Generative AI Adoption Framework Slides

STRUCTURE FRAMEWORK

STRUCTURE FRAMEWORK

GENAI MATURITY PHASES

GENAI MATURITY PHASES

GENAI MATURITY PHASES OUTCOME

GENAI MATURITY PHASES OUTCOME

EVALUATE RISK OPPORTUNITIES

EVALUATE RISK OPPORTUNITIES

EVALUATE ERROR

EVALUATE ERROR

GENAI THREATS

GENAI THREATS

CHALLENGES OF GENAI

CHALLENGES OF GENAI

UNCONTROLLED BEHAVIOR

UNCONTROLLED BEHAVIOR

GENAI SCENARIOS FOR ADOPTION

GENAI SCENARIOS FOR ADOPTION

BEST PRACTICES FOR ADOPTION

BEST PRACTICES FOR ADOPTION

Additional Comments



Adoption Framework for GenAI in Enterprises


  • Adoption framwork help companies determine areas where generative AI adoption can happen quickly. Areas that are less mission crticial and where out of box generative AI works well with low error rate are good candidate to onboard generative AI.

  • Framework need to be structured. It shuold provide stages, best practices and how to evaluate risks and opportunties.

  • Slides describe 5 stages of gnerative AI adoption phases.

  • It describe areas where out of box model can be used without issues. It describe areas where out of box model will not work and there is opportunity to innovate

  • Slide also describe how to extend AI risk and consider all ris for generative AI

  • finally slide describe use caes that can be adopted with ease

  • Mission critical areas where out of box model does not work - should be adopted at last stage. Companies should evaluate whether training on domain specific data will help. If building such model produce good result, it will provide competitive advantage

  • Factors to Consider for Generative AI Adoption
    • Data Availability: Assess the availability and quality of data required for training the generative AI model.
    • Computational Resources: Evaluate the computational resources needed to train and deploy the generative AI model.
    • Expertise and Skills: Determine the level of expertise and skills required to develop and maintain the generative AI model.
    • Ethical Considerations: Consider the ethical implications and potential biases associated with the generative AI model's outputs.
    • Legal and Regulatory Compliance: Ensure compliance with relevant laws and regulations when using generative AI.
    • Business Objectives: Align the adoption of generative AI with the organization's strategic goals and objectives.
    • Costs and Return on Investment: Evaluate the costs associated with implementing and maintaining generative AI, and assess the potential return on investment.
    • Security and Privacy: Address security and privacy concerns related to the data used and generated by the generative AI model.
    • User Acceptance: Consider the acceptance and usability of generative AI outputs by end-users or customers.

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    Adoption-framework-stages    Best Practices for Adoption    Challenges-of-genai    Evaluate-error    Evaluate-risk-opportunities    Genai-maturity-phases-outcome    Genai-maturity-phases    Genai-scenarios-for-adoption    Genai-threats    New 1   

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