By Jens Löhmar
According to the Workday report AI IQ: Insights on Artificial Intelligence in the Enterprise, 73 percent of business leaders feel increased pressure to adopt AI and machine learning (ML). There are three key barriers to their progress: ensuring that AI is based on high-quality data, establishing clear use cases, and addressing the skills gap.
ChatGPT has effectively brought the world of AI within reach of everyone. AI and Machine Learning (ML) are no longer futuristic concepts; they are here and more accessible than ever. The potential and promise that has been there for years is now more visible than ever. To capture the prevailing sentiment around this incredible technology, Workday partnered with the international research experts at Vanson Bourne. They carried out an independent assessment of how AI is being used today. These included 1,000 quantitative surveys, nearly 500 conducted in EMEA, and five qualitative interviews. The target personas for this study were senior decision-makers in HR, Finance, and IT working in organizations with more than 500 employees.
Our research uncovered something very significant: many people still don’t know how to use AI effectively. This is particularly true in large organizations, where AI and its subset, machine learning (ML), have been the talk of the town for a long time but haven’t delivered on their promised benefits due to issues with existing software, complicated workflows, company culture, and limited budgets. The issue of responsible use of AI is even more complicated. Many decision-makers are confused and directionless when planning, justifying, implementing, and making the most of AI and ML.
Ensuring that AI is based on good data
Bad data can mislead even the most sophisticated AI and ML tools. Of those surveyed, 77% are concerned that their organization’s data is neither timely nor reliable enough to use with AI and ML. Likewise, insufficient data volume or quality was the top reason (29%) for their AI and ML implementations not meeting expectations. As a CIO, your first challenge is to address this. Before you can reap the full benefits of AI and ML, it’s crucial to prioritize validating, accessing, and managing your organization’s data to meet the stringent requirements of these technologies. Also, look at your existing (legacy) applications and/or analytics solutions that use data from your current systems to see if your software architecture will support these new data needs.
Defining clear use cases
Almost everyone feels the need to move fast with AI, and this push usually comes from the top. Interestingly, however, the motivation for the pressure varies. For example, IT leaders feel pressured to be more competitive, while HR leaders feel pressured to improve the employee experience.
This demonstrates the importance of tailoring AI and ML to specific use cases. Regardless of the use case, most respondents recognize a common set of benefits associated with the adoption of AI and ML:
- Gaining a competitive edge.
- Increasing revenue.
- Improving customer and employee experience.
- Managing risk, fraud, and compliance.
- Improving operational efficiency.
- Make more informed decisions.
As a CIO, your role is critical in navigating this landscape. You need to take a strategic approach to ensure that AI and ML are effectively aligned with your organization’s unique goals and requirements.
Finding the right skills to make it work
The third major challenge in deploying AI and ML is finding the right people with the skills to make these technologies work effectively. Surprisingly, 72% of decision-makers believe that their organizations currently lack the skills needed to fully implement AI and ML. This skills gap is a significant barrier to realizing the full potential of these advanced tools. To address this challenge, CIOs need to invest in talent management, which includes not only training and educating existing employees but also attracting AI superstars to their organizations. This means actively seeking out individuals with expertise in AI and ML and creating an environment that is attractive to top digital talent. By doing so, businesses can better position themselves to take advantage of the transformative capabilities of AI and ML in today’s rapidly evolving business landscape.
Conclusion
As we’ve explored in this article, several key challenges stand in the way of adopting AI and ML to power the future of work. In the face of these challenges, Workday is here to empower CIOs like you to navigate the future of work with confidence. As the pressure to adopt AI and ML continues to mount, we’re committed to supporting your journey to a brighter and more innovative future.
Jens Löhmar is CTO of continental Europe at Workday
Workday is a leading provider of enterprise cloud applications for finance and human resources, helping customers adapt and thrive in a changing world. Workday applications for financial management, human resources, planning, spend management, and analytics are built with artificial intelligence and machine learning at the core to help organizations around the world embrace the future of work. Workday is used by more than 10,000 organizations around the world and across industries – from medium-sized businesses to more than 50% of the Fortune 500. For more information about Workday, visit workday.com.