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Gen AI curious to Gen AI ready : Path to successfully adopting Generative AI
Gen AI curious to Gen AI ready : Path to successfully adopting Generative AI

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Harvard Business Review Analytic Services and Boomi have shared a report titled "Unlocking Gen AI’s Potential by Strengthening Data and Organizational Readiness" that extensively covers all the factors that serves as an empirical guide for the enterprises that are looking to adopt Gen AI to its full potential. Out of those adopting Gen AI, better prepared organizations can easily prevail organizations that are not taking steps attending to foundational steps such as data quality, system integration, and organizational readiness etc.

The report highlights some of the guiding factors that will prove to be crucial in the journey of the adoption of Gen AI. 

1. It is imperative to establish an AI steering committee or AI COE or AI value office or community of practice. The committee should include cross functional team across HR, IT, Legal and Risk Management Professionals. Multiple Gen AI leaders may be required to span the wider scope of responsibilities. right conversations around strategy, architecture, governance, value frameworks, data readiness, and skill building across the enterprise.

2. To establish a Gen AI roadmap, it is recommended to prioritize both factors, Value verses feasibility. Gen AI use cases need to directly be aligned to support organizations strategic goals.

3. 5 Ways to assess Gen AI use cases.

  1. Assess the use case business validity and feasibility.
  2. Use case quantified business value.
  3. Data readiness
  4. Alignment with responsible AI
  5. Culture is ready to adopt the use case.
  6. Cost  
Two Types of GenAI use cases
  Efficiency Based   Growth Based  
  a) Automating Processes
b) Gathering Data
c) Streamlining Workforces
d) Performing tasks
  a) Idea Generation
b) Business Model Innovation
c) Higher Order Tasks
 
         

 

4. Some guiding principals to embrace Responsible AI is essential right at the start of Gen AI journey. To deploy AI applications, it is important to keep  in check the following.

  • Data privacy
  • Explainability and transparency
  • Safety and security
  • Fairness and bias detection
  • Reliability and Validity
  • Accountability.

 

5. The organizations should be transparent with the employees to address management overconfidence and employee’s trepidation about the technology. The management should be part of change management initiatives to to ensure adherence to policy, set expectations, alleviate mistrust, and engender a mindset shift.

6. Managing and curating institutional data and Data readiness review is recommended to ensure solid data foundation. It is important to measure the effectiveness for successful Gen AI adoption.

Following 5 Dimensions can be adopted for measuring Gen AI effectiveness.

a. Level of Data preparedness

b. Efficacy of models

c. Value being produced at use case level

d. Business value produced by Gen AI

E. Regulatory and compliance KPIs.

 

Source: Unlocking Gen AI’s Potential by Strengthening Data and Organizational Readiness


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Madhumay
Deputy Manager - Research

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