Considering the AI Factory

Nicely covered by Irving:

The AI Factory: A New Kind of Digital Operating Model

“Whether you’re leading a digital start-up or working to revamp a traditional enterprise, it’s essential to understand the revolutionary impact AI has on operations, strategy, and competition,” wrote Harvard professors Marco Iansiti and Karim Lakhani in “Competing in the Age of AI”, a recently published article in the Harvard Business Review (HBR).  Earlier this year, they also published a book of the same title, which expands on the ideas in the article and illustrates them with a number of concrete use cases.

The age of AI is being ushered by the emergence of a new kind of digital firm.  Rather than just relying on traditional business processes operated by its workers, these firms are leveraging software and data-driven algorithms to eliminate traditional constraints and transform the rules of competition.  Managers and engineers are responsible for the design of the new AI-based operational systems, but the system then runs the operations pretty much on its own.

“At the core of the new firm is a decision factory - what we call the AI factory,” note the authors.  “[T]he AI factory treats decision-making as a science.  Analytics systematically convert internal and external data into predictions, insights, and choices, which in turn guide and automate operational workflows…  As digital networks and algorithms are woven into the fabric of firms, industries begin to function differently and the lines between them blur.”

The Industrial Revolution transformed the economy by developing a scalable, repeatable approach to manufacturing.  The AI factory is now driving another fundamental transformation by industrializing the data gathering, decision making, and overall digital operations of 21st century firms.  

The AI factory involves four key components:   

Data pipeline - the process which systematically gathers, cleans, integrates, and safeguards data;

Algorithm development, - the component which generate predictions about the future states of the business and drives its most critical operating activities;

Experimentation platform - the mechanism on which predictions are tested to ensure that they will have the intended effect; and

Software infrastructure, the systems that embed these various components in software and connect it as needed to the appropriate internal and external users. ..... 

(Much more at the link)   Will look at this more closely.