AI Strategy for Digital Business

High-level framework to define AI Strategy.



1.    Define Business Goals:

•       Identify Digital business overarching business objectives.

•       Understand key performance indicators (KPIs) and success metrics.

•       Determine how AI can contribute to achieving these goals.

2. Understand Client Needs:

•       Conduct client surveys, interviews, and feedback sessions via Mural boards.

•       Identify common pain points and challenges faced by clients.

•       Determine where AI can enhance client satisfaction and deliver value.

3. Assess Current Capabilities:

•       Evaluate existing AI capabilities within Apply Digital.

•       Identify areas where AI can be integrated or improved.

•       Assess the skillset of the current workforce in relation to AI.

4. Establish Clear AI Objectives:

•       Define specific, measurable, achievable, relevant, and time-bound (SMART) AI objectives.

•       Align AI goals with business and client objectives.

5. Develop a Roadmap:

•       Create a phased roadmap for AI implementation.

•       Prioritize AI initiatives based on impact and feasibility.

•       Establish milestones and timelines for each phase.

6. Identify Key AI Use Cases:

•       Select AI applications that align with Digital business core competencies.

•       Consider AI use cases that address client pain points.

•       Prioritize use cases that deliver tangible business value.

7. Build a Cross-Functional AI Team:

•       Assemble a multidisciplinary team with expertise in AI, data science, software development, and domain-specific knowledge.

•       Foster collaboration between technical and non-technical teams.

8. Invest in AI Infrastructure:

•       Ensure the availability of the necessary computing resources and infrastructure.

•       Consider cloud-based solutions for scalability and flexibility.

9. Implement Ethical AI Practices:

•       Develop and adhere to ethical guidelines for AI usage.

•       Ensure transparency and fairness in AI algorithms.

•       Establish protocols for handling sensitive data.

10. Continuous Learning and Improvement:

•       Implement mechanisms for continuous learning and adaptation.

•       Monitor AI performance and gather feedback for improvements.

•       Stay informed about advancements in AI technology.

•       Eg. Learn on new technologies like RAG (Retrieval Augmented Generation) which helps increasing accuracy & reliability of GenAI models with facts fetched from external sources.

11. Client Education and Engagement:

•       Educate clients about the benefits and limitations of AI.

•       Provide training and support to clients for AI-driven solutions.

•       Foster a collaborative approach to AI implementation.

12. Measure and Report:

•       Define key performance indicators (KPIs) to measure the success of AI initiatives.

•       Regularly assess and report on the impact of AI on business goals and client satisfaction.


Also see:  Role based AI for Ecommerce


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