The AI Trap

The Cycle of Shiny New Technologies

Mark Twain said, “History doesn’t repeat itself, but it often rhymes.” This is not only true for world-events but also in the business world with the adoption of new technologies. In this newsletter, we tackle a recurring mistake: businesses rushing to adopt new technologies like Generative AI without solving real customer problems. We've seen it with web, mobile apps, and now GenAI. Tech hype leads, while strong Product Management takes a back seat. The result? Misalignment between customer needs and what the technology actually delivers. The solution is simple but often overlooked: resist the noise, focus on clear problem definitions, and prioritize customer-driven, iterative processes to guide smart tech adoption. Let’s break the cycle.

In today’s fast-paced world of technological advancement, businesses often fall prey to the allure of new innovations, hastily adopting them without fully understanding the real customer problems they aim to solve. However, this cycle of excitement, adoption, and eventual disappointment is not new, it has been repeated through various waves of technology over the years. The cycle is particularly relevant today as businesses rush to integrate Artificial Intelligence (AI), particularly Generative AI (GenAI), into their operations. The rapid rise of AI tools such as large language models (LLMs) like ChatGPT has ignited both excitement and fear of missing out (FOMO). But without a clear understanding of real customer needs, companies risk falling into the same traps they did with previous technologies like the web and mobile applications.

Source: Jeremy Kemp https://commons.wikimedia.org/wiki/File:Gartner_Hype_Cycle.svg 

Understanding the Gartner Hype Cycle is critical for contextualizing this pattern of over-adoption and eventual disillusionment with new technologies. The Hype Cycle offers a framework that maps the typical life cycle of emerging technologies as they progress through five distinct stages. It begins with the "Technology Trigger," a phase marked by early proof-of-concept and media interest, sparking excitement and curiosity among both businesses and the public. However, as initial adoption spreads, this enthusiasm often grows unchecked, leading to the "Peak of Inflated Expectations," where businesses invest heavily in the technology based on its perceived potential, sometimes without fully understanding its practical applications or limitations. This stage is driven by the fear of missing out (FOMO), as companies rush to stay ahead of competitors or please shareholders, even when the technology's benefits are not yet proven.

Inevitably, the overhyped promises of the technology fail to materialize as quickly or as comprehensively as expected, leading to the "Trough of Disillusionment." This phase is characterized by a widespread recognition that the technology is not a panacea, and many companies begin to scale back or abandon their initiatives, often citing unmet expectations or unanticipated challenges. It's at this point that businesses realize they have invested in a solution without clearly identifying or addressing the core problems their customers face.

However, not all is lost, those companies that survive the disillusionment phase often recalibrate their approach, refine their use of the technology, and emerge into the "Slope of Enlightenment." In this stage, businesses start to recognize realistic applications and gradually build sustainable use cases for the technology. Finally, the technology reaches the "Plateau of Productivity," where its value is fully understood, and it becomes a mature, stable tool integrated into mainstream business processes. The key lesson from the Gartner Hype Cycle is that premature adoption, spurred by external pressures and technological optimism, frequently leads to disappointment when the real-world utility of the innovation falls short of its initial promise.

The Web Hype

The rise of the World Wide Web in the 1990s serves as an example of businesses jumping on a new technology without fully understanding its purpose or long-term value. When companies first rushed to establish websites, the focus was simply on having an online presence. Many businesses lacked a clear strategy for how these websites would drive value. As a result, many early websites were little more than digital brochures, static, difficult to navigate, and offering limited customer interaction.

It wasn’t until years later that businesses began to understand how to truly leverage their web presence. The adoption of more sophisticated tools like Search Engine Optimization (SEO), e-commerce platforms, and integrated marketing strategies helped companies realize the full potential of their websites. This shift marked the evolution from websites as a novelty to websites as indispensable tools for business growth.

Notably, the lack of established Product Management practices in this era contributed to the slow adoption of these more strategic approaches. Agile methodologies were in their infancy, and businesses did not yet have a structured way to iterate and improve based on customer feedback.

The Mobile App Craze

Fast-forward to the early 2000s, and the same pattern of technology adoption can be observed in the rush to develop mobile applications. Much like the rush to create websites, businesses scrambled to develop mobile apps without a clear understanding of how these apps would solve real customer problems.

