AI adoption: What’s holding companies and HR back?

Most business leaders understand that artificial intelligence (AI) can improve productivity and efficiency, but most companies have only just started to invest in enterprise AI tools, including generative AI. Specifically, many companies’ current investment in AI for HR is low, despite organizations being aware and excited about the value AI can bring to the HR function.

HR research scientists at SAP SuccessFactors conducted extensive research to understand the barriers organizations face with AI adoption. The team interviewed 79 HR and IT professionals from 59 SAP SuccessFactors customer organizations and gathered survey responses from 4,023 full-time permanent employees across regions and industries. The findings are consolidated in our new report HR’s Guide to Enterprise AI Adoption: Strategies for AI Governance and Workforce Engagement.

AI is a leading driver of digital transformation. Understanding the concerns organizations have around it and what causes those concerns can help companies overcome the barriers to AI adoption so they can leverage its full potential and value. Our research uncovered a number of barriers to greater AI adoption—including legal and psychological concerns—but one specific issue leads the list: AI governance.

Lack of AI governance is a top concern

The current state of AI governance in the organizations we interviewed is lacking in maturity: Two-thirds (67%) have no governance model at all. While most of these organizations were taking steps to develop one, some organizations were less proactive, planning to govern AI like any other technology purchase or relying on regional- or federal-level external governance.

About one-quarter (27%) of organizations have an AI governance model in place, but not for AI specifically in HR. The HR function was always included in these governance models, but an HR-specific model was not realistic given the variability in regulations across regions, and often HR professionals felt they needed greater representation in their organization’s broader governance models. Only 6% of organizations have a governance model specifically for AI in HR, often rolling up to a broader governance model but still accounting for the unique applications and data sources in AI for HR.

An AI governance model is crucial to ensuring businesses are developing, selecting, deploying, and using responsible AI. In addition to ensuring its employees use AI consistently, responsibly, and effectively, an organization’s AI governance helps ensure ongoing compliance with internal and external standards of AI ethics. Organizations hoping to improve their strategies for AI governance should consider three key factors, outlined in greater detail in the report:

• Stakeholders to be included
• Budget sources for AI solutions and investments
• Criteria to guide AI purchasing decisions

Overcome the barriers to AI adoption

What does it take for employees to adopt new AI tools in an organization? It’s best to ask the employee directly. The report on AI adoption identifies 10 of the top interventions to consider when encouraging a workforce to start using new AI tools. These interventions include providing training and support for using the new tool and the ability to provide feedback about the tool. Keep in mind interventions that improve enterprise AI adoption must be multifaceted and cross-functional.

Organizational leaders can take steps to improve AI adoption, including:

• Adopting an enterprise-level AI strategy for guidance
• Prioritizing alignment of AI decisions
• Exemplifying AI literacy, AI skills, and AI usage themselves

Using HR-specific AI capabilities, HR is uniquely positioned to improve AI adoption in several ways, such as:

• Adopting low-effort, high-reward AI use cases to get started
• Providing training to increase AI literacy and skills
• Addressing employees’ fears and hesitancy around AI

AI is reshaping the future of HR. Modern HR solutions that show employees how AI fits into the workplace to elevate their experience—plus, finding the right tools and strategy—can help boost AI adoption and drive meaningful results for organizations.