TLDR: A recent Salesforce survey of nearly 6,000 global knowledge workers indicates that the quality, accuracy, completeness, and security of data are critical factors determining workers’ trust in AI. Over half of AI users find it difficult to get useful outputs from AI, with many distrusting the data used to train these systems, posing a significant risk to AI adoption in enterprises.
A comprehensive survey conducted by Salesforce among nearly 6,000 global knowledge workers has brought to light a crucial challenge facing the widespread adoption of Artificial Intelligence in the workplace: data quality and trustworthiness. The study, titled ‘Your Data, Your AI,’ reveals that the integrity and handling of data will ultimately ‘make or break’ employees’ confidence in AI technologies.
According to the findings, a significant 56% of AI users report difficulty in extracting useful information from AI systems currently. This sentiment is further underscored by the fact that over half (54%) of workers express distrust in the data utilized to train these AI systems. A staggering 75% of those who distrust AI training data also believe that AI lacks the necessary information to be truly useful in their roles. This skepticism directly impacts adoption, with 68% of workers who distrust AI data also being hesitant to adopt the technology.
The survey emphasizes that accurate, complete, and secure data is paramount for building trust in AI, a sentiment echoed by more than three-quarters of the workforce. Wendy Batchelder, SVP, Chief Data Officer at Salesforce, highlighted this point, stating, ‘The future of enterprise AI isn’t about more data – it’s about the right data. When AI is grounded in a company’s own data, it delivers more useful results and ultimately drives greater trust and adoption.’
Also Read:
- Salesforce Report Highlights AI Agents as Pivotal for Enhanced Security and Business Growth
- UK Government’s AI Investment Surges Amidst Persistent Data Quality Challenges
Key factors that erode trust include out-of-date public data, which 62% of workers say would break their trust in AI, and consistently inaccurate outputs, cited by 71% of respondents. While eight out of ten business leaders anticipate generative AI will reduce costs and boost revenue, the survey clearly indicates that successful deployment hinges on grounding AI outputs in trusted customer data. The research suggests a significant ‘trust gap’ that must be addressed for organizations to fully realize the benefits of AI across their operations.
