AI isn’t a solution, it’s a tool

The world is currently abuzz with AI. From self-driving cars to AI-generated art, it seems like there's no limit to what this technology can do. But amid all the excitement, it's crucial to step back and ask: Are we caught up in a hype cycle, and if so, where are we on that curve? To understand this, let's turn to the Gartner Hype Cycle. Whenever new technology emerges, it’s good practice to remember Gartner’s Hype Cycle.

Source: Gartner (via Aditya Ranjan Patro)

The Gartner Hype Cycle depicts the journey of emerging technologies from their initial spark of innovation to widespread adoption and practical application. It starts with the innovation trigger, where a new technology captures attention and generates excitement. This is followed by a peak of inflated expectations, fueled by media hype and unrealistic claims. As the technology fails to deliver on these inflated promises, it enters the trough of disillusionment, marked by waning interest and skepticism. However, as the technology matures and its true potential becomes clearer, it climbs the slope of enlightenment, where successful implementations and practical applications begin to emerge. Finally, it reaches the plateau of productivity, where the technology becomes mainstream and widely adopted, delivering tangible benefits.

There are many historical examples of the hype cycle in action, one of them being the dot-com bubble. The late 90s saw the internet explode onto the scene, with companies promising to revolutionize industries overnight. Investors poured money into startups, often without a clear understanding of their business models. The peak of inflated expectations was unsustainable, leading to a crash when reality failed to match the hype.

Fast forward to today, and AI is taking center stage. Companies are eager to integrate AI into their products and services, often driven by a fear of missing out. But are we truly understanding the problems AI can solve, or are we merely applying a solution in search of problems?

In day-to-day work scenarios, this is manifested by leaders asking "How can we use AI in our product?". While this might seem to be a sensical question to ask, it also becomes clear that this scenario prioritizes technology over user needs. Haven't UXers been preaching for years that this approach often results in products that fail to resonate with users? That it's crucial to start with the users and their problems?

Here’s McDonald’s recent AI update. They introduced AI in taking drive-thru orders. With this, they aimed to introduce voice-over in taking orders and limit human intervention. But instead of improving the customers' journeys, it turned out a bunch of funny viral videos. 

It almost appears that this effort was driven by an "AI first" approach: How can we use AI to eliminate humans in food ordering? But what is the underlying problem here? Did customers really want to eliminate human interaction in the food ordering process? It’s more likely that McDonalds wanted to increase profits by reducing their workforce. If that was the main goal, what solutions could have helped achieving this goal? AI might have been one venue to explore, but there are certainly other solutions imaginable that would support McDonalds business goals without introducing a sub par experience for their customers. In the end, embracing AI prematurely, led to a non-functioning product with a bad customer experience.

The danger of the current AI hype cycle is that implementing AI models is expensive. The energy consumption and computational resources required for training and running these models are substantial. If companies fail to identify clear use cases and viable business models, they risk financial problems.

So, where do UX professionals fit into this landscape? Our role is to champion the user's perspective. We need to ask the hard questions: What are the actual problems users face? What potential solutions can we develop for these problems? Can AI be part of that solution? If so, how?

By prioritizing user research and applying a user-centered design approach, we can guide companies towards developing AI-powered products and services that truly add value. We can help steer them away from the risky path of blindly chasing the hype, ensuring that AI investments are well-founded and sustainable.

The AI revolution is full of promise, but it's essential to navigate it with a clear head. By focusing on user needs and real-world problems, we can harness AI's power to create meaningful and impactful solutions. As UX professionals, we have a crucial role to play in shaping this future.