Trustworthy GenAI Pipelines with Small Language Models
Keywords:
Enterprise GenAI Governance,Small Language Models (SLMs),Workflow Intelligence Automation,Governance-Aligned AI Pipelines,Responsible Enterprise AI,AI Compliance and Risk Management,Lightweight Language Models,Enterprise Workflow Orchestration,Secure AI Decision Systems,Explainable AI for Enterprises.Abstract
Governance-aligned Generative AI (GenAI) systems enable enterprise-grade GenAI capabilities by embedding governance safeguards directly into GenAI pipelines. Such pipelines instantiating enterprise workflows mitigate GenAI risks in GenAI model choices, foundation datasets, user prompts, and output consumption. Decisions regarding these GenAI pipeline elements should be made with the same formal structures and rigor applied to enterprise decision-making. A wealth of governance-aligned GenAI pipelines applied to enterprise processes would deliver comprehensive enterprise workflow intelligence at a fraction of the cost of traditional GenAI implementations.
For enterprises to harness Generative AI (GenAI) safely, enterprise governance objectives for GenAI must be realised. Candidates address the five enterprise corporate governance objectives—compliance, risk management, strategic alignment, performance and accountability—iteratively for all GenAI pathways; in computer science parlance, the task is to devise a breadth-first search through the enterprise GenAI pipeline graph. A foundational support system is a community-shared catalog of representative governance-aligned pipeline instances that address specific enterprise workflows or aspects thereof, deployed enterprise, domain or solution-wide with appropriate safeguards or controls. Candidate pipelines should instantiate enterprise workflows; the assets used in the pipeline or any GenAI input or output that may pose risk or compliance issues require particular attention. Enterprise workflows are risk scenarios against which GenAI adoption should be justified; pipeline adoption a risk-control measure.
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