Enterprises are moving beyond “bigger is better” AI. Small Language Models (SLMs) are emerging as a practical path to value, delivering targeted performance with far lower compute, latency, and cost than general-purpose LLMs—making them ideal for high-volume, domain-specific tasks across the business. This shift reflects a maturation of enterprise AI from experiments to production-ready solutions that scale efficiently and responsibly.
These organizations need a clear decision framework for choosing SLMs versus LLMs. Key criteria include task scope, latency targets, data sensitivity and compliance needs, deployment model (on-prem, cloud, edge), and the breadth of reasoning required. Many common workload patterns—customer support assistants, document classification and summarization, retrieval-augmented generation, edge/IoT inference, and multi-step agent workflows—tend to favor smaller models, delivering lower TCO and faster responses without sacrificing task-level accuracy.
In our latest market brief,
Leveraging Small Language Models for Enterprise AI: Benefits, Use Cases, and IBM’s Approach,
Futurum Research, in partnership with IBM, details the core benefits of SLMs and examines IBM’s Granite family as a case study in enterprise-grade SLMs—covering transparency, deployment flexibility, guardrails, and uncapped IP indemnification available through watsonx.ai.
In this brief, you will learn:
- The core advantages of SLMs: cost efficiency, low-latency performance, and easier fine-tuning for domain tasks.
- A practical decision framework for when to choose SLMs vs. LLMs, including deployment and compliance considerations.
- High-impact use cases: customer support, document summarization/classification, RAG, edge/IoT, and agentic workflows.
- How IBM’s Granite models enable enterprise transparency, governance, and legal protection, including Granite Guardian and IP indemnification via watsonx.ai.
- Steps to operationalize SLMs at scale and measure business impact across units.
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Leveraging Small Language Models for Enterprise AI: Benefits, Use Cases, and IBM’s Approach today to see how organizations can accelerate ROI while strengthening governance and trust.
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