One of the main drivers for adopting generative AI was to predict business performance and industry trends, Alteryx revealed.
Alteryx, Inc., an Analytics Cloud Platform company, has released its predictions for AI trends in the year 2024. These insights reflect a comprehensive understanding of the evolving business landscape and the revolutionary impact of data-driven AI technologies.
Karl Crowther, VP of MEA at Alteryx said, “Reflecting on the dynamics of the current business landscape of 2023, the new year offers opportunities to further push boundaries, explore uncharted territories, and utilise technology and innovation to redefine success in the Middle East’s dynamic business ecosystem. However, a business-wide approach to data-driven decision-making that empowers the entire workforce to take full advantage of technology such as AI is crucial to success. Our focus for the coming year is to continue to simplify the complexities of data science and help democratise accessible AI through intuitive, low-code and no-code solutions that empower all to navigate this era of AI-driven intelligence.”
As business leaders strive to take advantage of this era of decision intelligence, the focus for every sector in 2024 will be on harnessing AI’s power for business value by making AI-driven decision-making accessible and secure for the entire workforce.
Alteryx recently surveyed data leaders globally and found that one of their top main drivers for adopting generative AI was to predict business performance and industry trends. As more organisations unlock the potential of generative AI, market share capture from direct competitors and expansion into adjacent markets will become the new norm.
The survey also revealed that the year 2024 is anticipated to see the development of robust governance frameworks that facilitate responsible and effective implementation of generative AI across enterprises. These frameworks are vital for managing risks associated with AI applications, including their embedded large language models (LLMs), the end users of those applications, and the exchanges between the first two.
