By leveraging out-of-the-box AI solutions, improving internal knowledge sharing, and investing in training, companies can overcome these obstacles and successfully implement AI projects, driving strategic objectives and increasing profitability. This is highlighted by Qlik, in its latest surveys on the AI sector, where it reveals the main obstacles that hinder the progress of AI globally and suggests ways to overcome them.
“This study shows that CEOs know the value of AI, but face a multitude of barriers that prevent them from moving from proof of concept to deploying the technology to create value. The first step in creating an AI strategy is identifying a clear use case, with defined objectives and KPIs,” says James Fisher, Chief Strategy Officer at Qlik.
Main barriers to AI implementation
The survey identifies several critical barriers to successful AI implementation, including lack of AI skills, governance issues, and resource shortages. These challenges often result in many AI projects getting stuck in the planning stages. To address these issues, companies operating globally are increasingly turning to “off-the-shelf” AI solutions as the preferred option to kick-start their AI initiatives and achieve a return on investment.
AI projects stuck in planning or abandoned
Despite the high importance placed on AI, with 88% of C-suite executives considering it essential or very important to achieve strategic objectives and increase profits, few projects advance beyond the planning phase. Many are abandoned completely.
61% of companies are reducing their investment in AI due to lack of trust
The survey reveals that 20% of companies globally have between 50 and more than 100 AI projects in the definition or planning stages that are not yet real projects. Additionally, another 20% have had up to 50 projects in the planning phase or more advanced, but have stopped or canceled them entirely.
To maximize the return on investment in AI and provide better service to customers, it is crucial that organizations advance more AI projects from planning to implementation. Given the difficulty of achieving this, 74% of respondents see greater value in “off-the-shelf” AI solutions to improve implementation.
Skills gap, trust and governance issues among main barriers
Several factors slow down or completely block AI projects, the most significant being a lack of skills to develop (23%) and deploy (22%) AI, followed by data governance issues (23%), budget constraints (21%). %) and the lack of reliable data that AI can work with (21%).
Although there is a high level of understanding of the need for AI for business—95% of respondents say they know what types of AI could be used in their company—trust issues within the company appear to be holding back progress in certain areas. sectors.
More than a third (37%) of AI decision makers report that senior managers do not trust the technology, and 42% believe that lower-ranking employees do not trust it either. Additionally, 21% think their customers don’t trust AI. Worryingly, 61% say this lack of trust is significantly reducing AI investment in their company.
Build trust to advance AI
Improving internal knowledge sharing between the company and its customers can help increase trust and, consequently, investment, as 74% of respondents want to raise awareness of the benefits of AI within their organization and among their clients.
Training employees in the development and use of AI is another way to build trust and ensure that AI projects move beyond planning and are successfully implemented.
Globally, 65% of decision makers surveyed believe their country has the potential to lead in AI skills in the next five years. To achieve this, 76% think their industries must do better at training and developing skills for AI, and 75% believe their government must provide more AI funding and training.
