Estimating and demonstrating your business value is the main barrier to adopting Artificial Intelligence
O Gartner, a world leader in research and advice for companies, announces that Generative Artificial Intelligence (GenAI) is the number 1 solution among the most implemented Artificial Intelligence technologies in companies.
According to Gartner research conducted in the fourth quarter of 2023, 29% of 644 respondents from companies in the United States, Germany and the United Kingdom said they have deployed and are using GenAI, and that it is the most frequently implemented Artificial Intelligence technology. GenAI has been identified as more prevalent than other solutions such as graphing techniques, optimization algorithms, rule-based systems, natural language processing, and other forms of Machine Learning (machine learning).
The survey also found that utilizing Generative Artificial Intelligence built into existing applications (such as Microsoft's Copilot for 365 or Adobe's Firefly) is the top use case, with 34% of respondents stating this is their primary method of use. This scenario is observed to be more common than other options, such as customizing GenAI models with prompt engineering (25%), training or tuning custom GenAI models (21%), or using standalone GenAI tools such as ChatGPT or Gemini (19%).
“GenAI is acting as a catalyst for the expansion of Artificial Intelligence in companies,” says Leinar Ramos, Senior Director of Analytics at Gartner. “This creates a window of opportunity for AI leaders, but also a test of whether they will be able to capitalize on this momentum and deliver value at scale.”
Demonstrating the value of Artificial Intelligence is the main barrier to its adoption: The main obstacle to the adoption of Artificial Intelligence, as reported by 49% of the research participants, is the difficulty in estimating and demonstrating the value of projects. This problem overcomes other barriers such as talent shortages, technical difficulties, data-related issues, lack of business alignment and trust in Artificial Intelligence. “Business value continues to be a challenge for companies when it comes to Artificial Intelligence,” says Ramos. “As companies expand AI, they need to consider the total cost of ownership of their projects, as well as the broad spectrum of benefits beyond improved productivity.”
Source: Gartner (May 2024)
“GenAI has increased the degree of adoption of Artificial Intelligence in companies and made topics such as training and IT governance much more important,” says the Gartner analyst. “GenAI is forcing companies to improve their Artificial Intelligence capabilities“, he adds.
Lessons from companies with maturity in Artificial Intelligence: “Companies that are struggling to obtain business value from the use of Artificial Intelligence can learn from companies that are more mature in using this technology,” says Ramos. “These are companies that are applying Artificial Intelligence more broadly across different business units and processes, deploying many more use cases that remain in production for longer.”
The research found that 9% of companies are currently mature in Artificial Intelligence and found that what sets these companies apart is that they focus on four fundamental capabilities:
- A scalable Artificial Intelligence operational model, balancing centralized and distributed capabilities;
- A focus on Artificial Intelligence engineering, designing a systematic way to build and deploy Artificial Intelligence projects into production;
- An investment in training and change management across the company;
- A focus on capabilities trust, risk and security (TRiSM) to mitigate the risks arising from Artificial Intelligence implementations and drive better business results.
“Mature AI companies invest in fundamental capabilities that will remain relevant no matter what happens tomorrow, and this allows them to scale their AI deployments efficiently and securely,” says Ramos.
Focusing on these fundamental capabilities can help companies mature and alleviate the challenge of taking AI projects to the production phase. Research shows that, on average, only 48% of AI projects reach production and it takes eight months to go from an AI prototype to implementation.
Gartner clients can read more at “Survey Shows How GenAI Puts Organizational AI Maturity to the Test.”
About Gartner for Information Technology Executives
Gartner for Information Technology Executives provides objective, actionable insights for CIOs and IT leaders to help them drive their companies through digital transformation and lead business growth. More information is available at www.gartner.com/en/information-technology.
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