It’s fairly well documented that businesses are often struggling to capture benefits from investments in AI. A recent paper from New York University aims to help leaders do better, and urges them to also invest in complementary assets alongside the AI technology itself.
“When you have a new technology, or a new innovation that you’re adopting in your firm, complementary assets are the additional things that you need in order to get value from this technology,” they explain.
Smart investments
Consider a scenario where a company incorporates machinery and a human worker in their production process. To enhance efficiency, they decide to introduce a robotic arm for handling parts. However, this investment alone does not suffice. The company must undertake additional investments in complementary assets. For instance, they may need to attach a specialized appendage to the robotic arm for manipulating a specific part unique to their production.
This serves as just one illustration of a complementary asset. Another example involves the implementation of sensors to monitor the actions of the robotic arm, aiding its alignment with the machine responsible for placing the parts. Consequently, the company might need to invest in a comprehensive computing system and accompanying software to oversee these operations.
Furthermore, there is a necessity to invest in human capital. Specifically, the company must hire a new worker who possesses the requisite knowledge of the new process, the software, and troubleshooting skills for the robotic arm. It is crucial to recognize that simply investing in the robotic arm alone does not yield any value. Without proper utilization and integration within the production system, it remains nothing more than an inert component.
To gain insights into how organizations will navigate the challenges posed by the rapid advancements in artificial intelligence (AI), it is instructive to examine historical precedents of rapid technological progress, such as electrification, the telephone, and the Internet. Although tempted to perceive each new technology and its implications as unprecedented, the underlying dynamics and management considerations remain consistent with earlier technological advancements.
“A good starting place is to look at these prior disruptive technologies and see how they changed industries and firms and see which firms did well and which ones didn’t, and why,” the authors explain. “Apply that same logic to AI. What’s similar to prior episodes of new technologies and innovations, and what’s different?”
According to the authors, the impact of AI on various jobs and industries will be transformative, albeit not necessarily resulting in their complete elimination. The emergence of AI-driven language capabilities, for instance, signifies imminent changes that can be anticipated in the realm of postsecondary teaching occupations.
“Imagine we were having this conversation in 1980 about personal computers. Many jobs changed, your job changed, my job changed. Our jobs were not eliminated. I think the same is true with artificial intelligence,” they conclude.
