Is AI Really Worthy of All The Hype?

By Eric Lambeth

September 26, 2024

While artificial intelligence (AI) has garnered significant attention recently, much of the hype overstates its true impact. In reality, AI represents an iterative step forward in software development, rather than a revolutionary leap. AI builds on decades of progress in fields like machine learning, data science, and automation, and many of its core technologies are refinements of existing concepts. Algorithms such as neural networks, now generally perceived to be an AI-related innovation, were developed as far back as the 1950s, highlighting that modern AI is built on foundational work that has evolved over time.

The focus on AI’s potential often overlooks its limitations. Most AI systems today excel at specific tasks, but they lack true understanding or general intelligence. These narrow applications, such as image recognition or natural language processing, are quite impressive – yet fundamentally limited. They are not groundbreaking shifts in the sense that they don’t dramatically change how software functions; rather, they automate processes we’ve been improving incrementally for years.

Furthermore, much of the current excitement around AI stems from its application in consumer-facing products, like voice assistants and recommendation algorithms. These are useful, but they don't represent a transformation of software development as a whole. Instead, AI tools are primarily enhancing existing capabilities, streamlining processes, and improving efficiency—advancements that are certainly valuable but hardly the monumental breakthroughs that some claim.

The current AI hype reminds me of the dot-com mania of the late 1990s and early 2000s, where excitement around the emergence of the internet into widespread commercial usage led to exponentially skyrocketing valuations of tech companies, many of which had weak business models (or, in some cases, no business model at all). Companies like Pets.com and Boo.com soared in popularity and stock prices despite lacking sustainable revenue streams, leading to their collapse when the tech bubble burst. Similarly, today’s AI buzz has led to lofty expectations, with many companies jumping on the AI bandwagon without clear, long-term strategies. Just as the dot-com crash tempered expectations, we may see a correction in how AI is viewed and valued, with a shift towards more practical, grounded applications rather than speculation-driven excitement.

The comparison serves as a cautionary tale, reminding us that technological advancements, no matter how promising, should be assessed with realism. In the case of the dot-com crash, the excitement outpaced the actual business and technological readiness, leading to market corrections. AI may follow a similar path, where only companies with tangible, value-driven applications will endure once the initial hype fades.

In essence, AI's advancements represent the natural evolution of computing and software development, continuing a trajectory of improvement rather than a complete paradigm shift. It offers valuable tools and efficiencies, but treating it as a massive leap forward oversimplifies the reality of its contributions to the tech world.