Enterprises See 45% ROI from AI Investments, Says Snowflake Executive
Snowflake's Head of AI, Baris Gultekin, recently discussed the growing trend of enterprises seeing strong returns on their AI investments, emphasizing how the technology is driving productivity, reducing costs, and automating tasks, even amid challenging macroeconomic conditions. Gultekin highlighted that the increasing demand for AI services is yielding tangible benefits for businesses, with Snowflake’s recent report revealing a 45% return on every dollar spent on AI.
AI Driving Productivity and Accessibility Across Industries
According to Gultekin, enterprises are reaping the rewards of AI-driven productivity gains, as processes that once took extensive time or expertise are now more accessible and efficient. He noted that the demand for AI is surging across industries, with companies increasingly seeing the return on their investments. "Everyone is very cost-conscious, and they are clearly seeing the returns on their investments," he said.
Also Read: Cortex Trade Launches AI-Powered Crypto Trading Platform
Snowflake's Focus on Indian Market and Services Sector
While Snowflake doesn’t have specific India-focused products, Gultekin highlighted the company’s focus on multimodal and multilingual data, which benefits customers in the region. Snowflake is also collaborating with Indian enterprises through proof-of-concept projects and co-building applications to improve AI ROI. Gultekin noted that the company is seeing significant demand from sectors like financial services, insurance, healthcare, manufacturing, and retail, where AI is used to enhance efficiency in handling large amounts of data and paperwork.
Overcoming Challenges in AI Adoption
However, Gultekin acknowledged some challenges in the enterprise AI landscape, including the need for companies to evaluate and monitor products before scaling them for large production use. Data silos remain a significant barrier, as AI requires large, accessible datasets. He also highlighted the ongoing costs of GPUs, which are still expensive for hosting large language models (LLMs). Snowflake recently optimized its Llama 3.1 model, reducing costs by 70%, reflecting the savings back to customers.
