Most of us are familiar with the concept that it is better to fix the cause than the effect. This idea is at the core of the Lean Manufacturing concept, created by Taiichi Ohno and Toyota, and of the Lean Start-up movement started by Eric Ries.
Even though we’re aware of this principle, we very often end up doing the opposite. It is natural to just fix the effect, as it is faster and the results are easier to see. Yet in the long run you lose time and money with this method, because, with the root cause unfixed, the same effect will occur.
The future of technology holds amazing sci-fi -like tools. Nano technology, bio engineering, genetics, robotics, space-travel and so on. But the only tool that can help us fight the root cause of poor productivity and resource wasting is development of Artificial Intelligence, AI. All the listed technological advantages aim to increase the efficiency of human activities, but the difference is that AI is the only one that can help us understand which activities are worth doing in the first place, and how to do them in the most efficient way. For example, while robotics help us do things in high efficiency, maybe that activity was not needed at all in the first place. In other words, while AI can give us the GPS coordinates to our destination and map to follow, robotics can only make us move incredibly fast, and us humans decide on the direction in which we want to move. My example of robotics comes from physical production, but the same idea applies also for product design, marketing, HR and so on.
Our world is not lacking food, physical resources or talent. Yet we are wasting all of these in staggering amounts daily, especially human talent. We need improvement in use of the world’s resources, and for this AI is the most important technology.
The significance of AI has been recognized widely, and all major technology companies are involved in developing ways to improve the technology and offer multiple ways to implement it to our lives. Even though the benefits of AI management tools are clear, strong incentives exist in the modern global market to fight against the “AI manager”.
AI management tools would steer companies toward long-term, sustainable growth, but the contemporary stock exchange and market place encourages to seek short-term profits. Since investors want to see short-term value increase in the companies they invest in, the managements they name have incentives to sacrifice long term plans over short-term ones. This is obviously nothing new, but every time AI takes a step forward, the decision to act against facts will have a higher opportunity cost. Eventually this cost will be so high that it cannot be ignored, but the sooner we can bring AI into decision-making, the better. And since we are fighting issues like global warming and other ecological disasters, there really is no time to waste.
Fighting against better solutions sounds counter-intuitive, but the world is full of similar examples where existing structures prevent obvious improvements from taking over. Why do they still have separate taps for hot and cold water in the UK? Why do Phillips-head screws still exist when we have Torx screws? Why don’t all cars come with Run Flat tyres? The Run Flat tyres, the PAX system, is especially interesting. The PAX solution offers better safety and flexibility for the customer, the technology was shared with multiple tyre and car manufacturers, and market studies show that the demand is there, but still we are not using it. The answer lies in co-adaptation and co-innovation risks. When there is some external entity in the supply chain that is not benefiting of the improvement, they will not be active in taking it into use, or, even worse, they might fight against the change. This theory and the PAX system example is presented in Ron Adner’s book The Wide Lens.
Technology is advancing faster day by day. AI management tools will be the most significant of all upcoming advances because they will make all other advancement faster. Improving the technology and creating applications for it is not enough, as there are obstacles to solve before AI is widely taken into use. Finding ways to smooth the path for AI to enter our world is the second most important task we face now, right after AI itself. And these two tasks will be the last ones us humans will have to do on our own.
“There is nothing quite so useless as doing with great efficiency something that should not be done at all.” – Peter Drucker
Lean Startup: http://theleanstartup.com/
The Wide Lens: http://thewidelensbook.com/
The PAX- system: https://en.wikipedia.org/wiki/Michelin_PAX_System
Deep Knowledge Ventures, the first company to appoint AI to its board of directors: http://www.deepknowledgeventures.com/