How AI Breaks the Business Case Rule (And Why That's Actually Good)

Most of the time, I try to resist shiny object syndrome.

New tech comes out, everyone loses their minds, and we end up with a graveyard of half-baked prototypes that never see the light of day. So my default posture—especially as a CTO—is to lead with business problems. 

What’s the actual pain point? 

Where are the opportunities for value creation? 

The tail shouldn’t wag the dog.

But AI is a bit different.

It’s a foundational shift in how we interact with software—and how software interacts with the world. And because the space is changing so quickly, starting with the tech might actually be the smart move.

Not in a “let’s install this for funsies” way, but in a deliberate exploration of what’s newly possible. 

That phrase—the art of the possible—has become a sort of North Star for how I think about generative AI.

The key insight here is that GenAI often creates the business case, rather than the other way around, because before AI, some things simply weren’t possible. Or, they weren’t possible at scale. 

I know this isn’t how we typically suggest folks think about AI. But I promise I have a point here! Let me explain.

GenAI Made Global Expansion a Possibility 

We’ve seen this “Art of the Possible” with several of our customers. Take MagellanTV, for instance. 

Their team came to us with a big ambition: expand their library of documentaries to reach a global audience. That meant captioning and dubbing thousands of hours of English-language content into languages like Spanish and Mandarin. Previously, they planned to rely on a mix of third-party services and manual editing. Because the process was time-consuming, expensive, and hard to scale, MagellanTV considered the project to be impossible from a business perspective.

We worked with them to design a GenAI-powered pipeline built entirely on AWS-native services—Transcribe, Translate, Polly—and tied it all together with SageMaker and a large language model from Bedrock.

This involved full automation of transcription, translation, slang detection, summarization, speech synthesis, and dubbing—down to the sentence level. Need a sentence sped up to match the cadence of the original English clip? No problem. Need to rewrite a line because the translated version feels awkward or unnatural? The LLM handles that too. And because this solution was part of the AWS Migration Acceleration Program (MAP), it was cost-optimized from day one.

This wasn’t even the project they originally approached us about. It started with cost optimization. But once we saw what they were trying to achieve, we brought a GenAI lens to the conversation. That changed everything.

This is what I mean by “the art of the possible.”

Curiosity vs. KPIs

Oftentimes, the most impactful projects come from curiosity versus KPIs. They start with “What if…” questions like:

“What if we didn’t have to do this manually?”
“What if we could serve a whole new customer segment?”
“What if we completely rethink how this workflow works?”

So yes—AI is different. And it requires a different posture.

If you’re waiting for a fully scoped use case and a guaranteed ROI before you engage with GenAI, you’re going to miss the window. The leading companies in this space are already experimenting, already learning, already integrating. Not because they have to—but because they can.

If you're ready to explore what’s possible, now’s the time!