What’s Your AI Strategy?

This year he is the special advisor for artificial intelligence to the Connecticut legislature. He also holds a dual PhD in AI and in public policy from Carnegie Mellon University, three master’s degrees in computer science, operations research, and mathematics from Columbia University, and an LLM in Innovation and Information Law from New York University School of Law.

Alderucci is not given to hyperbole, so given his background he should be taken seriously when he says “AI is the most transformative technology that we’ve seen in our lifetimes. It’s only just beginning to affect our economy, and it will cause profound changes in the years to come. Executives need to understand AI’s potential and integrate it strategically into their organizations.”

Since 2018, Alderucci has taught two AI-focused MBA courses at Tuck. This spring, he will teach an Executive Sprint program called AI Transformation for Executives: Strategy, Implementation, and Organizational Change, a two-day live online program with Tuck Executive Education that provides participants with a comprehensive understanding of successful strategies and frameworks for AI adoption by firms.

We caught up with Alderucci to talk about the intersection of AI and business.

Tell us about the Executive Sprint program you developed and will teach this spring.

At a very high level, it is about AI strategy for firms. What that means is, what should my company be thinking about AI? What should the executives be thinking about so that we can fully utilize AI? An AI strategy is distinct from AI projects. Some companies have done pilot project after pilot project, testing out AI in different ways, applying it to different operations. But without a strategy, companies are often left not really accomplishing as much as they would like, even after investing in numerous AI projects. Several factors contribute to the gap between aspirations and achievements. In summary, a company strategy must be formulated to avoid some of the pitfalls that happen often during AI adoption.

How do you conceptualize the transformation an organization can make with AI strategy?

There are generally two phases to AI transformation of an organization. The first, and simpler, approach is using AI to enhance existing tasks and operations, such as helping to draft emails faster, analyze invoices more efficiently, and streamline everyday workflows. You might also automate your supply chain to reduce some human involvement to make things faster and less error prone. The second phase, which is more difficult but more profitable, is: what can we do with AI that we couldn’t do before? In other words, now that we have AI, what new operations and services can we bring to bear? That’s a very interesting problem to solve for any organization.

Can you give us an example of that two-part transformation that happened in a real company?

Amazon is a great example. When it started in the 1990s, it was primarily a bookseller. It used machine learning and analytics to manage its inventory and its pricing. It automated many things that workers in a brick-and-mortar bookstore would do. But then Amazon used AI to do things that existing booksellers didn’t and couldn’t do, thereby delivering new sources of value.  For example, it started collecting user ratings of products, a new service for clients. Ratings tell customers what others thought of a book. Similarly, Amazon began developing an understanding of each customer’s product preferences. So, if you and I bought most of the same things over the course of the year, Amazon would start to develop customer profiles that essentially say Kirk and Dean are similar in that respect. Therefore, if Dean buys products that Kirk hasn’t bought yet, Amazon can suggest that product to Kirk. Amazon can say “people like you, Kirk, have bought this.” Building that customer understanding is a quintessential machine learning and analytics task.

We all know AI technology is changing very rapidly. How do you advise firms and managers to navigate this shifting terrain?

First, you must take a different view of technology transformation than you might have traditionally. Some firms have gone through technology transformations with a five-year plan. With AI, a five-year plan is not entirely appropriate. What I advise more often is to have a two-year plan, and you need to really get into the weeds of what are you going to accomplish in those two years. You incorporate a lot of learning in the strategy. You build in a lot of flexibility because the technology is going to change rapidly. Finally, the plan must match the right tools to each challenge.

In your teaching and advising, what have you noticed is the biggest blind spot executives have about AI?

What I’ve personally seen is executives generally don’t dig into the details of AI. They might be familiar with chatbots, but they don’t understand the capabilities of AI. Part of that blind spot is executives may view AI as they have traditionally viewed new technology. They say, ‘I don’t need to know about networks; I have a person that handles my networks. I don’t need to know about cybersecurity; I have a CIO who does that.’ However, the distinction with AI is that it truly represents a disruptive force for most industries, whether in the short term or long term. I believe that AI will eventually be adopted by virtually every firm in every aspect of our economy. The companies that rapidly adopt AI and incorporate AI in their strategy will acquire a competitive advantage over the companies that don’t. The CEO, who is responsible for creating and sustaining the firm’s competitive advantages, must have a detailed understanding of AI’s capabilities and potential impact on the industry. Without this knowledge, they can miss opportunities from AI and can fail to anticipate the transformations it could bring to their firm.