Qlik, a global leader in data integration, analytics, and AI, has launched new research from a survey of 4,200 C-Suite executives and AI decision-makers, highlighting global barriers to AI progress and potential solutions to overcome them. According to the findings, key issues such as a lack of AI skills, governance challenges, and insufficient resources are hampering successful AI deployment. Many AI projects remain stuck in the planning stages, preventing organizations from realizing a return on investment in AI technologies.
Key Findings:
- AI Projects Stuck in the Planning Phase: Despite widespread acknowledgment of AI’s importance to organizational success (88% of senior decision-makers agree), many AI projects fail to move beyond the planning phase. 11% of businesses report having 50 to 100+ AI projects still in the scoping or planning stages, while 20% have had up to 50 projects that were paused or canceled after reaching planning or later stages.
- The Role of Ready-Made AI Solutions: With many AI projects stalling, 74% of AI decision-makers now view ready-made AI solutions as a good foundation for accelerating AI development. These solutions are increasingly seen as a reliable starting point for organizations to deploy AI and see returns on their investments.
Key Barriers to AI Progress:
- Lack of Skills: One of the primary reasons AI projects fail is the shortage of skilled talent. 23% of respondents cited a lack of AI development skills, while 22% pointed to challenges in deploying AI after it has been developed.
- Data Governance Issues: Governance challenges also stand in the way, with 23% of decision-makers highlighting difficulties in managing data for AI applications. These challenges can complicate AI projects and slow down progress.
- Budget Constraints: 21% of businesses face budget constraints that limit their ability to successfully roll out AI projects.
- Lack of Trusted Data: A further 21% of businesses are hindered by insufficient access to trusted data, which is crucial for AI systems to function effectively.
Trust Issues Impacting AI Adoption:
- Lack of Trust from Senior Management: Despite the general understanding of AI’s potential, 37% of AI decision-makers report that senior management lacks trust in AI. Additionally, 42% feel that lower-level employees have reservations about the technology, while 21% believe that customers also mistrust AI.
- Impact on Investment: The lack of trust is significantly hindering AI investment, with 61% of organizations reporting that it is reducing their AI investment.
Building Trust and Overcoming Barriers:
- Knowledge Sharing: Promoting AI’s benefits within the organization and to customers is key to building trust. 74% of decision-makers plan to focus on better knowledge sharing to increase understanding and trust in AI technologies.
- AI Training and Upskilling: Upskilling the workforce is another important strategy to overcome these barriers. 65% of AI decision-makers believe their country has the potential to lead in AI skills within the next five years, but to achieve this, 76% think industries need to be better at nurturing and upskilling staff for AI, and 75% believe government support is essential, including more funding and training programs.
Strategic Insights:
- James Fisher, Chief Strategy Officer at Qlik, stated:
- “Business leaders recognize AI’s value, but the challenges preventing the move from proof of concept to full deployment are significant. The first step is to identify a clear AI use case with defined goals and success measures, and to gather the skills, resources, and data necessary to scale it. Building trust and securing management buy-in is crucial to overcoming barriers and succeeding with AI.”
Organizations must address the barriers hindering AI progress, including lack of skills, data governance issues, and trust challenges. By focusing on ready-made AI solutions, upskilling staff, and fostering better knowledge sharing, companies can move AI projects forward and unlock the potential of this transformative technology.
