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The Rise of the AI-Powered Company in the Postcrisis World (BCG)

Global shocks bring moments of truth and companies that make bold moves during challenging times can turn adversity into advantage. For example, the SARS outbreak of 2003 is often credited with giving rise to e-commerce giants such as Alibaba and, while companies such as American Express and Starbucks pivoted during the global financial crisis of 2008−2009 to digital operating models that enabled them to thrive and dramatically increase shareholder value.

In this sense, COVID-19 is likely to be no different from other crises. It will greatly accelerate several major trends that were already well underway before the outbreak and that will continue as companies shift their focus to recovery. For instance, rather than heavily concentrating sourcing and production in a few low-cost locations, companies will build more redundancy into their value chains. Consumers will purchase more and more goods and services online. And increasing numbers of people will work remotely.

We believe that the application of artificial intelligence will be immensely valuable in helping companies adapt to these trends. Advanced robots that can recognize objects and handle tasks that previously required humans will promote the operation of factories and other facilities 24/7, in more locations and with little added cost. AI-enabled platforms will help companies better simulate live work environments and create on-demand labor forces. Through machine learning and advanced data analytics, AI will help companies detect new consumption patterns and deliver “hyperpersonalized” products to online customers. The most successful use cases will be those that seamlessly combine AI with human judgment and experience.

During the four previous global economic downturns, 14% of companies were actually able to increase both sales growth and profit margins, according to BCG research. The majority of companies, however, are at the very early stages of the journey—or have yet to begin.


We believe a successful AI-centered operating model needs to integrate human judgment and experience at its core. Here are 5 guiding principles to building what we call a “human plus AI” operating model:

1. Bring leadership onboard by building the case for change. Strong leadership commitment is key to successful transformations. One powerful way for the leader of an AI initiative to convince the CEO or board to support bold moves is to demonstrate how little the company is gaining from AI compared with its competitors. A simple acid test: ask the CEO or board members if they can identify at least two critical, strategic processes where the consensus is that AI can make a real difference. Then ask if they think the company has made progress on those fronts. Failure to answer yes to both questions means the company isn’t doing AI right and dramatic change is needed.

2. Reimagine the organization with AI at its core. Once a company’s leadership has come to support bold change, it should consider another disruptive question: How would a new AI-based firm provide the same, or enhanced, value to its customers? Answering that question requires a shift away from the traditional tradeoff between scale and marginal costs. Everything should be based on human plus AI—so long as AI adds value. As Alibaba’s chief strategy officer, Ming Zeng, has said, “Your firm must enable as many operating decisions as possible to be made by machines fueled by live data.”

3. Transform into a human-powered AI company. Even with AI placed at the core, it is crucial to avoid a “zero-human mindset.” Indeed, the human role must be elevated to ensure that there is no area in which AI operates unchecked. Even the most autonomous algorithms and applications need humans to provide the contextual understanding and expertise that AI typically lacks, and to guard against bad judgment or biases. At one point during the COVID-19 crisis, for example, website traffic on a popular British online grocery marketplace soared fourfold. The company’s AI-based cybersecurity software interpreted this spike as evidence of a denial-of-service attack and acted to block new transactions. Fortunately, company staff were standing by to correct that mistake.

4. Contain or discard legacy processes. When reinventing the company for AI, it is important to redesign legacy processes, technology, and organizational structures from the top down. Trying to augment preexisting workflows and legacy ERP platforms by “plugging in” AI is a mistake. Realizing the potential of AI requires consistent, companywide application. And while the top-down redesign of organizational structures allows for the elimination of unnecessary layers, that doesn’t mean everything has to go. Certain applications and infrastructure that have strong interfaces and are able to connect with the central data infrastructure can be retained. But these features should be assessed after the redesign, and the desire to retain them cannot be allowed to influence the transformation.

5. Prepare people now for the change. AI systems require a fundamentally different mindset and new capabilities. Preparing employees for change is critical. An absence of leadership and organizational support can cause users to detach, cede responsibility, and avoid risk. Companies must provide employees with on-the-job learning opportunities to master new skills. At a bare minimum, they must understand what AI can and cannot do so they’re able to work with the new technology.

To read the full BCG article, please click here.


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