Phase	Task	Objectives	Actions	Deliverables
1. Requirement Analysis & Planning	1.1 Define Project Specifications Document	Clearly outline the scope, goals, and requirements for AI implementation in recruitment.	Identify Key Stakeholders	Project Specifications Document
			Document automation opportunities.	
			Establish clear objectives and success metrics.	
	1.2 Architecture Document	 Design the technical architecture for AI integration.	Gather feedback from stakeholders (e.g., ADE, HR).	Comprehensive Architecture Document
			Outline system architecture including data flow.	
			Define data governance and ethical AI guidelines.	
	1.3 Develop Automation Roadmap	Create a strategic plan for phased AI implementation.	Prioritize tasks based on impact and feasibility.	Automation Roadmap
			Create a detailed timeline with milestones.	
			Assign resources to each task.	
	1.4 Communication Plan	Establish a structured communication strategy to keep all stakeholders informed and engaged throughout the project lifecycle.	Create a strategy to keep all stakeholders informed throughout the project lifecycle.	A documented strategy detailing how information will be shared with stakeholders, including frequency, channels, and content formats.
	1.5 Risk Management	Identify potential risks to the project and develop strategies to mitigate them, ensuring project resilience.	Develop a risk management plan to identify potential risks and mitigation strategies.	A dynamic log tracking identified risks, their status, and mitigation actions.
2. Infrastructure Setup	2.1 Infrastructure Planning	Determine and procure the necessary hardware and software for AI deployment.	Assess current infrastructure and identify gaps.	Infrastructure Plan
			Provision hardware/software resources for deployment.	
			Ensure compliance with data protection regulations.	
	2.2 System Configuration	Set up the technical environment for development and testing.	Configure servers and databases for optimal performance.	Configured Systems Ready for Development and Testing
			Set up development and testing environments.	
			Document all configuration settings.	
3. LM Evaluation & RAG Pipeline	3.1 AI Model Evaluation	Assess the suitability of various AI models for recruitment tasks.	Establish key performance indicators (KPIs) for evaluation.	AI Model Evaluation Report
			Conduct a detailed cost-benefit analysis.	
			Develop metrics for ongoing impact tracking.	
	3.2 LM Performance Evaluation	Specifically evaluate Language Models for tasks like job matching and communication.	Assess LMs for accuracy and efficiency.	LM Evaluation Report
			Conduct user testing to gather qualitative feedback.	
			Document findings and recommendations for improvements.	
4. High-Priority Automation	4.1 Automate Job Matching	Implement AI-driven job matching to enhance candidate-job fit.	Implement RAG pipeline for job matching.	Automated Job Matching System with UI
			Develop user interface with search filters.	
			Ensure system adaptability to various job roles and industries.	
	4.2 Automate Candidate Sourcing	Streamline the sourcing of candidates from various platforms.	Create systems for automated candidate sourcing.	Automated Candidate Sourcing Tool
			Implement algorithms to prioritize candidates.	
			Ensure compliance with data privacy regulations.	
5. Medium-Priority Automation	5.1 AI for Candidate Communication	Enhance communication with candidates through automation.	Automate initial outreach and follow-ups.	Automated Communication System
			Develop customizable communication templates.	
			Incorporate personalization features based on candidate profiles.	
	5.2 Offer Discussion & Confirmation	 Facilitate AI-assisted offer management and onboarding communications.	Facilitate AI-assisted offer discussions.	AI-Assisted Offer Management and Onboarding System
			Create a dashboard for tracking discussions.	
			Integrate feedback mechanisms for continuous improvement.	
6. System Integration & Testing	6.1 System Integration	Ensure AI modules work seamlessly with existing recruitment tools.	Integrate AI models with existing recruitment tools.	 Fully Integrated Recruitment System
			Develop necessary APIs or middleware.	
			Conduct security assessments post-integration.	
	6.2 Pilot Testing	Validate the system with real-world scenarios before full deployment.	Identify a group of users for pilot testing.	Validate the system with real-world scenarios before full deployment.
			Collect and analyze user feedback for adjustments.	
			Document pilot results for review.	
	6.3 Final Testing & User Acceptance	Ensure the system meets all requirements and is ready for full-scale deployment.	Execute comprehensive testing (performance, usability).	Final Testing Report and User Acceptance Sign-Off
			Conduct training sessions for end users.	
			Obtain formal user acceptance through sign-off process.	
7. Deployment & Monitoring	7.1 System Deployment	Launch the AI-driven recruitment system into the live environment.	Deploy AI modules in live environments.	Deployed Recruitment Automation System
			Conduct user training sessions; provide documentation.	
			Develop a rollback plan for deployment issues.	
	7.2 Post-Deployment Monitoring	Ensure the system operates optimally and continues to meet objectives.	Continuously monitor AI performance and usage data.	Ongoing Monitoring Reports and Optimization Plans
			Establish a feedback loop for optimization.	
			Schedule regular reviews with stakeholders to assess impact and make adjustments.	
	7.3 Documentation	Maintain thorough documentation and facilitate knowledge transfer.	Ensure comprehensive documentation at each phase for knowledge transfer and compliance.	Complete Documentation Set
	7.4 Change Management	Ensure smooth adoption of the new AI system within the organization.	Implement a change management process to handle modifications in scope or objectives effectively.	Change Management Plan

This is a high level plan for automating the recruitment process using Generative AI. Can you please help me in enhancing the quality of the plan and come up with a tabular report of it.