According to McKinsey, “Research shows that 70 percent of complex, large-scale change programs don’t reach their stated goals. Common pitfalls include a lack of employee engagement, inadequate management support, poor or nonexistent cross-functional collaboration, and a lack of accountability.”
Last year I was doing some spring cleaning and looking for space in my home office for a digital piano. As I pulled books from my bookcase, packing them into boxes to go into storage, I found my Blockbuster Video membership card. I’d tucked it inside a book as a bookmark. That membership card must be more than 10 years old. In addition to the books, I also put my DVD player into storage. With the easy availability of streaming services like Netflix, Hulu, and Apple TV, I can’t remember the last time I rented a video or used a DVD.
When it was founded in 1998, Netflix offered a subscription model that replaced trips to rental stores with home delivery service. In 2000, Netflix offered Blockbuster a partnership, but the home movie provider turned it down. Seven years later, when Netflix transformed its business model to streaming content, it wasn’t long before Blockbuster eventually went out of business.
This was not a technology failure, but a failure to embrace organizational change.
AI won’t replace humans. AI will create jobs—and contrary to what you might expect, these jobs won’t just be for computer geeks.
The key reason is comparative advantage. David Ricardo developed the economic theory in 1817 to explain why countries engage in international trade even when one country’s workers are more efficient at producing every single good than workers in other countries. It isn’t the absolute cost or efficiency that determines which country supplies which goods or services. It is the relative strengths or advantages of producing each good or service in each country and the opportunity cost of not specializing in what you do best. The same principle applies to humans and computers.
Computers are at their best doing repetitive tasks, mathematics, data manipulation, and parallel processing. These comparative strengths are what propelled the Third Industrial Revolution, which gave us today’s digital technology. Many of our business processes already take advantage of these strengths. Banks have massive computer systems that handle transactions in real time. Marketers use customer relationship management software to store information about millions of customers. If a task is repetitive, frequent, or common, automate it. If it has a predictable outcome, and you have suitable data to reach that outcome, then automate that workflow.
Humans are strongest at communication and engagement, context and general knowledge, common sense, creativity, and empathy. We are inherently social creatures. Research shows that customers prefer to deal with humans, especially in situations when they experience a problem and want help solving it. Don’t replace human interactions with computers. Don’t force customers to use an automated system and press buttons when they just want to hear a human voice and talk to someone who will fix their problem.
As part of your organizational transformation to an AI-driven enterprise, you will need to redesign work tasks with the comparative strengths of humans and computers in mind. But how easy is it to evaluate the strengths of each? Can humans reliably self-assess whether AI outperforms them?
The Dunning-Kruger effect is a cognitive bias in which unskilled persons overestimate their capabilities. It is strongly related to the cognitive bias of illusory superiority and comes from people’s inability to recognize their lack of ability. In popular culture, people who exhibit this bias are sometimes described as “knowing just enough to be dangerous” or said to be on “Mount Stupid.
