It is now possible to demonstrate a tangible relationship between behaving in a way that instils trust and, ultimately, delivering better financial returns.
Using these AI-based tools, it is now possible to demonstrate a tangible relationship between behaving in a way that instils trust and, ultimately, delivering better financial returns in both the short and long term. A high trust rating reflects positively on customer and employee retention, price inelasticity and competitive advantage.
Demonstrating this correlation and causality between trust and financial performance also compels asset managers (who have a fiduciary duty to maximize returns for their investors) to look beyond traditional financial metrics.
What about other intangibles such as wellbeing, inclusion, talent, diversity, environmental impact, innovation and corporate governance? These are all important but, to date, have also proved difficult to measure effectively. This is now changing, thanks to the power of AI and the digitalization of business. Below are examples of three areas where AI can make a difference: culture; measuring environmental, social and governance (ESG) risks; and ESG reporting.
Culture and AI
Looking at the culture within a business is nothing new, but companies are increasingly investigating other measurement options beyond the traditional focus groups and staff surveys.
AI can analyze communications across an entire organization (including emails and messages on collaboration platforms), focusing on grammar, syntax, sentiment and keywords, and identify the tone within messages. (Clearly, when performing such analysis, attention needs to be paid to the appropriate privacy standards and regulations.) This helps to identify trends and to evaluate how healthy the culture within an organization truly is.
Measuring ESG risks using AI
Four of the top five global risks in terms of severity of impact are related to the environment or society, according to the WEF’s Global Risks Report 2020. This means the quantification of ESG risk is essential.
Again, AI can help. For example, companies could analyze and predict risks related to human rights issues among suppliers from a certain country or sector. And by screening social networks and news broadcasts, emerging risks could be pinpointed sooner.
AI makes it possible to aggregate the ESG-related information that is currently provided in various reports, to inform comparisons and decision-making by companies, market participants and ratings agencies.
ESG reporting and AI
Investors are actively looking for more disciplined and rigorous approaches to evaluating nonfinancial performance, particularly around ESG, as the recent EY Institutional Investor Survey showed. From the perspective of investment analysts and portfolio managers, there are significant advantages in using AI to make an informed judgment on corporate governance and industry-wide standards.
Unlike financial reporting, which follows a set of strict and uniform rules, ESG reporting is flexible and often dependent on what companies choose to disclose. The use of AI could prove beneficial here as ESG reporting becomes more prominent and consistent. In the interim, AI also makes it possible to aggregate the ESG-related information that is currently provided in various reports, to inform comparisons and decision-making by companies, market participants and ratings agencies.
Learning to use AI
It’s clear from these examples that AI is suited to the measurement of long-term value and, in particular, the attributes that drive long-term value in an organization. However, it should be used correctly and in conjunction with other technology. AI can improve the performance of companies, but not in isolation; rather, it should be regarded as part of a pool of new technological resources, alongside big data and blockchain.
There is also a learning curve to contend with. Many companies do not fully appreciate the potential of what can be achieved using AI, and individuals with the expertise to use it most effectively are in short supply. The level of insightful data gathered via AI – for instance, establishing the appropriate correlation between a range of KPIs – will evolve over time as companies become more adept in its application.
But, while it may be early days, companies should be getting to grips with this technology. If they don’t, their competitors will be.
Summary
Artificial intelligence (AI) can be used to measure new KPIs that are increasingly in demand as stakeholders focus on how companies create long-term value. KPIs involving trust, culture, ESG risks and ESG reporting can be measured using AI. But there is a learning curve, and organizations risk getting left behind if they do not understand what AI can do and have the people with the expertise to use it effectively.