INDUSTRY VIEW decisions, and request corrective action when unintended outcomes arise. Ethical guardrails are no longer philosophical ideals they are essential to regulatory compliance and long-term adoption.
Updating SLAs for Generative AI reality
Traditional service level agreements were never designed for systems that learn, adapt and sometimes behave unpredictably. Generative AI introduces challenges such as hallucinations, data drift and inconsistent outputs, all of which must be acknowledged contractually.
Partners should update SLAs to include AI-specific performance benchmarks, monitoring mechanisms, and escalation procedures. Risk disclaimers must clearly state that AI-generated content may not always be accurate or contextually appropriate. Regular model reviews and updates should also be built into agreements to ensure sustained performance over time. Just as important is educating customers setting realistic expectations is foundational to responsible deployment.
Building trust through transparency
Trust in AI begins with transparency. Partners reselling or customising third-party models should disclose the model’ s source, version, training scope and known limitations. Any modifications or fine-tuning must be documented and shared with clients.
Generative AI introduces challenges such as hallucinations, data drift and inconsistent outputs, all of which must be acknowledged contractually.
Labelling AI-generated content, enabling explainability tools and offering audit capabilities all contribute to greater accountability. Many organisations are also adopting ethical AI frameworks or
INTELLIGENT TECH CHANNELS 35