Strategic artificial intelligence efforts will go much farther than tactical deployments. Okay, fine – but what makes an AI effort “strategic”?

The much-discussed 95%-fail study on generative AI published by researchers at MIT revealed that these efforts lacked a strategic focus, according to noted AI and analytics guru Tom Davenport, writing in a recent essay. “Its primary finding is that tactical, individual-level, broad-and-shallow implementations of generative AI don’t provide substantial value to the companies that employ them. Enterprise-level, deep-and-narrow generative AI projects that are consistent with a company’s business strategy, on the other hand, do often yield measurable value.”

Companies seeing success with AI, he adds, are those who see as a transformative force, versus merely productivity bumps or fancy pictures.

So what exactly does it mean to go with “strategic” AI approaches? That’s a source of confusion, related Sangeet Paul Choudary, founder of Platform Thinking Labs and author of Platform Revolution and Reshuffle, recently interviewed on Michael Krigsman’s CXOTalk program.

When executives today say, “We need an AI strategy,” when I ask them about it, very often what they mean is, “We want to figure out what we should do with AI,” Choudary explained. “And that sort of traps them within thinking about, ‘Here’s our business. How do we apply AI into it to get things cheaper, better, faster?’ But that’s not really what strategy is about. Strategy is fundamentally about answering two questions. Where do we play? How do we win?”

To understand the larger implications of AI, shipping containers provide a classic illustration of an industry disrupted and rebuilt. The impact of shipping containers a few decades back resulted in a reimagination of the entire industry.

“It’s an interesting parable to understand what’s possible with AI today,” Choudary illustrated. “When the shipping container was introduced, its first-order effects were seen as automation, because prior to that, we used to live in a world of break bulk cargo. You needed dock workers to go up and down a ship moving cargo off and on a ship. And that lack of standardization made port operations slow. So, when the shipping container was invented, people assumed that the port would get automated because cranes could move cargo on and off of ships.”

Automation of cargo movement was the first-order effect. And, like today with AI, there was great concern about job losses on the docks.

But the impact of shipping containers then rippled across the supply, distribution, and manufacturing chain. “What happened next was that trucks, trains, and ships agreed on a common standard for the shipping container, and that totally unlocked logistics at a global scale,” Choudary said. “Because now you could move shipment from source to destination completely seamlessly, and that made logistics reliable. And because shipping now became reliable from source to destination, the logic of manufacturing changed.”

That’s because previously, manufacturing was built around the assumption that shipping was slow and unreliable, requiring vertical integration and co-location of suppliers. But with reliable, standardized shipping via multi-modal containers, manufacturers could move to component-based production and global supply chains. “New jobs were created because of that component-based manufacturing and competition that emerged. And eventually, even countries rose and fell based on how they plugged into this new system of global supply chains.”

With AI, the cost of performing “certain forms of knowledge work dramatically collapses,” Choudary says. “For example, the cost and speed of translating a document was very high just a few years back, but today, it’s completely collapsed.” And as with dockside efficiency, the implications of AI go far beyond document movement. “The assumptions on which your business is structured fundamentally change, and with that, you have to reimagine your business, you have to reimagine what kind of competition will come, and you have to reimagine what’s the basis of advantage.”

To bring about the changes needed to grasp the implications – and therefore benefits – of AI, Davenport makes the following recommendations:

• Understand the differences between strategic versus tactical AI. In a strategic approach, AI is employed in an “organization’s overall strategy for how it goes to market and succeeds with customers. Strategic implementations of AI often cost more, take longer, and involve more people than tactical ones. They usually involve major change to business processes and business capabilities. Perhaps they are the basis of a new product line or a new relationship with customers.” On the other hand, “tactical returns from tactical AI projects generally involve easier implementation, and involve incremental change without a lot of senior management deliberation. Changes to business processes are usually relatively minor. In many cases, AI is being used to perform a task that is already done by humans.”
• Corporate culture matters, along with the mindset of leaders. “Choosing strategic versus tactical projects and returns is often dictated by the management and financial situation within the company,” he states. “Are senior leaders aware of what AI can do and motivated to employ it aggressively? Is the strategic intent for AI clearly defined and communicated across the company? Is there a deep experimentation mindset across the company? If these factors are in place, strategic projects will be a natural step to take. If they are missing, it is unlikely that any strategic project will be successful.”
• If a company is not ready to embrace strategic AI, start tactical and gradually weave the pieces together. At a minimum, companies should undertake tactical AI projects with an eye to how they might fit together to make possible a broader strategic objective.
• Identify the levers required to achieve AI value. “These levers many include changes in business strategy, leadership, culture, AI talent, organization, and technology,” Davenport says. “Pinpoint key gaps. Identify and evaluate alternative strategic initiatives, and tactical projects that could eventually produce strategic value, around a coherent vision for generating return.”
• Communicate and work with all levels of the business. Conduct sessions or workshops to achieve greater buy-in from both managers and employees.
• Monitor and measure. “Remember that strategic returns are measured in business change, not incremental savings. These deep changes to an organization won’t happen overnight, but the investment and effort over time to achieve them can position an organization for a long and successful future.”