AI and Corporate Purpose

Today EY, SalesChoice, and The Bedford Group did an AI governance session with over a hundred executive leaders in Toronto to discuss the importance of Corporate Purpose in making technology decisions, especially regarding AI. One of the areas that we discussed was the new Navigator whitepaper that Dr. Sara Diamond and I wrote.

Corporate purpose includes a corporation or business focusing on its values, vision, and mission, and aligning the social, and environmental impacts, with a clearly defined business strategy.

Mark Carney, author of Values: Building a Better Future for All, defines purpose as operating on several planes. First, internally, it creates the necessary social capital within the firm to underwrite foundations of value creation: tightly functioning teams, and high employee participation and engagement. Secondly, it acts as a means of generating customer service and alignment. Third, purpose functions as a social narrative, helping to create and sustain the firm’s social license to operate.? At the highest level, purpose captures the moral contribution of companies to the betterment of the world now and in the future.

In our current global economy, we have many alignment challenges in advancing effective corporate decision-making aligned to corporate purpose and ensuring responsible and trusted AI practices are efficient and effective.

We live in a world where AI and machine learning influence every aspect of online technologies. Connectivity to the Internet continues to expand, which means that products and services reach an ever-growing network of business-to-business and business-to-consumer or customers. A Digital 2022 - Global Overview report found that across all devices, the average internet user aged 16 to 64 spends seven hours online daily. More than two-thirds of the world’s population now uses a mobile phone with unique users reaching 5.31 billion in early 2022.

With the internet ubiquity in place, and increased cloud server capacity, AI investments have skyrocketed, creating a global economy valued at $15.7tr.5

PWC research asserts that the total economic gains by 2030 will come from product enhancements, stimulating consumer demand. This is because AI will drive greater product variety, with increased personalization, attractiveness, and affordability over time. The greatest economic gains from AI will be in China (26% boost to GDP in 2030) and North America (14.5% boost), equivalent to a total of $10.7 trillion and accounting for almost 70% of the global economic impact.

Despite these growth dynamics, EY research and other leading organizations are highlighting that despite AI growth and investment, the return on investment (ROI) on AI use cases is on average at 15%. Cognizant released a report on AI: Data and ROI, and identified areas where returns are better bets, mainly in customer-facing applications

Volume is not the game we need to play.

Focusing on the most optimal use cases and ensuring corporate purpose is foundational is key. Leaders need to think harder about what they are doing and why. Taking quality time to dig deeply into the impact an AI use case will have on ecosystem stakeholders is a board governance responsibility in high-risk AI use cases, which currently, often board oversight is not connected to the technology adoption leadership practices.

Rather, leaders need to identify diverse use cases ranging from quick fixes to higher-risk solutions to ensure both agile emergence, and also ensure more corporate-wide diffusion approaches are underway.

At a governance level, executives must ensure they have a clear policy on AI and an ethics code of conduct to govern all operations. Also, educating all employees in a robust digital literacy strategy is a governance matter. Building a social narrative aligned with corporate purpose is a serious gap.

IBM reported in a Global AI Index 2022 study that 60% of organizations across the globe do not have an AI ethics policy in place, and 74% of organizations do not have practices to ensure there is no data bias in their data sets used to train AI models. These are only two of the many gaps identified in IBM's research.

To get ahead and close out these gaps and many more, board directors and CEOs need to ask governance questions like:

1. How does a specific AI technology impact and change our products or services?
2. What greater purpose or value does the adoption of this AI technology bring to our stakeholder community?
3. What strategies surrounding its adoption will keep us true to our purpose and values?
4. What disruptions will result? How will we address these? (Stakeholder technology impact maps, risk analysis, and mitigation, and communication strategies are critical tools when planning technology change.)
5. Given our commitment to climate change mitigation, do we have a circular economy strategy for this technology?

You can read more on this topic by downloading our research paper on Putting Corporate Purpose at the Center of Technology Decisions.