"But their "small" counterparts aren't far behind. And as questions swirl about whether AI can actually generate meaningful returns (ROI), organizations should take notice. Because, as it turns out, small language models (SLMs), which use far fewer parameters, compute resources, and energy than large language models to perform specific tasks, have been shown to be just as effective as their much larger counterparts."
"SLMs are proving to be an ROI savior. Ultimately, SLM-enabled agentic AI delivers the best of both SLMs and LLMs together - including higher employee satisfaction and retention, improved productivity, and lower costs. And given a report from Gartner that said over 40% of agentic AI projects will be cancelled by the end of 2027 due to complexities and rapid evolutions that often lead enterprises down the wrong path, SLMs can be an important tool in any CIO's chest."
Small language models (SLMs) use far fewer parameters, compute resources, and energy than large language models while performing specific tasks with comparable effectiveness. SLMs reduce costs and can deliver stronger ROI. Agentic AI combining SLMs and LLMs can raise employee satisfaction and retention, improve productivity, and lower costs. Gartner predicts over 40% of agentic AI projects will be cancelled by end of 2027 due to complexity and rapid change, making SLMs a pragmatic option. In IT, SLMs automate ticket handling, routing, approvals, workflow orchestration, autonomous resolutions, and knowledge access. In HR, SLMs personalize employee support, streamline onboarding, and handle routine inquiries with privacy and precision.
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