A minority of organizations are already deriving value from AI, while the majority suffer from false expectations and a lack of trust in the data.

Although the potential benefits of AI are enormous, a recent report from Capgemini shows that only a small proportion of companies are fully exploiting the technology’s capabilities. Capgemini surveyed 500 technology managers and 504 business managers for the study.

The report shows that the adoption of AI varies greatly among companies. Only a small percentage of organizations are described as Data Masteruses AI effectively to achieve meaningful business results. These organizations use AI not only for data analysis but also for predictive and prescriptive decisions that give them a competitive advantage.

However, such implementations are the exception: only just under 16 percent of the organizations surveyed fall under the Data Master label. Most companies are lagging behind in the introduction of AI.

Reactive vs. proactive

Many companies are still in the early stages of AI adoption and their decision-making processes are still largely reactive. According to Capgemini, this means they focus primarily on descriptive (what happened) and diagnostic (why did it happen) analytics.

Only 23 percent of companies use predictive analytics (what might happen), and even fewer (eighteen percent) use prescriptive approaches (recommendations to improve outcomes). In addition, only eight percent of organizations use autonomous or self-optimizing approaches, where AI systems help make decisions to achieve specific goals.

Challenges in introducing AI

A major obstacle to effective AI adoption is data quality. Many companies struggle with poor data quality, which impacts the accuracy and reliability of AI models.

In addition, there is a trust gap between business and technology managers regarding the reliability of the data, which further hinders AI adoption. Only 20 percent of business leaders say they fully trust the data they receive, while 62 percent of technology managers believe their business users trust the data.

The report also highlights the lack of alignment between data/AI strategies and overall business strategies in many organizations. Thirty-eight percent of executives believe their company’s data/AI strategy is aligned with their business strategy, compared to 56 percent of technology executives. This discrepancy leads to AI initiatives that do not deliver the expected business value.

Transformative role for AI

AI can help companies achieve significant improvements in operational efficiency and productivity. According to the report, data masters achieve, on average, nineteen percent higher operational efficiency than their peers.

For example, data masters are using AI to increase customer loyalty through personalized interactions and improved customer service. AI models can analyze customer preferences and predict which products or services are likely to be attractive, allowing companies to optimize their marketing strategies and increase customer satisfaction. The report shows that data masters achieve a 22 percent reduction in customer churn, which is 87 percent more than other companies.

The path to better acceptance

To effectively integrate AI, companies must take a strategic approach that aligns with their business objectives, addresses data quality issues, and fosters a culture of data-driven decision-making. The report recommends that companies establish an AI and analytics center of excellence (CoE) to coordinate and manage AI activities, drive innovation, and help become a truly data-driven organization.