Prediction Machines: The Simple Economics of Artificial Intelligence

by Ajay Agrawal

The implementation of AI tools generates four implications for jobs:

Strategy

“only the paranoid survive,

Adopting AI in one part of the organization might require changes in another part.

When does a fall in the cost of prediction matter enough that it will change strategy?

How AI Can Change Business Strategy

This scenario neatly illustrates three ingredients that together could cause investment in that AI tool to rise to the level of being a strategic rather than operational decision.

First,

Second,

Third,

with a database of 3 billion past transactions and hundreds of other variables (including search terms and demographics), was able to create a prediction machine to handle the forecast.

For a prediction machine to change your strategy, someone has to create one that is useful to you in particular.

In the AI world, Google is Iowa.

using statistical prediction to overcome the biases of human baseball scouts and improve prognostication

A sabermetric analyst develops measures for the rewards that the team would receive from signing different players.

These analytics experts have mathematical skills, but the finest of them understand best what to tell the prediction machine to

do.

They provide j...

prediction and judgment are complements; as the use of prediction increases, the value of judgment rises.

using prediction machines in sports management means an increase in the value of people who have the judgment to determine payoffs and, therefore, the judgment to use predictions in decisions.

To make the most of prediction machines, you need to rethink the reward functions throughout your organization to better align with your true goals.

That is, if you have many years of data on, say, yogurt sales, then in order to predict yogurt sales using a prediction machine, someone will need that data.

We have highlighted three types of data—training, input, and feedback data.

Training data is used to build a prediction machine.

Input data is used to power it to produc...

Feedback data is used ...

Training data is used at the beginning to train an algorithm, but once the prediction machine is runn...

In other words, it may be valuable today, but it is unlikely to be a source of sustained value.

To do that you either need to generate new data—for input or feedback—or you need another advantage.

Because they operate at the decision level, the same is true for prediction machines.

They could then sell their modeling skills and, as a result, capture the value created by their insights. They abandoned this plan—likely for good reason—but in AI, this strategy might work. AI providers may try to disrupt traditional players.

“In this new era, only those who connect with other companies to build the next generation of cars will survive, while those who shut themselves up in a room making vehicles will die.”

The Simple Economics of AI Strategy

First,

prediction machines reduce uncertainty.

As the cost of AI falls, prediction machines will resolve a wider variety of strategic dilemmas.

Second,

prediction machine’s data become so important that you may need to change your strategy to take advantage of what it has to offer.

KEY POINTS

AI can lead to strategic change if three factors are present: (1) there is a core trade-off in the business model (e.g., shop-then-ship versus ship-then-shop); (2) the trade-off is influenced by uncertainty (e.g., higher sales from ship-then-shop are outweighed by higher costs from returned items due to uncertainty about what customers will buy); and (3) an AI tool that reduces uncertainty tips the scales of the trade-off so that the optimal strategy changes from one side of the trade to the other (e.g., an AI that reduces uncertainty by predicting what a customer will buy tips the scale such that the returns from a ship-then-shop model outweigh those from the traditional model).

Prediction machines will increase the value of complements, including judgment, actions, and data.

prediction machines enable managers to move beyond optimizing individual components to optimizing higher-level goals and thus make decisions closer to the objectives of the organization.

When AI Transforms Your Business

Where does your business end and someone else’s begin? Where exactly are the boundaries of your company?

This long-term decision requires careful attention at the organization’s very top level.

Prediction machines will change how businesses think about everything, from their capital equipment to their data and people.

AI might lead to strategic change.

First, lower cost versus more control is a core trade-off. Second, that trade-off is mediated by uncertainty; specifically, the returns to control increase with the level of uncertainty.

Machine learning startup Ada Support helps other companies interact with their customers.

“Half the money I spend on advertising is wasted; the trouble is, I don’t know which half.”