Adoption of Generative AI in Companies Quadruples in Just One Year

Generative AI implementations in companies have quadrupled in just one year, according to the study "Harnessing the value of generative AI: Use cases across sectors" by Capgemini's Research Institute. The report reveals that 80% of companies have increased their investments in generative AI since 2023, and three-quarters of organizations consider this technology essential for driving revenue and fostering innovation.

The research indicates that 97% of companies allow their employees to use generative AI in some form, and nearly a quarter of companies have already integrated it into their operations, a 6% increase from the previous year. Companies pioneering the adoption of this technology have seen significant improvements in operational efficiency ratios, customer experience, and sales growth, with an average 6.7% increase in customer satisfaction in areas where AI was implemented.

Pascal Brier, Chief Innovation Officer at Capgemini, states that generative AI is ushering in a new era for businesses by enabling profound transformation in business models, going beyond mere cost optimization and exploring new value creation opportunities. To accelerate this transition, Brier emphasizes the importance of reliable data, clear processes, and maintaining trust, transparency, and accountability in managing AI systems.

The study also points to the evolution of AI chatbots into multi-agent systems, which accelerate value creation and expand companies' ability to innovate and increase their return on investment. Despite ethical challenges, most organizations maintain high levels of trust in using these agents for specific tasks, such as writing emails, coding, and data analysis.

The widespread adoption of generative AI has also been facilitated by the growing accessibility of public tools to non-specialists, with only 3% of companies prohibiting their use in the workplace. However, the study warns of the need for clear guidelines to ensure the transparency and reliability of operations and to mitigate risks associated with the use of these tools.