The concept of the “CEO’s app” emerged, a situation where company executives pushed for a mobile app simply because their competitors had one. The result was often poorly designed, rarely used applications that provided little value to customers. These apps frequently lacked intuitive functionality or a real use case, and many were quickly abandoned by users.

Technological challenges exacerbated this trend. Although hybrid development frameworks, allowing for one codebase to support both web and mobile applications, seemed like a promising solution, they never achieved widespread adoption. Furthermore, while Product Management was more established during the mobile app craze, it was often misapplied or entirely bypassed in favor of delivering what executives wanted rather than what customers needed.

The GenAI Trap – History Rhyming Again

Today, as businesses rush to implement AI technologies, particularly Generative AI tools like ChatGPT, we are witnessing history rhyme once more. Companies are adopting AI tools with the same urgency and lack of forethought that characterized earlier technology trends. Despite advancements in Product Management, businesses are repeating familiar mistakes: neglecting customer needs and prioritizing the technology itself over practical applications.

Several factors drive this behavior. Shareholder and board pressure is immense, as organizations race to avoid falling behind competitors. Fear of missing out on the next big technological revolution pushes businesses to adopt AI, often without a clear understanding of how it will impact their customers or operations.

In the adoption of any new technology, there is often a tension between engineers and product managers. Engineers, being on the front lines of innovation, tend to be eager to introduce new capabilities, sometimes without considering whether the technology solves a real customer problem. They are often captivated by what is possible, which can lead to premature technology adoption.

On the other hand, Product Managers typically focus on solving current customer problems with existing tools. While this approach is valuable in maintaining product-market fit, it can sometimes lead to a reluctance to adopt new technologies that could provide better solutions. Successful innovation, therefore, requires balancing the visionary enthusiasm of engineers with the customer-focused practicality of product managers.

To ensure that new technology delivers value, businesses need both teams to collaborate closely. Engineers should bring their innovative ideas, but Product Management must validate the need for those ideas in the context of solving real customer problems. Only then can a new technology, such as AI, move beyond proof of concept and deliver meaningful results.

How to Avoid the Next Trap

Given this recurring cycle of shiny new technologies, how can businesses avoid falling into the next trap? The key lies in a disciplined approach to innovation that starts with a clear understanding of customer needs and emphasizes collaboration between engineers and product managers. Here are some actionable insights:

1. Understand the Problem First: Before adopting any new technology, businesses must start with a clear understanding of the customer problems they aim to solve. This step is often overlooked in the rush to adopt the latest tech.

2. Involve Product Management Early: Product managers should be involved in the technology adoption process from the very beginning. They play a crucial role in validating the long-term value of new technologies and ensuring that they align with customer needs.

3. Collaborate with Engineers: Product managers and engineers must work closely to explore how new technologies can solve real problems. Engineers bring innovative solutions, but their enthusiasm needs to be balanced with a focus on practicality and customer value.

4. Resist External Pressure: Companies should make customer-centric decisions, even in the face of pressure from shareholders and boards. It’s essential to avoid adopting technology simply to appear innovative or keep up with competitors.

Despite decades of technological advancement and the growing maturity of Product Management practices, businesses continue to make the same mistakes when adopting new technologies. Whether it was the web, mobile apps, or AI, the lesson is clear: new technologies must serve real customer needs to deliver long-term value.

In reflecting on these cycles, it becomes apparent that businesses must adopt a more thoughtful, customer-first approach to technology adoption. This requires discipline, patience, and a commitment to learning from past mistakes. Companies must prioritize solving real problems over adopting the latest trends, ensuring that history doesn’t continue to “rhyme” in unproductive ways.

As we move further into the age of AI and beyond, businesses have an opportunity to break the cycle of adopting shiny new technologies without a clear purpose. By focusing on customer problems, collaborating effectively between product managers and engineers, and resisting external pressures, companies can ensure that they harness the true potential of new technologies. In doing so, we will avoid the pitfalls of over-adoption and disillusionment that have characterized previous technological revolutions and be prepared for the next one.