Most companies are struggling to realize Artificial Intelligence’s potential to completely transform the way they do business. The problem is, they typically apply AI in a long list of discrete uses, an approach that doesn’t produce consequential change. Yet trying to overhaul the whole Organization with AI all at once is simply too complicated to be practical.
What’s the solution? Using AI to reimagine one entire core business process, journey, or function end to end, say three McKinsey consultants. That allows each AI effort to build off the previous one by, say, reusing data or enhancing capabilities for a common set of stakeholders. An airline, for example, focused on its cargo function, and a telecom provider on its process for managing customer value.
Scaling up AI involves four steps: (1) Identify an area where AI will make a big difference reasonably quickly and there are multiple interconnected activities and opportunities to share technology. (2) Staff the team with the right people and remove the obstacles to their success. (3) Reimagine business as usual, working back from a key goal and then exploring in detail how to achieve it. (4) Support new AI-based processes with organizational changes, such as interdisciplinary collaboration and agile mindsets.
Idea in Brief
The Problem
Most companies aren’t setting themselves up to realize the full potential of AI. That’s because they focus on applying it in discrete use cases, which delivers only incremental change and requires much more effort to scale up.
The Solution
Organizations are most successful when they reimagine a core business process, journey, or function enabled by AI end to end. That allows each AI effort to build off the previous one, triggering an organic cycle of change.
How to Make It Happen
Leaders must help their organizations identify business domains where AI can make a big difference and target one or two for a complete overhaul. That will involve deploying new technology, redesigning operational processes, changing how people work together, and even fundamentally rethinking business models.
Most CEOs recognize that Artificial Intelligence has the potential to completely change how organizations work. They can envision a future in which, for example, retailers deliver individualized products before customers even request them—perhaps on the very same day those products are made. That scenario may sound like science fiction, but the AI that makes it possible already exists.
What’s getting in the way of that future is that companies haven’t figured out how to change themselves to meet it. To be fair, most have been working hard to incorporate digital technologies, in some instances genuinely transforming the way they serve their customers and manufacture their offerings.
To capture the full promise of AI, however, companies must reimagine their business models and the way work gets done. They can’t just plug AI into an existing process to automate it or add insights. And while AI can be employed locally across functions in a laundry list of specific applications (known as use cases), that approach won’t drive consequential change in a company’s operations or bottom line. It also makes it much harder and more costly to get AI to scale, because each far-flung team must reinvent the wheel with respect to stakeholder buy-in, training, change management, data, technology, and more.
But that doesn’t mean companies should try to overhaul the whole Organization with AI all at once. That would almost certainly end in failure. A complete makeover is an enormously complicated process involving too many moving parts, stakeholders, and projects to achieve meaningful impact quickly.
