
Workday, Inc., a leader in enterprise cloud applications for finance and human resources, today published its latest global study examining how AI and machine learning (ML) will impact how the future works. The report, which is based on insights from 2,355 business leaders from the offices of the CEO, CIO, CHRO, and CFO, reveals that leaders are optimistic about the potential impact of AI and ML despite concerns about trust and data accessibility.
Key findings include:
- 98% of CEOs said there would be some immediate business benefit from implementing these capabilities.
- 47% of all business leaders believe AI and ML will significantly amplify human potential.
- 43% of all business leaders are concerned about the trustworthiness of AI and ML.
- 59% of respondents said their organizations’ data is somewhat or completely siloed.
- Only 4% of all respondents said their data is fully accessible.
“Despite some uncertainty, leaders are optimistic that AI and ML will augment their workforce and drive productivity,” said Jim Stratton, chief technology officer, Workday. “Trust is paramount to embracing these benefits, and building trust requires the right data foundation and commitment to governance. By implementing trustworthy solutions that prioritize data quality and transparency, companies can reap the rewards of AI and ML across their organization.”
AI and ML: Not Just Hype
CEOs and other business leaders know that AI and ML will impact their organizations, but some have been hesitant to fully embrace the technology. 71% said the global business landscape will be affected in the next three years, and 64% believe their organization as a whole will be affected by AI and ML in the next three years.
Nearly all (98%) CEOs surveyed said there would be some immediate business benefit from implementing AI and ML, with the top benefits being increased productivity, data-driven decision-making, and improved collaboration. Despite this, 49% of CEOs said their organization is unprepared to adopt AI and ML as they lack some or all the tools, skills, and knowledge necessary to embrace these technologies, and 28% of CEOs want to wait to see how AI and ML affect their organization before they decide on their approach.
Despite Uncertainty, Leaders are Optimistic
Among CEOs, 30% are concerned that employees will struggle to keep up with rapid changes as AI and ML become more integrated into their organization. In addition, 32% of HR leaders and 30% of finance leaders worry their teams will not have the technical skills they need to work effectively with AI and ML.
While leaders have concerns about the immediate effect AI and ML adoption will have on employees, they are ultimately optimistic about the overall impact. 47% of business leaders believe AI and ML will significantly amplify human potential, and 45% of CEOs believe AI and ML will create a more equitable and diverse workforce. 39% of CEOs believe increased productivity is the biggest potential benefit they see coming from AI, reinforcing the critical connection between technology and human potential.
So, What’s Holding Them Back?
Uncertainty about data and privacy, and a lack of trust are holding CEOs and other business leaders back from fully embracing and adopting AI and ML. 43% of all leaders surveyed said they were concerned about the trustworthiness of AI and ML, with 67% of CEOs citing potential errors as a top risk of AI and ML integration, reinforcing that lack of trust.
Increased transparency is needed to build trust, but siloed data is obscuring leaders’ ability to lean in. 59% of organizations surveyed reported that their data is somewhat or completely siloed. Only 4% of all respondents said their data is fully accessible.
For additional information:
- Read more about the survey on the Workday Blog, Global Study: C-Suite Optimism on AI and Why First Movers Win.
- Download the report, C-Suite Global AI Indicator Report: AI Is the Ultimate Level-Up.
- To learn more about how Workday is helping its customers navigate these challenges, register to attend Workday Rising, Sept. 26-29, 2023.
- Learn about Workday’s approach to responsible AI governance here.
- Read more about how Workday is leading the enterprise generative AI revolution here.


Archive
- October 2024(44)
- September 2024(94)
- August 2024(100)
- July 2024(99)
- June 2024(126)
- May 2024(155)
- April 2024(123)
- March 2024(112)
- February 2024(109)
- January 2024(95)
- December 2023(56)
- November 2023(86)
- October 2023(97)
- September 2023(89)
- August 2023(101)
- July 2023(104)
- June 2023(113)
- May 2023(103)
- April 2023(93)
- March 2023(129)
- February 2023(77)
- January 2023(91)
- December 2022(90)
- November 2022(125)
- October 2022(117)
- September 2022(137)
- August 2022(119)
- July 2022(99)
- June 2022(128)
- May 2022(112)
- April 2022(108)
- March 2022(121)
- February 2022(93)
- January 2022(110)
- December 2021(92)
- November 2021(107)
- October 2021(101)
- September 2021(81)
- August 2021(74)
- July 2021(78)
- June 2021(92)
- May 2021(67)
- April 2021(79)
- March 2021(79)
- February 2021(58)
- January 2021(55)
- December 2020(56)
- November 2020(59)
- October 2020(78)
- September 2020(72)
- August 2020(64)
- July 2020(71)
- June 2020(74)
- May 2020(50)
- April 2020(71)
- March 2020(71)
- February 2020(58)
- January 2020(62)
- December 2019(57)
- November 2019(64)
- October 2019(25)
- September 2019(24)
- August 2019(14)
- July 2019(23)
- June 2019(54)
- May 2019(82)
- April 2019(76)
- March 2019(71)
- February 2019(67)
- January 2019(75)
- December 2018(44)
- November 2018(47)
- October 2018(74)
- September 2018(54)
- August 2018(61)
- July 2018(72)
- June 2018(62)
- May 2018(62)
- April 2018(73)
- March 2018(76)
- February 2018(8)
- January 2018(7)
- December 2017(6)
- November 2017(8)
- October 2017(3)
- September 2017(4)
- August 2017(4)
- July 2017(2)
- June 2017(5)
- May 2017(6)
- April 2017(11)
- March 2017(8)
- February 2017(16)
- January 2017(10)
- December 2016(12)
- November 2016(20)
- October 2016(7)
- September 2016(102)
- August 2016(168)
- July 2016(141)
- June 2016(149)
- May 2016(117)
- April 2016(59)
- March 2016(85)
- February 2016(153)
- December 2015(150)