New research from Gartner has revealed that generative Artificial Intelligence (GenAI) is the most frequently deployed AI solution in organisations, ahead of graph techniques, optimisation algorithms, rule-based systems, natural language processing, and other types of machine learning.

Conducted in Q4 2023, the survey found that 29% of the 644 respondents from organisations in the U.S., Germany, and the U.K. have deployed and are using GenAI.

"GenAI is acting as a catalyst for the expansion of AI in the enterprise," said Senior Director Analyst at Gartner, Leinar Ramos.

The survey revealed that the top method for fulfilling GenAI use cases is by embedding GenAI in existing applications, such as Microsoft's Copilot for 365 or Adobe Firefly, with 34% of respondents stating this as their primary method.

However, the adoption of AI is not without its challenges. "Business value continues to be a challenge for organisations when it comes to AI," Ramos said. The survey found that the primary obstacle to AI adoption, as reported by 49% of survey participants, is the difficulty in estimating and demonstrating the value of AI projects.

Despite these challenges, 9% of organisations are currently AI-mature, focusing on four foundational capabilities: a scalable AI operating model, a focus on AI engineering, an investment in upskilling and change management, and a focus on trust, risk and security management (TRiSM) capabilities. "GenAI has increased the degree of AI adoption throughout the business and made topics like AI upskilling and AI governance much more important," Ramos said.

"Organisations who are struggling to derive business value from AI can learn from mature AI organisations," Ramos said. "AI-mature organisations invest in foundational capabilities that will remain relevant regardless of what happens tomorrow in the world of AI, and that allows them to scale their AI deployments efficiently and safely."

According to the research, the journey from AI prototype to production is not a quick one. On average, only 48% of AI projects make it into production, and it takes eight months to go from AI prototype to production.