Framework to maximize the potential of Gen AI

To implement a framework that maximizes the potential of Gen AI in corporate strategy, particularly in areas like finance, procurement, HR, customer service, and Global Business Services (GBS), a roadmap similar to below can be followed:

1. Vision & Strategy Alignment

• Define Strategic Objectives - outline the objectives Gen AI is meant to achieve in different departments (finance, HR, etc.), while aligning these goals with the broader corporate strategy.
• Assess Current Capabilities: Evaluate current tools, systems, and digital infrastructure, identifying gaps that Gen AI can address.
• Stakeholder Buy-in: Involve top leadership, department heads, and other key stakeholders to ensure alignment with the organizational vision and budgetary support.

2. Data Governance Framework

• Data Discovery and Inventory: Create a comprehensive data inventory for the organization, ensuring that the most relevant datasets for Gen AI use cases (financial records, customer interactions, HR records, procurement data) are easily accessible and of good quality.
• Data Quality Management: Establish data quality standards. Implement processes for cleaning, enriching, and preparing data to ensure it is fit for Gen AI models.
• Data Governance Policies: Define clear data ownership, usage, privacy, and security policies, adhering to relevant legal and regulatory requirements (e.g. GDPR, HIPAA, etc.). Include protocols for sharing and updating data across departments.

3. Digital Skills & Talent Development

• Training Programs: Develop training and certification programs for employees at different levels, particularly those in GBS, finance, HR, procurement, and customer service, focusing on AI literacy, data science, and AI-driven decision-making.
• Hiring Talent: Recruit data scientists, AI specialists, and change managers to build internal capabilities. Also think about leadership – CIO to CAO (Chief AI Officer).
• Upskilling Existing Teams: Leverage tools and platforms that allow non-technical staff to engage with AI and automation workflows through no-code or low-code solutions.

4. Gen AI Tools & Platform Integration

• Tool Selection: Evaluate and select Gen AI platforms that integrate with existing enterprise systems. Look for serverless model platforms that offer AI-as-a-service models, such as Google Cloud AI, Microsoft Azure AI, or custom LLM-based solutions.
• Platform Integration: Integrate Gen AI tools into existing enterprise resource planning (ERP), customer relationship management (CRM), and other business systems. Ensure the platform can scale across different departments.
• API and Cloud Enablement: Set up APIs for seamless data exchange and processing between your existing tools and the new Gen AI models. Cloud platforms like AWS or Azure will facilitate scalability and agility.

5. Use Case Development & Piloting

• Prioritize Use Cases: Start by identifying and prioritizing high-impact use cases across departments. For example ... Finance: Predictive analytics for financial forecasting and fraud detection. Procurement: Dynamic supplier evaluation, cost optimization, and risk management. HR: AI-driven recruitment, workforce planning, and personalized employee experiences. Customer Service: Automating customer queries, enhancing personalization, and sentiment analysis. GBS: AI-driven insights to optimize shared services and streamline processes.
• Pilot Programs: Run pilot projects for each use case with controlled datasets to test the effectiveness of the AI models and assess ROI.

6. Data-Driven Decision Making

• AI Model Monitoring: Establish a system for continuously monitoring the AI model’s output, ensuring that the decisions align with business strategy and deliver desired outcomes.
• AI-Assisted Dashboards: Implement AI-powered dashboards to visualize real-time data insights. These should be accessible to decision-makers across the organization, empowering them with actionable insights.

7. Change Management & Scaling

• Change Management Strategy: Deploy a strong change management program. Educate teams on the benefits of Gen AI and its application across different functions. Regular communication and training workshops can ease adoption.
• Cross-functional Collaboration: Facilitate ongoing collaboration between departments (IT, finance, HR, procurement, etc.) to integrate AI insights into decision-making processes.
• Scaling AI: Once initial use cases show success, scale the AI models across other business units, customizing the models as needed to suit different functions or regions.

8. Continuous Improvement & Governance

• Feedback Loops: Implement continuous feedback loops to gather input from end-users and adapt AI models based on evolving needs.
• Performance Audits: Regularly audit the performance of AI models to ensure they are accurate, unbiased, and aligned with business goals.
• Governance and Ethics: Set up an AI ethics committee to ensure the responsible use of Gen AI technologies, focusing on transparency, fairness, and accountability.

By following this roadmap, you can establish a framework that leverages Gen AI to turn data into actionable insights, enabling improved decision-making, operational efficiency, and value creation across your organization.

Mahesh Mirchandani

October 2024

https://www.dhirubhai.net/in/maheshmirchandani