Does AI Matter?

Abstract image of a business person holding a phone with an overlay of an AI bot connecting to different icons


In 2003, Nicholas Carr shook the business world with his provocative Harvard Business Review article, “IT Doesn’t Matter.” Carr’s argument was that information technology had evolved into a commodity, rendering it a non-strategic factor for businesses. While the controversy continued for years, Carr’s theory ultimately played out. In fact, Carr’s article lays a foundation for us to evaluate new technological advancements and their impacts on business… including artificial intelligence. While Carr asked if IT was still relevant, we’re asking where we are in the continuum between temporary competitive advantage and commodity as it relates to AI.

What Does This Mean?

In the original article, Carr discusses how he believed IT infrastructure became a commodity, that is, something that was easily accessible, inexpensive, and necessary to function well in the modern business landscape. In simpler words, everyone used it and everyone needed it.

So what does this mean? Well, in order for a tool to become a commodity, it must be easily accessible and necessary for the normal functioning of business. So let’s apply this logic to today’s AI world. AI-driven solutions, such as natural language processing, image recognition, and predictive analytics, have actually existed in the market for years.

It wasn’t until the launch of ChatGPT did the masses get to experience an accessible AI tool first hand. Millions of people flocked to ChatGPT and other text generating AI applications. So upon initial examination, it appears that commoditization of AI is already here right? After all, if you look at news sources, AI is being used everywhere and by everybody.

A Deeper Dive

However, delving below the surface exposes the truth. Many of these AI tools are just copy cats or re-skins of popular tools. Generative AI tools are particularly at fault as many look-a-like ChatGPT tools have surfaced over the past year. As it stands, the adoption of AI – despite news headlines – is nowhere near complete.

In fact, a minority of businesses actually use AI tools as part of their functional infrastructure and even fewer leverage it well. Those that have adopted the technology are able to turn a rather small initial time and money investment and parlay it into true competitive advantages. Cost reductions, accuracy improvements, and enhanced output are just a few results that, when combined with core competencies of business, have given them a unique competitive advantage.

It Is Really Early

But, we are early in the adoption curve of AI. Like the advent of IT infrastructure, the very presence and use of IT generated a significant although temporary competitive advantage to early adopters. Companies quickly found that for every new company that adopted IT infrastructure, their respective competitive advantage began to experience diminishing returns. 

This is almost a direct roadmap to the evolution of new business technologies, and particularly AI adoption. Firms that do adopt AI early have seen a jump in their competitive advantage, many of which have leveraged it to enhance their market share by taking advantage of the lagging firms. However, as more and more firms begin to leverage AI, the relative competitive advantage experiences diminishing returns. Until, like IT infrastructure, it becomes a commodity.

The Strategic Value Is Now

As Carr originally posited, the competitive advantage of IT once commoditized lay in how companies implemented it, and the same will hold true for AI. Implementing AI effectively in specific business processes, optimizing data quality and management, and integrating it with existing systems is where businesses enhance their competitive edge. It’ll no longer be just about having the technology; it’s about how you use it.

While Carr’s argument suggested that IT was no longer a strategic differentiator, AI can still offer strategic value. Companies that apply AI innovatively can create new business models, deliver personalized user experiences, and derive data-driven insights that set them apart. This means even a commoditized AI can be a powerful driver of innovation and competitive advantage when implemented strategically.

The Question Remains

The question remains: Does AI matter in business today? The answer echoes Carr’s insights from two decades ago. AI has, to some extent, transitioned into a commodity, providing fundamental support to various industries. However, its strategic significance persists for companies that leverage it effectively and ethically in their operations and innovations. AI is more than just technology; it’s a tool for solving real-world problems, creating innovative solutions, and driving business growth. So, does AI matter in business? The resounding answer is yes.

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