AI is fighting itself?! Here's my take on the “AI Bowl”

This year’s Super Bowl was supposed to be about football, snacks, and at least one emotionally manipulative animal commercial, yet it quietly turned into a televised turf war between AI companies, each one spending eight million dollars at a time to convince you they should be the voice living inside your computer, your phone, and possibly your conscience. Google showed up, Anthropic threw a few elbows at OpenAI, and Amazon tried to make the machines seem cuddly. It was less an ad slate and more a model cage match in prime time.

Most years you walk away remembering one clever ad and forgetting the rest before Monday morning, but this time the repetition was too coordinated to ignore, because AI kept reappearing across breaks and brands until it felt less like a creative trend and more like a category takeover. According to iSpot, roughly 23 percent of this year’s Super Bowl ads, fifteen out of sixty-six, referenced or featured AI, which feels less like coincidence and more like a statement of intent.

The four ways AI was packaged for America

If last year’s Super Bowl treated AI as a supporting feature, this year’s broadcast gave it top billing, with a wave of companies introducing not just products but entry points into a broader ecosystem. The ads that prominently featured AI generally fell into a few clear categories:

AI inside tools people already use: Google (Gemini), Microsoft (Copilot), Amazon (Alexa AI), Meta, and Zoom AI Companion. These spots were built around use cases viewers could imagine trying the very next day, which gave them an air of immediate accessibility. 

Start-here introductions to the AI world: OpenAI, Anthropic, and the breakout AI.com. These ads were more front door than feature tour, designed to say “begin here” rather than walk through specs. 

AI running work behind the scenes: Salesforce, IBM watsonx, ServiceNow, Oracle, and Intuit. These business leaning ads focused on workflows, operations, and decision support rather than consumer flash.

AI as a creative engine: Adobe Firefly and NVIDIA: These ads positioned AI as something you build with and create through rather than merely accelerating what they already do.

Major brands such as Google, Meta, and Amazon tied their Super Bowl spots directly to AI features and AI driven experiences. That strategy makes sense on a stage that still reaches roughly 130 million viewers and generates over $700 million in ad revenue. Companies do not spend at that level to experiment with tone; they spend to declare direction.

Which ads worked and which didn’t

As I watched the commercials from my home couch in real time, my reaction to the ads themselves varied widely, because while some were thoughtful and emotionally calibrated, others felt unintentionally ironic or tonally conflicted in ways that were more revealing than persuasive.

OpenAI: OpenAI’s commercial skipped the usual techno-spectacle and leaned into human imagery of reading, studying, sketching, and building ideas through deliberate effort, and I genuinely found the tone motivating. What struck me, though, was the built in contradiction, because the ad celebrates discipline and craft only to end by suggesting the same results can be produced in seconds through automation, which left me impressed and a little amused, since the message is basically “master the skill,” followed by “or just click the button.”

Claude: AI Companies are now critiquing each other on air?! Anthropic delivered one of the only ads of the night that felt like an AI company openly poking the industry, with its Claude spot humorously mocking ad stuffed chatbots and emphasizing that its assistant would not rely on embedded ads to push products, which I read as a very direct jab at OpenAI’s ad rollout. I liked that it put the joke directly inside a chat interface, because the format itself became part of the punchline, and it worked precisely because it said out loud what a lot of us are already thinking about monetization creeping into our AI tools.

Amazon Alexa:The Alexa commercial featuring Chris Hemsworth went for comedy by spoofing classic AI-gone-rogue movie scenarios, and while I get the joke, I found it a little awkward that the pitch basically says “AI is scary” before turning around and asking you to install more of it in your home, which is not exactly reassuring even when played for laughs.

Google Gemini: Google’s Gemini ad took the opposite route and leaned fully into emotion, showing a parent and child visualizing life in a new home through AI generated imagery, and I thought that approach worked much better because it grounded the technology in a real relationship moment instead of a gag. I have seen similar tools used for things like redesigning kitchens and generating personalized children’s story settings, so the use case felt believable to me, and overall it was one of the few AI ads that almost made me forget I was being sold AI at all, which is probably why it landed.

Genspark AI: I actually liked Genspark’s ad that was positioned around structured productivity. It showed AI doing something concrete instead of just waving at “creativity” in the abstract, and that kind of clarity is refreshing in a lineup full of big promises and soft visuals. To me, it stood out as one of the more practical spots of the night, since it focused on producing organized, usable charts and excel files rather than vague inspiration, which is exactly the kind of workflow impact I find far more convincing than concept heavy AI storytelling.

Nothing tests a launch like 130 million viewers

One of the most talked about moments of the night centered on AI.com, where the strategy seemed designed less as a product demonstration and more as a domain level coronation. Reports indicate that roughly 70 million dollars went into acquiring the domain and related assets, followed by an estimated eight million dollar Super Bowl placement that invited viewers to visit the site and claim personalized handles, a simple and bold call to action that succeeded in driving immediate traffic and just as immediately overwhelmed the infrastructure, causing the site to crash within minutes.

Although the platform recovered and later analytics suggested engagement far above typical Super Bowl medians, I strongly believe that if you invite the entire country to your digital front door, the door needs to open. The added requirement for users to submit a credit card is also a steep ask for mainstream viewers who are not yet sure what they are signing up for, and it leaves room for understandable skepticism.

My take on the “AI Blitz” and integrating these tools

My reaction to the AI heavy ad wave is mostly practical skepticism, because I use these tools every day and see both the upside and the confusion firsthand. Once the curiosity clicks turn into “okay, let’s actually use this,” companies quickly discover they do not just need AI tools, they need AI translation. 

In my own workflow, I have found Salesforce’s Agentforce tools genuinely useful for putting AI agents to work inside everyday business processes, while Genspark has been especially strong for building personalized AI assisted decks. Claude Code has also been instrumental in helping us build our email outreach agent, since it speeds up development and debugging while still requiring real architectural decisions.

What stands out right now is that interest is running far ahead of understanding, because you can see across Reddit, forums, and internal company chats that people are eager to use AI but are still asking very basic questions about where it fits, what to automate first, and how to avoid breaking existing workflows. That is the adoption gap, and it is wider than most commercials admit, which is why AI success usually depends less on the model you pick and more on how you wire it into real processes, real teams, and real guardrails.

That is exactly where aidatalyst focuses, since our work is not about chasing shiny demos but about turning scattered AI experiments into systems that actually function inside daily operations, whether that means workflow mapping, tool integration, guardrail design, or training teams so the technology reduces noise instead of adding to it. Super Bowl ads can introduce the promise, but adoption is what determines the payoff, and adoption almost always needs a guide.