KPMG Report Shows Executive Trust Gap in Data and Analytics

This year’s already shaping up to be a transformative period for data-driven organizations and the regulatory environment, with a number of data management laws like GDPR taking effect. At the same time, 81 percent of IT leaders are investing in or plan to invest in AI, according to a 2017 study by Cowen. In the eye of this perfect storm is data privacy.

As today’s enterprise rapidly adopts machine learning and AI to make critical business decisions, questions and concerns regarding the amount of trust that we – meaning consumers, businesses, and governments – place in these advanced technologies proliferate.

C-suite executives show growing trust gap in data and analytics

KPMG, published a report on “Guardians of Trust” which explores the evolving nature of trust in the digital world based on a survey of nearly 2,200 global executives involved in strategy for data initiatives. The report shows a widening gap in how much trust is placed in the data and analytics that underpin critical business decisions. According to the results, more than 65 percent of executives have some reservations or active mistrust in their AI, data and analytics, while 92 percent are concerned about the negative impact of data and analytics on corporate reputation.

Who’s responsible for trust in the digital age?

Despite growing mistrust of data and analytics, executives are still unsure who should be accountable for algorithmic decisions that deliver poor business results, financial loss, or the loss of customers. According to the report:

The governance of machines must become a core part of governance for the whole organization. Chief executives and functional leaders will need to manage machines as rigorously as they manage their people.

Trust as a success factor

As trust becomes a key business success factor, it is helping drive awareness about how we collect, manage and use data. Organizations that have committed to become ‘AI-driven’ are recognizing that they need to think strategically about the data they use to feed their machine learning programs. And while they still have work to do in order to gain greater control of the data being fed into their algorithms, allowing them to speed up the deployment of AI and machine learning – just having these conversations about data management and data privacy is a fundamental step towards investing in the future of data science.  This opportunity to provide better, faster connectivity, transparency and control over the data which feeds AI is one that we’ve been working on for years.  It’s great to see this issue, and opportunity highlighted by the folks at KPMG.  

You can download the full KPMG “Guardians of Trust” report at