Tim Fountaine

Brian McCarthy

Tamim Saleh

<article-ideainbrief class="article-ideainbrief">
 <h4 class="ideainbrief-title">Idea in Brief</h4>
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  <h5>The Problem</h5>
  <p>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.</p>
  <h5>The Solution</h5>
  <p>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.</p>
  <h5>How to Make It Happen</h5>
  <p>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.</p>
 </div>
</article-ideainbrief><p>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.</p>

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<p>Most companies are struggling to realize artificial intelligence&#8217;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&#8217;t produce consequential change. Yet trying to overhaul the whole organization with AI all at once is simply too complicated to be practical.</p>
<p>What&#8217;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.</p>
<p>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.</p>

Getting AI to Scale

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.

Getting AI to Scale

Summary.

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