AI Won’t Replace Humans — But Humans With AI Will Replace Humans Without AI - HBR
Just as the internet has drastically lowered the cost of information transmission, AI will lower the cost of cognition.
As the public comes to expect companies that deliver seamless, AI-enhanced experiences and transactions, leaders need to embrace the technology, learn to harness its potential, and develop use cases for their businesses.
Executives and regular employees can (and must) develop a digital mindset and change management is a critical skill that must be in the DNA of any successful organization.
Research shows that the nature of corporations (often dating from the 1920s and 30s) is changing foundationally because of technologies like AI, like machine learning. In terms of business model, how you create value, how you capture value, and your operating model, how you deliver value, how you achieve scope, the number of customers you serve, the number of products you have, scale, the number of customers you serve, and learning these fundamental parts of a business architecture.
For example, reflect about how much of your Google experience is fully automated, from the ads you see to the search you do to, if you’re using Gmail, how you interact with them. It’s not people that do those activities, it’s the algorithms that make that happen. Similarly with all the large e-commerce platforms like an Amazon or Alibaba or Netflix. These companies work in a fundamentally different way than a company like General Electric. The machines and the algorithms are at the center. The work is automated. The humans are actually designing the algorithms and testing them and checking them, making sure they’re working within bounds, but the actual transactions and activities are being mediated through the machines.
Most companies will not have a choice but to adopt AI and adopt digital at the core functions. We are already living in an AI age. In many ways: our personal lives are mediated through our transactions, through our smartphone, through our devices, and how we interact with consumer technology products.
Many of us get mad when our Uber car doesn’t show up in three minutes. People just expect the best experience in every experience they have. But executives, in their own companies, are completely satisfied if a customer service interaction can take two weeks, or if onboarding a new vendor takes six months.
We’re living in this disconnected world. Most consumers are living in an AI-first world but, then, encounter our companies and our organizations, and they’re like, “What is this?”
A transition is really inevitable. And for the folks that are behind, the good news is that the cost to make the transition keeps getting lower and lower. The playbook for this is now well-known. And finally, the real challenge is not a technological challenge, that’s like a 30% challenge. The real challenge is 70%, which is an organizational challenge. Every executive, every worker needs to have a digital mindset, which means understanding how these technologies work, but also understanding the deployment of them and then the change processes you need to do in terms of your organization to make use of them.
The next big wave is generative AI. But that won’t be the last wave, and quantum will hit us at some point, and things we can’t even anticipate will hit us. How do you prepare for that? How do you create a culture or mindset or organization that knows there will be unexpected waves of technology, we’ll have to figure out if they’re relevant to us or not, and if they are, we need to adapt quickly? Is there a general way to think about that?
There are two imperatives for most executives, for most managers, for most leaders.
One is a learning imperative. There’s lots of learning you need to do, and the learning has to be continuous. The idea is not that you need to become AI engineers or data scientists. For example, you might not want to be an accountants, but you need to learn accounting because that’s the language of business. That’s the way in which you think about how value is kept track of, how expenses are tracked, and so on. Super important. You don’t take the accounting course to become accountant, but you need to understand accounting so you can be a good business person. Same thing now with digital technologies and machine learning. You need to understand the machine learning stuff and the AI stuff, not because you’re going to become an AI engineer or an AI scientist, but because that is now going to be a critical table stakes for you to understand how business works.
The second bit is equally important, but completely underrated: change and change management. How you change, continuously, how you build a DNA for changing. The best companies will be the ones that can understand how change becomes a skill. If you think about change as a skill, what does that mean? Skills require acquisition of the skills. You’ve got to invest in learning. What does it mean to change? It requires practice. You’ve got to keep changing as well. And it requires adjustment. Those elements will become a key part of the ways in which leaders need to adapt to this world. You’ve got to keep experimenting. You have to keep current.
However, most executives are like senior citizens, the elderly, who have resisted technology, and now have no choice but to deal with it, are frozen and need a ton of help. That’s the thing we have to get over as we think about this.
30 years ago approximately, the [web] browser got invented. It lowered the cost of information transmission dramatically, and then in the last 30 years, we’ve been living through the build out of the internet, and waves and waves of the internet changing more and more industries, over and over again. The cost of information transmission went to zero, and then new companies formed, Google, Amazon, Facebook, you name it, e-commerce got invented. That is the world we are coming out of.
The same thing’s happened with generative AI. There’s been 20 years of AI being deployed at scale inside of many tech companies. That was in the basement. Netflix movie recommendations, your Google search results, your Amazon recommendations, your Spotify music results, your car access, your Waze access, your directions. All that was being empowered by AI tools. Even your spam killers. Remember how bad spam used to be for a while, and then overnight it went away? Because people deployed machine learning systems.
Think about generative AI as a drop in the cost of cognition. If the internet was the cost of information dropping to zero, the cost of cognition (how we think, who we think with), is dropping to zero with generative AI. That has significant ramifications.
We’re in the super early stages of this hype, of this cycle. The rate of innovation and the rate of improvement is increasing rapidly, and it keeps increasing. The rate of application development is also increasing rapidly.
What should leaders do? What should managers do, what should executives do around this thing?
One is to start thinking about and start practice in their own sandboxes what the use cases may be. We’re seeing tremendous use cases, for example, just in content generation. The thing managers and leaders need to do is, step one, start using it. The bans on ChatGPT and these things are misguided in many companies. There are a hundred million users, it’s already there. Executives and IT departments and legal departments are fooling themselves if they don’t think their workers are already using these tools.
Instead of pushing against it and saying, “No,” you need to embrace it and run bootcamps, run use case analysis, figure out where it’s useful, and figure out where it’s actually going to be very helpful.
And don’t just run bootcamps for technology workers, run bootcamps for everybody. Give them access to tools, figure out what use cases they develop, and then use that as a basis to rank and stack them and put them into play.
AI is not going to replace humans, but humans with AI are going to replace humans without AI.
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