AI in 2025: SAS Predicts a More Specialized and Eco-Friendly Future

Artificial intelligence (AI) continues to drive significant shifts across industries, reshaping global business practices, with the Middle East, Türkiye, and Africa (META) region emerging as a leader in this transformation. According to the latest IDC forecast, AI spending in the META region is projected to grow at a remarkable compound annual growth rate of 37%, reaching $7.2 billion by 2026. SAS is at the forefront of this revolution, providing organizations with the tools and expertise to navigate their generative AI (GenAI) journeys, democratizing access to its platform and solutions to empower businesses to innovate and thrive.

A key focus for the AI industry is addressing its environmental impact. Faster and more efficient model training is essential for reducing AI’s carbon footprint. High-speed and algorithmic efficiency play a critical role in curbing cloud consumption. Similar to how advancements in energy efficiency transformed the home appliance and automotive industries, AI models must become more energy-efficient. Bryan Harris, Chief Technology Officer at SAS, emphasizes the importance of developing energy-conscious AI systems while advocating for sustainable energy sources such as nuclear power to support the growing energy demands of AI technologies.

The rapid rise of AI has also introduced significant risks, particularly in the form of AI-driven attacks. These threats, ranging from the manipulation of information to the erosion of social norms, pose risks to individuals, institutions, and democratic societies. Steven Tiell, Global Head of AI Governance Advisory at SAS, stresses the need for businesses to take proactive steps to mitigate these risks by establishing ethical AI practices. By doubling down on organizational values and implementing robust AI principles, policies, and controls, businesses can play a pivotal role in safeguarding civil discourse, elections, and cultural stability.

Data quality remains a critical determinant of AI success. As generative AI adoption accelerates, organizations are witnessing a divide between those thriving with advanced AI applications and those lagging due to poor data foundations. Marinela Profi, Global GenAI/AI Market Strategy Lead at SAS, warns that failing to address data quality issues will hinder AI performance, forcing businesses to abandon ambitious projects. The solution lies in organizations tackling pervasive data problems and ensuring AI systems are fed with clean, reliable data.

The initial excitement around generative AI is also transitioning into a more practical phase, as businesses shift from hyped expectations to delivering tangible value. Jared Peterson, Senior Vice President of Platform Engineering at SAS, notes that simplifying AI approaches and integrating large language models (LLMs) with specialized small language models (SLMs) will pave the way for meaningful advancements. This evolution highlights the importance of focusing on real-world applications over sensationalized expectations.

Environmental responsibility in the AI sector is a shared obligation. Jerry Williams, Chief Environmental Officer at SAS, highlights that both cloud providers and AI users must take accountability for minimizing the carbon footprint of AI operations. Optimized data and AI platforms are instrumental in reducing resource consumption, eliminating inefficiencies, and fostering sustainable practices. By adopting these strategies, businesses can align AI advancements with environmental stewardship.

The competitive landscape of AI is rapidly evolving. Fully AI-enabled organizations are expected to lead the IT sector by 2025, leveraging automation to enhance decision-making, identify opportunities, and foster innovation. Jay Upchurch, Chief Information Officer at SAS, believes these capabilities will distinguish market leaders from their competitors, emphasizing the critical role of operationalized AI in driving long-term success.

As LLMs become commoditized, the focus will shift to specialized applications and services built atop these foundational models. Udo Sglavo, Vice President of Applied AI & Modeling at SAS, predicts that open-source LLMs will decentralize the AI ecosystem, reducing reliance on dominant providers and promoting customization and integration as key differentiators.

In addition, AI and cloud advancements are prompting a significant transformation in IT infrastructure. Stu Bradley, Senior Vice President of Risk, Fraud, and Compliance Solutions at SAS, foresees a “Great IT Rationalization,” where businesses will simplify operations by modernizing on cloud-native, AI-powered platforms. This evolution will streamline vendor relationships, enhance agility, and maximize value by integrating data and decision-making capabilities across entire enterprises.

For marketers, generative AI is poised to move beyond simple content generation and productivity enhancements. Jennifer Chase, Chief Marketing Officer at SAS, envisions marketers using advanced tools such as synthetic data and digital twins, alongside established AI technologies like machine and deep learning, to deliver hyper-personalized campaigns while maintaining customer privacy. This shift will enable businesses to drive competitive advantages and revenue growth through innovative AI applications.

As AI reshapes industries and regional economies, SAS remains dedicated to empowering organizations to harness the potential of GenAI. By integrating cutting-edge solutions, democratizing access, and fostering innovation, SAS is helping businesses navigate the future of AI and drive growth across diverse markets.