BCG Six Steps to Bridge the Responsible AI Gap

As artificial intelligence assumes a more central role in countless aspects of business and society, so has the need for ensuring its responsible use. AI has dramatically improved financial performance, employee experience, and product and service quality for millions of customers and citizens, but it has also inflicted harm. AI systems have offered lower credit card limits to women than men despite similar financial profiles. Digital ads have demonstrated racial bias in housing and mortgage offers. Users have tricked chatbots into making offensive and racist comments. Algorithms have produced inaccurate diagnoses and recommendations for cancer treatments.

To counter such AI fails, companies have recognized the need to develop and operate AI systems that work in the service of good while achieving transformative business impact—thinking beyond barebones algorithmic fairness and bias in order to identify potential second- and third-order effects on safety, privacy, and society at large. These are all elements of what has become known as Responsible AI.

Companies know they need to develop this capability, and many have already created Responsible AI principles to guide their actions. The big challenge lies in execution. Companies often don’t recognize, or know how to bridge, the gulf between principles and tangible actions—what we call crossing the “Responsible AI Gap.” To help cross the divide, we have distilled our learnings from engagements with multiple organizations into six basic steps that companies can follow.

The Upside of Responsible AI

Concern is growing both inside and outside boardrooms about the ethical risks associated with AI systems. A survey conducted by the Center for the Governance of AI at the University of Oxford showed that 82% of respondents believe that AI should be carefully managed. Two-thirds of internet users surveyed by the Brookings Institution feel that companies should have an AI code of ethics and review board.

Much of this concern has arisen from failures of AI systems that have received widespread media attention. Executives have begun to understand the risks that poorly designed AI systems can create—from costly litigation to financial losses. The reputational damage and employee disengagement that result from public AI lapses can have far-reaching effects.

But companies should not view Responsible AI simply as a risk-avoidance mechanism. Doing so misses the upside potential that companies can realize by pursuing it. In addition to representing an authentic and ethical “True North” to guide initiatives, Responsible AI can generate financial rewards that justify the investment.

A Stronger Bottom Line. Companies that practice Responsible AI—and let their clients and users know they do so—have the potential to increase market share and long-term profitability. Responsible AI can be used to build high-performing systems with more reliable and explainable outcomes. When based on the authentic and ethical strengths of an organization, these outcomes help build greater trust, improve customer loyalty, and ultimately boost revenues. Major companies such as Salesforce, Microsoft, and Google have publicized the robust steps they have taken to implement Responsible AI. And for good reason: people weigh ethics three times more heavily than competence when assessing a company’s trustworthiness, according to Edelman research. Lack of trust carries a heavy financial cost. In the US, BCG research shows that companies lost one-third of revenue from affected customers in the year following a data misuse incident.

Brand Differentiation. Increasingly, companies have grown more focused on staying true to their purpose and their foundational principles. And customers are increasingly making choices to do business with companies whose demonstrated values are aligned with their own. Companies that deliver what BCG calls total societal impact (TSI)—the aggregate of their impact on society—boast higher margins and valuations. Organizations must make sure that their AI initiatives are aligned with what they truly value and the positive impact they seek to make through their purpose. The benefit of focusing strictly on compliance pales in comparison with the value gained from strengthening connections to customers and employees in an increasingly competitive business environment.

Improved Recruiting and Retention. Responsible AI helps attract the elite digital talent that is critical to the success of firms worldwide. In the UK, one in six AI workers has quit his or her job rather than having to play a role in the development of potentially harmful products. That’s more than three times the rate of the technology sector as a whole, according to research from Doteveryone. In addition to inspiring the employees who build and deploy AI, implementing AI systems in a responsible manner can also empower workers across the entire organization. For example, Responsible AI can help ensure that AI systems schedule workers in ways that balance employee and company objectives. By building more sustainable schedules, companies will see employee turnover fall, reducing the costs of hiring and training—over $80 billion annually in the US alone.


By Steven MillsElias Baltassis, Maximiliano Santinelli, Cathy CarlisiSylvain Duranton, and Andrea Gallego

BCG GAMMA is BCG’s global team dedicated to applying artificial intelligence and advanced analytics to business at leading companies and organizations. The team includes 800-plus data scientists and engineers who apply AI and advanced analytics expertise (e.g., machine learning, deep learning, optimization, simulation, text and image analytics) to build solutions that transform business performance. BCG GAMMA’s approach builds value and competitive advantage at the intersection of data science, technology, people, business expertise, processes and ways of working. For more information, please visit our web page.

Authors: Steven Mills, Partner & Associate Director, Data Science, Washington, DC: Elias Baltassis, Partner & Director, Paris; Maximiliano Santinelli, Associate Director, Data Science, Boston; Cathy Carlisi, Managing Director, BrightHouse, Atlanta; Sylvain Duranton, Managing Director & Senior Partner, Global Leader, BCG GAMMA, Paris, Andrea Gallego, Partner & Chief Technology Officer, BCG GAMMA, Boston