It’s becoming part of our daily lives—both in how we live and how we work. And since we’re not just any IT company—we develop engineering software—AI is becoming increasingly relevant in our field as well. That’s why the idea of establishing a dedicated center came about: to keep up with what’s happening in AI, to analyze it, and to make sure our company benefits from it.

The pace of development in this field is staggering. You see five major updates in a single week, and by the time you catch your breath, last month’s breakthrough is already outdated. So we needed a place to collect, process, and distribute information across the company. That’s where our AI Center of Excellence comes in.

What We Do

From the beginning, we set clear goals for the Center. The first is innovation and research. Whenever a new technology or tool appears, we evaluate whether it’s relevant to engineering software. If it is, we study it and share our conclusions.

The second focus is training. One of our tasks is to show everyone how valuable and helpful these tools can be. AI won’t replace developers, but it can take over repetitive, simple tasks and save a lot of time. It just doesn’t make sense to ignore it.

We also work on improving internal processes. As developers, we now have access to tools like GitHub Copilot®, Amazon CodeWhisperer™, and Tabnine™, etc. Everyone’s talking about it—and for good reason. It’s not a magic solution, but it really speeds things up. Instead of writing the same boilerplate code over and over, you can get it done in a couple of clicks. That’s the kind of improvement we aim to bring into our workflows.

Another important part of the Center’s work is providing consultations. We collect insights from both the industry and our own internal experience, and we share relevant information through various channels—whether it’s direct requests from teams, or insights we proactively distribute. For example, we’ve had several projects involving computer vision. On one of them, we were pioneers. When a similar project came up later, we were able to guide the team using the lessons we’d already learned. That’s what we’re here for—to help avoid the same mistakes and move faster.

In addition to consultations, we collect and manage data. We analyze statistics, conduct research, and share the results through internal seminars, strategic sessions, and other formats. There’s a lot of work involved in gathering this information and making sure it’s accessible to everyone.

Collaboration Across the Company

The AI-CoE was never meant to work in a vacuum. Early on, we built a company-wide network of “champions.” Each department and key team, from Delivery and PMO to Functional Offices, has a champion who exchanges questions, ideas, and updates with the Center. They carry fresh insights back to their teams and bring new challenges to us for research or advice. It’s a two-way channel that keeps information flowing and ensures every team can tap into the Center’s resources.

Often, research topics come directly from the field. A Delivery Manager might face a challenge with a specific technology and bring it to me. From there, we prioritize the request and carry out the research using a structured approach, answering key questions to guide our conclusions. If you spot an AI opportunity (or roadblock) on your project, reach out to your champion—or directly to me—and let’s tackle it together.

Practical Use and Success Stories

We approach AI in two ways. First, as a tool to improve how we work. Tools like GitHub Copilot, ChatGPT™, Midjourney™, or Claude™ are already in use by developers, designers, and even content creators. In this area, the Center helps with information gathering, evaluation, and implementation.

Second, we look at AI as a core technology—a central element of certain projects. For example, with our computer vision projects, the first implementation taught us a lot. When a new project started, the team was able to benefit from those previous lessons. That’s a real success story—using AI to improve both our work and how we deliver solutions to clients.

Legal and Client Communication

Of course, AI implementation brings legal questions. And we don’t take a single step forward without our legal team and customer approval. Before we use any tool in a client’s project, the legal team reviews all documentation and coordinates with the client. There are strict rules, and we follow them closely. Nothing gets implemented unless it’s officially approved.

Sometimes we help managers prepare performance justifications for clients—showing them market data and internal research that proves certain tools improve performance. But even then, it’s up to the client. If they agree and sign the documents, we proceed. If not, we don’t use it. It’s as simple as that.

From what I’ve seen, most clients are open to AI, especially when they see the benefits. Others are more cautious, some have much tighter restrictions, and AI is strictly prohibited. That’s understandable. In general, though, the trend is clear: interest in AI is ever-growing.

AI with a Grain of Salt—Staying Curious, Staying Grounded

Let’s be honest—there’s a lot of noise out there. Every day, we hear about the next big AI breakthrough, the next tool that promises to change everything, or bold claims that AI will soon replace entire professions. And while some of that is just hype or clever marketing, it doesn’t mean there’s no truth beneath it. The potential of AI is real—but only when it’s applied correctly, to the right problems, and in the right way.

To figure out where AI makes sense, you have to look at what your application does—and what AI actually does well. For instance, AI is particularly strong at interpreting and understanding human language. So, it’s not uncommon to enhance 3D web applications by adding the ability for users to interact through natural language requests—not just through static buttons or 3D UI elements. That kind of integration can simplify interaction, speed things up, and make the application more accessible overall. That’s why our approach is both curious and cautious: we stay open to innovation, but we also apply a critical lens. Hype fades—real value lasts.

Risks, and Reality Checks

There are definitely challenges. The biggest one is the speed of AI development. Keeping up with everything is difficult, and it takes a lot of effort to stay current.

We also face the well-known issue of AI errors—so-called “hallucinations.” AI can make mistakes, even in math. That’s why we always say: don’t blindly trust it. Think critically. Even so, using AI still saves time compared to doing everything manually. It’s a powerful tool, but it needs to be used responsibly.

Looking Ahead

Our main goal now is to make AI tools part of the daily routine for everyone at AMC Bridge—not just developers, but QA and non-technical staff too. Using AI should become as normal as using a search engine.

We also want to expand the number of projects where AI is the core technology. That’s the direction we see for the future. And we already have projects where AI plays a central role, even if I can’t share all the details here. What’s important is that we continue moving forward, learning, sharing, and applying AI in ways that help us all work smarter.

All third-party trademarks belong to their respective owners. For more details, please refer to the Third-Party Trademarks list on the Privacy and legal notices page.