By: Jim Freeman
Generative AI is revolutionizing the way we work, and I’ve seen its impact firsthand in recent months.
I have worked with many clients over the years, advising them on navigating digital transformations, but a recent experience with generative AI showed me just how powerful this technology can be. This isn’t some distant future — it’s happening right now, and for enterprise leaders, it can be a game-changer.
Customer use case
Case in point: my team faced a significant challenge while building a cloud-based architecture for a major client.
We developed the solution to meet all of the technical requirements. However, when we tried to move that environment to the client’s cloud, we hit a roadblock. The architecture was packed with hard-coded dependencies tied to our lab environment — dozens, if not hundreds, of them. It became clear that something had to change, fast, if we wanted to avoid delays and budget overruns.
We needed a radical solution. I turned to generative AI — in this case, an instance of Microsoft Copilot, which adheres to Kyndryl’s Responsible AI policy.
I uploaded the Azure Resource Manager templates—which did not include customer data—to Copilot and asked the tool to identify the hard-coded variables and refactor them into parameter files (OpenTofu), which it did, no problem. It also generated Ruby scripts to help manage and organize those files. In a matter of hours, what had seemed like an insurmountable problem was solved.
Generative AI’s ability to handle such a complex issue so efficiently was surprisingly impressive. The experience highlighted for me how far AI has come in such a short time. The technology not only saved us weeks of manual work, but it also demonstrated how generative AI can soon become an essential part of an enterprise.
More than just code
What makes generative AI a truly transformative tool is its versatility. It can not only refactor code, but it can also become a pair programmer for application development teams.
When developers face obscure errors, instead of waiting to consult a senior colleague, they can turn to generative AI tools. By pasting the error message into the generative AI input field, they can receive immediate suggestions. It isn’t just about speeding up coding—it can fundamentally change how we approach problem-solving.
Generative AI can suggest better ways to manage files and workflows, helping improve operational efficiency. These gains allow teams to shift focus from firefighting to driving long-term, strategic initiatives.
For enterprise leaders, these productivity gains can translate directly into accelerated timelines and cost savings.
