In brief
- The onus is on companies to define KPIs that provide a more holistic view of their activities and their long-term value drivers.
- AI can help to measure KPIs in areas such as: trust, culture, ESG risks, and ESG reporting.
- AI can improve company performance, but it should be used in conjunction with other technologies, including data analytics and blockchain.
Trust and financial performance
For example, AI is already being used to measure levels of trust – something that is vital to a company’s value. That’s because the way in which someone trusts a company or brand now will affect how they behave toward it in the future. While trust impacts consumers, suppliers and employees, it also impacts the company’s cost of capital insofar as it influences the views of capital providers and the capital markets. While these implications are clear, they are often difficult to report upon or measure directly.
Advanced analytics and AI can be leveraged to gather and aggregate large quantities of data, including data from multiple sources, and produce “trust scores” for a range of metrics such as integrity, consistency and openness. A variety of tools have been developed that address many versions of these so-called trust analytics, based on different attributes and factors. Companies and capital markets alike are increasingly using these tools to analyze market and consumer sentiment and understand the level of trust in a brand or organization. They can help companies to make managerial decisions, by directing them to areas of the business they need to enhance, while analysts and investors can use them to make investment and credit decisions.