![GenAI Forcing Organizations to Mature AI Capabilities — Gartner Report](http://media.assettype.com/cdomagazine%2F2024-05%2F3d8f9684-ce8d-47f9-9317-1d90b7fad51c%2Fai_cloud_concept_with_robot_arms_23_2149739749.avif?w=480&auto=format%2Ccompress&fit=max)
A Gartner survey conducted in the fourth quarter of 2023 marks GenAI as the most frequently deployed AI solution across enterprises. The survey report states that 29% of the 644 respondents from organizations in the U.S., Germany, and the U.K. have deployed and are using GenAI.
This makes GenAI the most frequently deployed AI solution and more common than solutions like graph techniques, optimization algorithms, rule-based systems, natural language processing, and other types of machine learning.
The survey also found that 34% of the respondents utilize GenAI embedded in existing applications (such as Microsoft’s Copilot for 365 or Adobe Firefly). According to the respondents, this is their primary method to use Gen AI, making it the top way to fulfill Gen AI use cases.
The lesser-used options included customizing GenAI models with prompt engineering (25%), training or fine-tuning bespoke GenAI models (21%), or using standalone GenAI tools like ChatGPT or Gemini (19%).
“GenAI is acting as a catalyst for the expansion of AI in the enterprise,” says Leinar Ramos, Senior Director Analyst at Gartner. “This creates a window of opportunity for AI leaders, but also a test on whether they will be able to capitalize on this moment and deliver value at scale.”
Around 49% of survey participants stated that the primary obstacle to AI adoption is the difficulty in estimating and demonstrating the value of AI projects. This issue surpasses other barriers such as talent shortages, technical difficulties, data-related problems, lack of business alignment, and trust in AI.
“Business value continues to be a challenge for organizations when it comes to AI,” says Ramos. “As organizations scale AI, they need to consider the total cost of ownership of their projects, as well as the wide spectrum of benefits beyond productivity improvement.”
However, Ramos mentions that GenAI has increased the degree of AI adoption throughout the business and made topics like AI upskilling and AI governance much more important. “GenAI is forcing organizations to mature their AI capabilities.”
“Organizations struggling to derive business value from AI can learn from mature AI organizations,” said Ramos. Gartner’s survey discloses that 9% of organizations are currently AI-mature. Focusing on the following four foundational capabilities makes the difference for them:
Having a scalable AI operating model, balancing centralized, and distributed capabilities.
A focus on AI engineering, designing a systematic way of building and deploying AI projects into production.
An investment in upskilling and change management across the wider organization.
A focus on trust, risk, and security management (TRiSM) capabilities to mitigate the risks that come from AI implementations and drive better business outcomes.