The importance of trust in the era of data and AI
Data is king in today’s global economy. It informs decisions made at every level of business. Companies rise and fall based on how they leverage and store data and how much their customers trust them with their personal information. At the same time, regulators around the world are increasingly placing limits on how that data is gathered, stored and used.
This is why it’s crucial for businesses to build a social contract of trust around data-gathering and sharing.
So says Ian Fletcher, director of the IBM Institute for Business Value, Middle East & Africa, who will be speaking at the ITWeb Cloud, Datacentre & DevOps Summit, to be held on 11 February at The Forum in Bryanston.
During his talk, titled ‘Build your trust advantage: Leadership in the era of data and AI everywhere’, Fletcher will unpack the global and local results of the IBM Institute of Business Value: Global C-suite Study, now in its 20th edition.
Based on interviews with 13 000 C-suite executives across a range of industries around the world that are achieving market leadership by emphasising trust in their use and sharing of data, the study points to some key trends occurring globally.
It reveals that data-driven leadership is determined by the levels of trust an organisation can create,among its customers, the people inside the enterprise, and the partners across its ecosystem.
Fletcher will share how executive perceptions and approach to data-sharing and transparency divide the leaders against the losers in today’s data economy – with the leaders viewing building trust in customer relationships as a strategic imperative much more than other groups, and working hard to earn and maintain it.
According to Fletcher, IBM offers several recommendations to businesses.
Firstly, it’s vital to strengthen relationships with customers by revealing data about offerings and workflows, and using the trust advantage they’ve earned to create differentiating business models.
Next, businesses need to build confidence in data and AI models enterprise-wide.
Finally, companies have to learn how to share data on business platforms without giving away competitive edge.
"Turn the corner from amassing data to determining how best to monetise it, including how to build ecosystems to create new exponential value."