Connected TV (CTV) advertising was hyped as the marketer’s latest shiny toy—a seamless fusion of creativity and data-driven precision, all orchestrated by the ever-mystical artificial intelligence (AI).
The pitch? Hyper-targeted ads that not only know what you want but also when you want it, blending so smoothly into your favorite shows that you’d swear they were part of the plot.
The reality? It’s more like a badly scripted sitcom where the punchlines fall flat, and the guest stars are utterly forgettable.
The ACR Fiasco: When AI Can’t Read the Room
Automatic Content Recognition (ACR) was touted as the holy grail of contextual advertising. The promise was simple: AI would read the room, detect the emotional tone of your current binge-watch, and serve up an ad that’s not just relevant but contextually flawless. Imagine watching a spine-chilling episode of The Walking Dead and getting interrupted by an ad for knitting needles instead of, say, zombie repellant. Sounds absurd? That’s where ACR often lands.
CEO/Co-founder at TVision
Yan Liu, CEO and Co-founder at TVision, doesn’t sugarcoat it: “AI is more about efficiency at this point, especially on some tasks you typically outsource. I think it will create more spam, MFA websites, and better creative for DR ads. AI is not good at linking multiple tasks yet. So I don’t think it can add tons to quality of execution or creative.” Most ACR systems can’t quite grasp the subtleties of human emotion. They recognize the genre but not the mood shifts that dictate what type of ad should follow. Instead of a seamless transition, advertisers end up with mismatched jingles that make viewers want to change the channel faster than you can say “ROI.”
Programmatic Buying: Precision or Pricey Guesswork?
Programmatic ad buying on CTV was supposed to be the sharpshooter’s dream—AI analyzing real-time data to hit the exact target with surgical precision. In theory, sounds like a marketer’s nirvana. In reality, it’s more like throwing darts blindfolded and hoping one lands in the right sector. Shared devices, fragmented data, and inflated CPMs (cost per thousand impressions) mean that “precision targeting” often misses the mark. You’re paying top dollar to reach your ideal demographic, only to have your ads shown to someone’s grandma binge-watching Golden Girls.
Marketer, Advisor, Founder
David Nyurenberg, of Rain the Growth Agency, cuts through the nonsense: “AI has fundamentally changed how we approach CTV, allowing us to score each impression based on its likelihood of achieving the outcomes we need.” While this sounds revolutionary, it’s essentially just a fancy way of saying, “We’re making educated guesses with more data.” And let’s face it, even educated guesses can be wildly off when you’re dealing with the chaos of CTV.
Lara Koenig, global head of product at MiQ, summed up the issue: “Programmatic buying is at a midpoint in maturity; many systems still can’t escape the fragmentation that drives up CPMs while reducing accuracy.” Advertisers find themselves frustrated, managing layers of devices, apps, and ad exchanges, all claiming to deliver results—yet missing key targeting elements.
Shoppable Ads: Novelty Over Functionality
Shoppable ads were pitched as the future of CTV—ads so interactive that you could buy products without ever leaving your couch. Hulu and Roku have toyed with features like QR codes and product carousels, but let’s be real: navigating a purchase with a remote is about as enjoyable as trying to text with oven mitts on. Most viewers would rather swipe on their phones or click through on their laptops. Shoppable CTV ads remain more of a novelty than a mainstream solution, leaving advertisers scratching their heads and consumers frustrated.
Take Hulu’s clickable product carousels during prime-time shows, for example. The idea was brilliant on paper—blend commerce with entertainment, allowing viewers to instantly purchase the stylish jacket their favorite character just donned. In practice, though, the execution falls flat. Viewers are left fumbling with their remotes, trying to select tiny QR codes or navigate awkward drop-down menus while half-watching an intense drama.
Andrew King, GM and Product Lead at TripleLift, notes, “We’re already witnessing applications—smarter ad placements within content, more relevant programming schedules, enhanced insights atop campaign reports, even upscaled creative assets.” Yet, even with these advancements, the fundamental issue remains: the CTV interface isn’t conducive to seamless shopping.
