Gen AI is still in the early maturity stage and its application in corporate environment comes with number of challenges. It will take some time before all regulations are in place and the industry standards and best practices are established.
However, not acting is not an option due to potential competitive disadvantages of not using the benefits of gen AI in the long run. With that, organizations must evolve and act now to understand its benefits, as well as potential risks and ways of dealing with them. New policies, practices, frameworks and data quality improvement programs need to be implemented while user experience and building trust should remain in focus.
Firstly, organizations need to develop quality evaluation and risk mitigation strategies towards gen AI. The organizations should define up front what quality measures and ranges will be acceptable to mitigate the level of risks they defined for their use cases.
With that, an up-front categorization of gen AI-based system risks and risk tolerance level identification is and frameworks required:
- Risk tolerance will be defined by stakeholder’s readiness or appetite to bear the risk to achieve its objectives.
- Legal and regulatory requirements should be considered and IT teams need to be involved as well.
- A gen AI-based multilayered model of gen AI should be considered in which each of the levels impact the overall solution quality and security in its own way.
- Gen AI model level quality risks mitigation options can be selected in a combined risk mitigation approach.
- Gen AI infrastructure and information security governance need to be established.
- Business process quality and security assurance need to be ensured.
- Gen AI-specific quality assurance capabilities need to be developed.
Gen-AI-saftey “per design”
This approach of Safe Gen-AI nicely complements our 4 Gen-AI Service Packages that include Gen-AI safety “per design”.
