SAS: A Tool to Measure Your GenAI Adoption Maturity

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To help organizations responsibly harness the full value of Generative Artificial Intelligence (GenAI), SAS – a global leader in data and AI – has launched the GenAI Maturity Assessment , an interactive tool designed to support companies on their journey to adopt this technology.

Through a series of multiple-choice questions, telegram data the tool allows companies to quickly understand their level of maturity in the use of GenAI. At the end of the questionnaire, each organization receives a personalized report that classifies them as “ observers ”, “ explorers ” or “ leaders ”, offering useful indications to orient themselves with greater awareness. The report also provides insights on how competitors in the sector are moving and offers practical recommendations for responsible and sustainable implementation.

“ As companies continue to invest heavily in AI technologies, it is important for each of them to know whether these investments are making a difference,” said Marinela Profi , Global AI and GenAI Strategy Lead at SAS. “This assessment helps them understand where they are starting and what steps they need to take to move forward, using an effective GenAI blueprint that includes governance, data security and ethical implementation.”

Adoption on the Rise, But Not Without Challenges
The launch of the tool comes amid new global research commissioned by SAS from Coleman Parkes, Generative AI Global Research: Strategies for a Competitive Advantage , which surveyed 1,600 decision makers around the world. The study explores GenAI adoption across major industries, highlighting opportunities and challenges.

The research paints a picture of great excitement: 86% of companies have already started investing in GenAI and one in five plans to adopt it at the enterprise level in the near term. However, the rush to experimentation often happens without adequate preparation. Only 10% of companies consider themselves fully prepared to comply with emerging regulations, while fewer than one in twenty have reliable systems in place to assess bias and privacy risks in large language models.

Despite these weaknesses, the initial results are encouraging. 89% of companies report an improvement in employee satisfaction, 82% report a reduction in operating costs, and another 82% observe an increase in customer loyalty.