AI-Powered Brand Placement: The Awkward Cameo No One Asked For
AI-powered brand placement was sold as a groundbreaking tool that would seamlessly insert brands directly into the content you love—blending logos, products, and billboards into the very scenes of your favorite shows without the need for traditional ad breaks. The vision? A fully integrated brand experience where ads would feel as natural as the storyline itself. Some technologies aimed to embed branded elements post-production, letting characters casually sip from a strategically placed soda can or walk by a logo-embellished billboard, supposedly without pulling the viewer out of the narrative. Sounds futuristic, right? Well, not quite.
In reality, these placements often stick out like a bad CGI effect from a B-list movie. Instead of enhancing the content, these awkward insertions end up drawing attention to themselves, breaking immersion rather than adding to it. You might be watching a dramatic scene, but when an out-of-place product appears, it’s like getting hit over the head with a brand. Suddenly, the emotional moment between two characters is hijacked by a poorly rendered energy drink can that feels jarringly forced. Instead of seamless integration, these placements often feel like a desperate attempt to gain visibility, ironically doing more harm than good.
Jason Fairchild, CEO of TvScientific, believes real AI can revolutionize CTV but cautions against the current “magic fairy dust” use of AI by most companies. TvScientific focuses on two main areas:
Co-Founder and CEO at tvScientific
- Campaign Optimization: Using AI to drive advertiser-declared outcomes like ROAS, CPA, and CPI by automating campaign adjustments based on a vast array of data points.
- Creative Optimization: Building and optimizing TV ad creatives at the element level, determining which ad variations perform best with specific audience segments.
Who’s Actually Delivering? A Few Shining Stars
Amidst the sea of overhyped AI tools, a few companies are actually making meaningful strides:
- Comcast’s FreeWheel: Integrating AI into programmatic buying, FreeWheel optimizes ad placements by finding premium inventory that aligns with real-time viewership trends.
- Origin’s Slingshot: Using AI to optimize ad delivery timing, Slingshot boosts viewer retention and ad effectiveness by aligning ads more closely with how people actually watch CTV.
- KERV Interactive: Pioneering shoppable CTV ads, KERV adds interactive elements that allow viewers to explore products in real-time, though the remote-based interface remains a hurdle.
- Vizio’s Inscape: Leveraging real-time viewing data, Inscape offers granular insights that help advertisers optimize placements based on actual viewer behavior.
- The Trade Desk’s Koa: Analyzing millions of data points, Koa enhances campaign effectiveness and audience reach across multiple devices, providing a more accurate targeting mechanism.
The Future: Efficiency Over Revolution (For Now)
Yan Liu sums it up best: “AI is more about efficiency at this point, especially on some tasks you typically outsource.” AI in CTV is great for automating repetitive, data-heavy tasks, but it’s not yet the creative powerhouse it was touted to be. As Liu puts it, “AI will create more spam, MFA websites, and better creative for DR ads. AI is not good at linking multiple tasks yet. So I don’t think it can add tons to quality of execution or creative.”
Jason Fairchild of TvScientific argues that real AI can revolutionize CTV by optimizing campaigns and creatives in ways humans simply can’t manage. “We think about AI/ML in terms of automating vitally important components of our business, which is leveraging TV advertising to drive actual business outcomes for advertisers,” he explains. His company has developed patented technology that optimizes campaigns and creatives to achieve advertiser-declared outcomes, proving that AI can indeed be transformative when applied correctly.
Final Thoughts: The Emperor’s New Algorithms
So, where does that leave us? AI in CTV is still wearing the emperor’s new clothes—glamorous on the surface but lacking real substance underneath. While companies like Origin, KERV Interactive, Vizio’s Inscape, The Trade Desk, and FreeWheel are making genuine progress, the majority of AI applications in CTV remain more smoke and mirrors than actual game-changers. The real magic, as Jason Fairchild suggests, lies in AI’s ability to handle vast data and optimize campaigns beyond human capacity, but this potential is yet to be fully realized.
For marketers, the advice is clear: approach AI in CTV with a healthy dose of skepticism. Don’t buy into the hype without seeing real results. Focus on leveraging AI where it truly adds value—efficiency, data analytics, and strategic optimization—while keeping your expectations grounded. Until AI can seamlessly blend into the creative process and deliver on its grand promises, it’s best to view it as a powerful tool rather than the wizard behind the curtain.
