We live in a data-driven world—data and analytics not only drive business decisions, innovation, and progress, but also profoundly influence the choices of employees and consumers. When making decisions, we increasingly rely on data rather than intuition. We embrace the power of information, shaping every aspect of our lives by reading reviews, assessing the probability of expected outcomes, and then making choices based on numbers.

However, as members of society, we also know that data can become tricky. Data can be manipulated to support a stance, advance a proposal, or push a narrative we want, rather than being presented objectively and without bias. Many people may feel a tug-of-war when trusting data: we understand we need data to make decisions and create better outcomes, but sometimes we don't know how to trust it.

Financial markets have largely overcome this trust gap. Due to regulation, transparency, and standards, shared financial data is inherently trusted. But in other areas, such as climate and AI—which can also have significant impacts on society—trusting data may be more difficult. How should organizations bridge this trust gap and build and maintain stakeholder trust that is crucial to advancing their work?

Putting trust at the core of value creation

The first priority is to prioritize trust to create value throughout the business. Prioritizing trust can manifest as leading with transparency or making strategic decisions that place "long-termism" above short-term profitability.

Take pricing as an example—an area where the trust gap is widening, and leaders can work to narrow it through transparency. When the reasons for price increases begin to weaken (such as costs or supply chain complexity), companies should be more prudent and open with stakeholders about the rationale behind pricing.

When problems arise, consumers equally crave transparency. Does the company proactively take responsibility, confront the issue, and communicate the path forward with consumers? If executives can build trust in good times, then when that trusted brand or organization faces challenges, or enters new areas to reinvent the business and drive growth—a strategic choice many companies face today—that trust will translate into customer loyalty. For companies that do it well, trust is transferable and therefore profitable.

Showing consumers and employees how data is protected

Sometimes, consumers face a fog of uncertainty about data—especially about how their own data is protected. Understanding privacy is crucial for employees and consumers in AI and technology fields and beyond.

Data from PwC's 2024 Trust Survey shows that,Bridging the trust gap meansfinding a balance between experience and a firm commitment to privacy. The survey shows that employees and consumers are highly concerned about data privacy policies—89% of employees and 88% of consumers say it's important for companies to disclose this information. In contrast, only 32% of executives say their companies actually do so, a strikingly low figure.

Trust is built through engagement—proactively and transparently communicating with consumers and employees about how you prioritize data protection. As strategies and technologies evolve, the trust you build will make stakeholders more willing to move forward with you.

Drawing conclusions from data with humility

Making decisions based on data often feels good—when numbers show that a business or product is driving expected outcomes, it's easy to feel confident. With AI and other technologies, we can often arrive at mathematical conclusions that support our agendas or beliefs more quickly.

But in this pace of rapid discovery, do we still leave room for alternative interpretations of data? Even in a data-driven world, stories have multiple facets. As leaders and team managers, we should create space for different interpretations of the same dataset. This approach is crucial for decisions of all sizes.

If you lack humility and a social perspective when addressing today's major societal and business issues, and fail to acknowledge that multiple interpretations may exist, you risk losing stakeholder trust by leaning too heavily toward one viewpoint. Drawing one-sided conclusions can give the impression that data is being manipulated, thereby undermining the author's credibility—this will undoubtedly widen the trust gap with your stakeholders and may hinder value creation or engagement in the future.

If stakeholders trust a company's data, then leveraging AI for growth and making an impact in areas like climate change will present tremendous opportunities. Recognizing this opportunity requires engagement, transparency, and humility—these human efforts will help drive progress.