AI in Streaming Is the New Snake Oil

Let’s call this what it is: AI has become the snake oil of the streaming industry.

Sold as the answer to every problem—churn, stagnation, bad UX, too many rom-coms and not enough retention—but under the hood, most companies are still running on duct tape, prayer, and dashboards built in 2017.

Every pitch deck now has a slide that screams “AI-powered personalization!” or “predictive churn prevention!”—meanwhile, half the platforms Kirby Grines surveyed in TheStreamingWars' study still can’t track a user across devices. You start watching The Bear on your tablet, finish it on your Roku, and your platform assumes two different people are watching—one into gritty chef dramas, and one into lifestyle comfort food. You can practically hear the AI short-circuiting.

But go ahead and spend $500K building a ChatGPT plug-in that can "summarize user behavior trends" before you've even figured out where your viewers are dropping off.

🤖 Here’s the uncomfortable truth: if your data stack is garbage, AI is just going to turn it into more organized garbage.

You know what “personalization” actually means on most platforms? You watch one season of Love Is Blind out of morbid curiosity, and now your homepage looks like Tinder and Bravo had a baby during a tequila bender. It’s not personalization. It’s pattern recognition for the terminally lazy.

And the problem isn’t the algorithm. The problem is the leadership that thinks AI is a magic wand, instead of what it really is: a very smart mirror. A mirror that’s going to show you exactly how busted your infrastructure is.

Grines’ report lays this bare. Most streaming companies are juggling three to six different analytics platforms, and not one of them is connected to anything resembling a central source of truth. Google Analytics, Mux, Adobe, JUMP, Tableau, NPAW, Conviva… it’s like the tech version of a potluck where everyone brought soup and no one brought spoons.

🎯 And what’s the result? Internal teams are basing million-dollar content decisions off conflicting dashboards. Data engineers are in therapy. UX designers are guessing. Executives are pointing at pie charts like it’s a magic 8-ball.

And the kicker? The people who need the insights the most—your monetization and UX teams—are the ones least likely to get access. The CPO and CEO are swimming in dashboards, while the person designing your onboarding flow is working off gut instinct and a vague memory of last quarter’s survey.

Then there’s the Wall Street Effect™. As in: internal analytics might be screaming “users are bouncing after the third click,” but if a sell-side analyst says your “brand awareness” is up 0.3%, that’s what gets the attention. Kirby Grines captured this disconnect perfectly: executives ignoring their own internal data because they’re too busy feeding investor narratives. It’s like rearranging the deck chairs on the Titanic because someone in a suit liked the symmetry.

And don’t even start with the predictive modeling fantasy. Everyone’s talking about AI like it's HAL from 2001, when most companies are closer to Clippy from Microsoft Word. 🧠💀

“Predictive churn modeling” sounds sexy until you realize your metadata tags are so inconsistent, your top-performing content is literally tagged as “drama” and “cooking show” at the same time. (This is not hypothetical.)

So, what do you do? You slap “AI” in your boardroom slide deck, say you’re building a “GPT-powered engagement system,” and hope no one asks for actual ROI. It's AI-washing, and it's happening everywhere.

So here’s the inconvenient checklist:

✅ Can you track a user across devices?
✅ Do your internal dashboards all say the same thing?
✅ Do your teams actually use the data you collect?
✅ Do you know what your best-performing content is—and why?
✅ Are your recommendation engines actually driving engagement, or just... echoing?

If you answered “no” to more than two of those, AI is not your savior. It’s your smokescreen. And when the fog clears, your churn rate will still be rising and your viewers still won’t know what the hell to watch next.

TL;DR:
📉 AI won’t fix a broken product strategy
🧹 You can’t automate what you don’t understand
🛠️ And you sure as hell can’t personalize if your data is a dumpster fire

If you want AI to work for your streaming platform, start by doing the boring, unsexy work:

• Clean your data

• Unify your tools

• Give your UX team access to real insights

• And stop letting “AI strategy” become code for we hope the robots fix this for us

Because if your platform still thinks Die Hard is a holiday rom-com just because it’s December… that’s not AI being dumb.

That’s you. ❄️🎄💥

Stay Bold, Stay Curious, and Know More than You Did Yesterday.