Big hype, no flavor: The missed opportunities in AI

AI is finally here in an "everyday" way. 

It's in our contact centers, our chatbots, our voice assistants, our internal tools. It's taking notes, drafting responses, summarizing conversations.

But it hasn't removed the work like we were promised. It feels like it's just changed what work looks like. Somehow, we don't feel any less busy and our customers aren't experiencing better service, faster wait times, or better resolutions. 

What is happening? Why do we still feel just as busy? Why aren't sales increasing and resolution rates improving? 

We were promised faster resolution, less admin, more seamless journeys. And instead, many teams are simply navigating more tools, more handoffs, and more work behind the scenes. The admin work that we previously did has shifted. It's shifted to correcting for the AI experience.

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We're still not seeing the better experience

I am the ideal user for AI and I use it regularly. 

I run my own business. I write a lot. I work across strategy, content, data, and operations. I use AI tools every day to clarify my thinking, draft content, fix spreadsheet formulas, and sense check ideas before they go out into the world.

Tools like ChatGPT are genuinely useful. They help me get started faster, organize my thoughts, and move through work more efficiently when I otherwise might get stuck.

I'm not new to this. I'm comfortable with prompting. I know how to guide outputs, refine tone, and iterate to get something usable. I also know when to throw in the towel and stop using it because it's not giving me anything useful. My standards are high so it happens far more often than I care to admit. 

But I'm also no slouch when it comes to AI agents. In addition to having used them in previous roles, I've worked with a number of clients who have implemented them to varying degrees of success. Because of that, I'm constantly being introduced to new tools. Every week there's another demo. Another platform. Another "agentic" solution promising to take work off of our plates, reduce customer support wait times, and give teams hours back in silly administrative tasks that artificial intelligence (AI) can do instead.  

And yet, I'm still just as busy. Most teams are. 

So what gives? Why are all these AI tools not delivering on said promises? 

It's not that AI isn't helping. It is. But the help doesn't seem to translate into meaningful time back. The email still needs editing. The tone still needs adjusting. The output still needs checking and rewriting. In many cases, we are not replacing the work, we're actually just shifting where the effort goes. 

Even after years of using some of the most advanced tools available, being told, "it will learn how you speak", "you can teach it to talk like you", "it improves with time", they still don't come close to hitting the mark. Everything is still a robotic, formulaic output that requires heavy editing, rewrites, and checking to feel human or on-brand. 

So if someone who actively uses AI, understands how to prompt it, and integrates it into their day-to-day work still isn't feeling a reduction in effort, is it actually doing what they told us it would? Or are we just changing the work we do?

Overpromise, underdeliver

Most AI tools are breaking the golden rule of customer experience: under promise and overdeliver. 

Instead, every AI platform out there is "the next big thing" or the most advanced. The one that will finally unlock the golden efficiency ratio. 

And maybe they could be, maybe they actually are. But where many of them are falling down is their own customer experience. AI is not a plug-and-play solution. It requires thoughtful implementation, clear use cases, strong data foundations, and alignment across teams to deliver real value.

High-touch customer success has become critical. An exceptional onboarding experience is non-negotiable now. But far too often this is what happens:

1. A short demo that shows off the best-case scenarios
2. A quick download and implementation
3. A few handover meetings with one or two stakeholders as "primary owners" while everyone else is left to figure it out. 

This then adds an administrative burden on teams:

• Work out where it fits
• Build workflows around it
• Train themselves
• Troubleshoot issues
• Manage expectations internally

All of that takes time. Time that was supposed to be saved.

Customer success, where are you?

In a market flooded with AI tools that all claim to do similar things, the differentiator is no longer just the technology itself. It becomes the experience of implementing it and getting the most use out of it.

This is where AI platforms have the biggest opportunity – in their frontline customer success teams. They shouldn't just be onboarding clients, they should be making sure they are using the tool to its fullest extent, holding their client's hand all the way through their first real steps. Setting them up to… succeed!

Right now, too much of the implementation effort is being pushed back on already stretched teams, many of whom have never used a tool like this before. Isn't the whole reason they're getting AI because they're already stretched too thin? The irony!

If AI is going to deliver on the many promises it gave us, the onboarding needs to be optimized for the very customer they're promising to help.

What successful organizations are doing differently

The organizations starting to see real impact from AI aren't necessarily the ones with the most expensive tools or the hottest ones in the market. 

The successful organizations I've seen and worked with are the ones taking a deliberate approach and have worked hard at nailing the onboarding experience, often internally.

Their secret? They start with a specific problem they are trying to solve and stick to it. There is alignment on priorities before any technology is introduced.

What are we actually trying to solve? Where is the biggest friction in the customer journey? Where is the highest effort for teams?

From there, they choose an AI system that works for them, not necessarily the one with the most features. One that aligns with how they operate, their existing systems, and their values.
They invest in upskilling their people. Not just how to use the tool, but how to think about it.

How to apply it. How to integrate it into day-to-day work in a way that actually reduces effort.

It's more important than ever that we are teaching our teams how to think in the age of AI. 
They focus on getting the foundations right:

• A strong, accurate knowledge base
• Clear workflows
• Defined ownership
• Governance around how AI is used

And importantly, they don't overpromise. They don't position AI as something that will magically remove all admin overnight. They treat it as something that, when implemented well, can gradually reduce effort and improve outcomes over time, eventually allowing team members to focus on something different, not less. 

The shift we need

It feels like a new AI tool is popping up every few seconds. More tools are being added. More capability is being introduced. But the experience isn't necessarily improving and that's where it begins to fail and under-deliver on its really big promises.

We need to change the way AI and agents are pitched. We need to change its promised purpose. And we need customer success teams to be the rockstars once again. 

Until that happens, all these AI tools will keep tasting the same. Big hype, no flavor. 

Quick links

• Building trust in digital-first brands: What we learned at All Access: Digital CX 2026
• How practitioners are spending their CX budgets in 2026
• Conversational AI: Where we really are – and what has to happen before you scale