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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”.



To understand our approach towards safe gen AI, Risk-based quality assurance of generative AI and more, see our whitepaper our Gen AI webpage or contact the authors Ulrich.Faisst@cognizant.com and Almir.Mardanov@cognizant.com.


Dr. Urlich Faisst

CTO Central Europe, Cognizant

Simon Formanowski

Dr. Ulrich Faisst is Chief Technology Officer (CTO) for the Central Europe region at Cognizant. There, he is responsible for the growth strategy while strengthening the company's customer:centricity and technology leadership in the region. Ulrich's expertise includes transformational strategy and execution, automation and AI, IoT, cloud, digital engineering, SAP and Salesforce.


Dr. Almir Mardanov

Lead Enterprise Architect, Central Europe, Cognizant

Author Image

Dr. Almir Mardanov is Lead Enterprise Architect for the Central Europe region at Cognizant. There he is responsible for solutioning large deals and supporting customers in transformation and innovation journeys. Almir’s expertise includes digital transformations, managed services, COEs, automation and AI, customer experience and Microsoft Technology Stack.


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