NBCUniversal Innovation & Technology Culture

What tools support your day-to-day work?

At the core of any productive team is a toolset that’s intuitive, reliable and secure. It should be tools that people actually want to use. For planning and visibility, we rely heavily on platforms like Jira. It serves as our central hub for organizing work, managing sprint cycles and coordinating production releases. Just as importantly, it gives stakeholders a transparent view into progress, helping bridge the gap between engineering and product teams. 

Alongside traditional tools, AI has quickly become an everyday companion in the workplace. Solutions like Microsoft 365 Copilot are particularly impactful. Because they’re embedded directly into familiar applications, they can assist with drafting emails, summarizing content and even helping to structure documents or technical solutions. Beyond productivity tools, AI capabilities within cloud platforms are advancing rapidly as well. Whether it’s integrated assistants in data platforms or cloud-native AI services, these tools are becoming more refined with each release and are helping teams accelerate development, improve documentation and uncover insights faster.

And despite all of this innovation, one thing hasn’t changed; the good ole’ spreadsheet still holds its ground. When it comes to quick collaboration, data validation or aligning on assumptions, a well-structured Excel file remains one of the most effective tools available. 

How does your team experiment?

Experimentation is essential, but it works best when it’s intentional. For us, experimentation starts in controlled environments like sandbox datasets or isolated cloud projects. These spaces allow teams to explore new ideas without impacting production systems or sensitive data. The goal is always the same: Learn quickly, but do it safely and transparently. AI is playing a growing role here as well. It can help teams rapidly generate potential solutions, identify edge cases and even highlight risks early in the process. In many cases, what previously took days of iteration can now be explored in hours. 

That said, speed doesn’t replace discipline. Every experiment is documented, and results, both successes and failures, are shared with the broader team. This ensures that knowledge compounds over time rather than staying siloed. Choosing the right tool is also critical. The wrong tool can slow things down more than it helps. For example, imagine trying to use a general purpose business intelligence dashboard tool to build a large-scale data pipeline. While the tool might allow limited data transformations, it’s not designed to handle complex dependencies, scheduling or large data volumes. The result is often fragile workflows, performance bottlenecks and increased maintenance overhead. A dedicated data engineering framework, on the other hand, is purpose-built for that scale and complexity. Experimentation should challenge assumptions but still respect the fundamentals of good engineering design. 

How does NBCUniversal adapt to change?

Adapting to change isn’t a one-time effort — it’s a continuous mindset. Within our organization, staying “in the know” is a shared responsibility. Teams regularly exchange ideas through forums, internal communities and peer-led sessions, known as engineering guilds, where engineers showcase what’s working in real-world scenarios. This kind of knowledge-sharing helps accelerate adoption and builds confidence across the organization. 

Knowledge-sharing around AI has been a key driver of conversation and focus for our teams over the past two years. Engineers actively exchange ideas through live “show-and-tell” demonstrations and Confluence documentation, where practical use cases and lessons learned are shared in real time. This collaborative approach is paired with structured upskilling opportunities, including vendor-led sessions, hands-on working labs and internal AI bootcamps that allow teams to learn by doing. Engineers also stay current by attending industry conferences where emerging AI capabilities are showcased along with practical ways to integrate them into existing architectures and data pipelines based on specific business needs.

In addition, NBCUniversal offers a broad suite of training resources designed to meet teams where they are in their AI journey, which includes free LinkedIn Learning pathways, curated office hours and town halls that highlight real-world AI applications. One standout experience that I enjoyed was the Microsoft-led Copilot office hours, where experts guided individuals through foundational and advanced use cases in an open, interactive setting. These sessions helped employees build practical skills, which enabled us to confidently incorporate AI into our day-to-day workflows.

This approach had an immediate impact. It enabled engineers to integrate AI into their workflows quickly and safely by using it to streamline development, improve documentation and reduce repetitive tasks. At the same time, it created a foundation for building internal AI solutions tailored to our specific needs. 

More importantly, it positioned the organization to lead rather than follow. By combining governance with enablement, we’re not just adopting new technology; we’re helping define how it can be used effectively, responsibly and at scale within the media and entertainment industry.