Humans should be involved in Ai decision-making

93% of business leaders believe humans should be involved in artificial intelligence decision-making.

77% of respondents are concerned about the timeliness or reliability of the underlying data.

29% said they are very confident that AI and machine learning (ML) are being applied ethically in business.

73% of business leaders are feeling pressure to implement AI at their organizations.

80% agree AI and ML helps employees work more efficiently and make better decisions.

72% of respondents said their organization lacks the skills to fully implement AI and ML.

Nearly three-quarters (73%) of business leaders are feeling pressure to implement AI at their organizations, but the vast majority are wary of giving up too much decision-making power. In the survey of 1,000 business decision-makers from around the globe, 93% said it's important for humans to have oversight of AI or ML when making significant decisions.

"Business leaders understand that AI and ML are critical to success in the future of work," said Jim Stratton, chief technology officer, Workday. "But enterprise organizations continue to lack the skills needed to implement the technology, and concerns around data integrity, ethics, and role elimination persist. Successful adoption of AI and ML require a commitment to keeping humans in the decision-making loop and working with partners who are committed to responsible AI and maintaining data integrity."

Despite the Case for AI Adoption, Concerns About Ethics and Data Accuracy Remain

More than 90% said they currently use AI within their operations for managing people, money, or both, and 80% agree AI and ML helps employees work more efficiently and make better decisions. The need for investment in this area is clear – 80% of respondents agree that AI and ML are required to keep their business competitive.

But despite wide-spread adoption and broad agreement around the case for AI and ML in the enterprise, concerns remain about its accuracy, ethics, and security. In fact, 77% of respondents are concerned about the timeliness or reliability of the underlying data, 39% consider potential bias to be a top risk when considering AI, and 48% cite security and privacy concerns as the main barriers to implementation. Only 29% said they are very confident that AI and ML are being applied ethically in business right now, but they are more optimistic about the future – with more than half (52%) saying they are very confident it will be applied ethically in five years' time.

Outlook for Workers is Optimistic, But New Skills Will Be Required

Business leaders are considering AI's impact on the workforce of today and tomorrow. Nearly half (45%) believe AI and ML will benefit workers, augmenting workloads and creating new career paths. 43% are more cautious, warning that AI and ML will replace some tasks, causing some unemployment among workers. 12% are more doubtful, saying that AI and ML will replace humans completely and have a negative impact on workers.

While leaders agree it is critical for humans to be involved in AI decision making, the survey also found a critical skills gap to successful AI implementation. Nearly three-quarters (72%) of respondents said their organization lacks the skills to fully implement AI and ML, and an even slightly higher percentage (76%) said their own knowledge of AI and ML applications needs improvement.

The full findings from the study identify widespread recognition of the potential for AI to transform enterprise business processes – along with significant gaps in how to get there.