Eitan Cohen is CEO of TechSee, a Visual AI company transforming customer service for ISPs, Smart Home, CE and Home Security brands.gettyMost contact center automation targets $2 problems. The $200 ones are still waiting.Every service leader I've spoken with this year is investing in AI. The strategies look similar: automate the high-volume interactions, reduce handle times, deflect calls where possible.It makes sense on paper. And it shows in results: faster responses, lower agent load, promising dashboards. But here’s something that rarely makes it into the board update: most of that automation is aimed at the cheapest problems in the stack. The Inversion Nobody Wants To DiscussInteractions like billing questions, password resets and subscription activations make up roughly 80% of contact center volume. They're repetitive, well-defined and relatively easy to automate. They're also, individually, among the least expensive interactions a service team handles.The real cost lives in the other 20%. These include connectivity failures, hardware breakdowns, onboarding gone wrong and smart home devices that simply won't connect. These cases are fewer in number, harder to predict and almost always end the same way: a field technician dispatch.A single truck roll costs $150 to $200 on average. But the financial exposure doesn't stop there. Complex service failures drive some of the highest frustration scores in the industry. Parks Associates research found that when customers experience connectivity issues, NPS drops to -28. Among those affected, 43% say they're likely to switch providers. The cost of a failed Tier 2 interaction isn't just the dispatch. It’s the customer you may lose because of it.Despite this, most AI investment flows toward volume rather than complexity. Not because leaders don't know where the costs are. But because Tier 1 calls are where the light is brightest.The Lamp Post ProblemThere's a well-known problem in research called the streetlight effect. A man searches for his keys under a streetlight, not because he lost them there, but because that's where the light is. We look for answers where it's easiest to search, rather than where the truth actually lies. Contact center AI has the same problem.Tier 1 automation is visible, measurable and demos well in a boardroom. You can show deflection rates and handle time reductions within a quarter. Tier 2 automation feels harder because the cases are messier, the variables are less predictable and results take longer to surface. So the investment keeps flowing to the quick wins, while the expensive problems stay expensive.I've watched this pattern play out across dozens of enterprise service organizations. Teams celebrate meaningful Tier 1 gains while their truck roll costs and churn quietly compound in the background.The Modality MistakeMost companies built their AI service stack in a specific order: text first, then voice and eventually visual. It felt logical to start simple and add layers over time. That logic holds until you trace where the expensive failures actually happen.The human brain processes images 60,000 times faster than text. Context is visual before it's anything else. We built AI for service in the opposite direction, and that ordering decision is a big part of why service organizations are still automating the $2 problems instead of the $200 ones. Complex, high-cost service issues are almost always physical. A router placed in the wrong spot, or a device that appears fully functional yet isn't connecting, for example. A setup that fails because the environment for the new product is not well suited for the job (a nuance never well communicated in manuals). These are problems you cannot reliably diagnose through text or voice alone. So when a customer reaches out to find solutions via a traditional AI Agent, AI is forced to guess, and in service, guessing means dispatching, or worse, getting something wrong and losing the customer entirely.Visual AI isn’t a phase three investment. It is the missing modality that provides context so everything else works. When agents can see the customer's environment, the actual device, the actual setup and the actual home, issues that would have ended in a truck roll get resolved in minutes. This isn't about replacing expert judgment. The most complex cases still need experienced people. But visual AI gives those people the context to act on, rather than assumptions to work around.Where ROI Actually LivesThe companies seeing the strongest returns from AI in service have something in common: they stopped chasing volume and started targeting complexity. Their AI investment is built around the cases that drive trucks, trigger churn and impact loyalty, not around the cases that were already cheap to handle.The contact center math is straightforward. If your strategy is built around Tier 1 call deflection, you are optimizing costs that were never the real problem. If it's built around eliminating unnecessary Tier 2 escalations and truck rolls, you're compressing the budget lines that actually move the needle.The 80/20 problem in AI service is hiding in plain sight. Fixing it doesn't require a new strategy. It requires looking past the lamp post and building AI that can finally see.Forbes Technology Council is an invitation-only community for world-class CIOs, CTOs and technology executives. Do I qualify?