AI Navigator Framework

 

This framework is designed to identify opportunities for AI integration within your company’s strategy, cutting your time investment by 50% and reducing process performance costs by 20%. Please select the phase that best aligns with the current stage of your company’s integration process, and contact me for more details.

With Arek, we have discovered innovations that wouldn’t have been possible otherwise. The Proof of Concept method is a powerful tool that helped teams in Discovery connect with innovation, something that would have remained untapped.

Jamie Cooke

Chief Operational Officer, Discovery Networks

Stage 1
L
Stage 1

Analysis and Diagnosis

1. Organizational Structure Review and Function Selection

    • Review organizational documentation and prepare selection criteria.
    • Conduct workshops with management and directors (3 meetings).
    • Prepare and present results.
    • Deliverables: Organizational structure analysis report, criteria for selecting functions for transformation, documentation of the selection of two key business functions.

2. Employee Interviews

    • Prepare an interview questionnaire.
    • Conduct individual interviews (15 employees).
    • Organize and moderate group workshops (2 workshops).
    • Analyze and document the results.
    • Deliverables: Interview questionnaire, interview transcripts, group workshop documentation, report with conclusions from interviews and workshops.

3. Analysis of Existing IT Systems

    • Inventory IT systems.
    • Analyze technical documentation.
    • Hold meetings with the IT team.
    • Assess infrastructure and data security.
    • Deliverables: IT system inventory with potential for AI integration, IT infrastructure report, data security assessment, and potential risks.

4. Data and Production Process Audit

    • Identify data sources.
    • Assess data quality and availability.
    • Analyze production processes.
    • Deliverables: Data source map, data quality assessment report, documentation of analyzed production processes, comprehensive audit report.
Stage 2
L
Stage 2

AI Potential Identification

1. Mapping Processes for AI

    • Analyze identified processes.
    • Assess automation potential.
    • Conduct workshops.
    • Prepare initial AI solution concepts.
    • Deliverables: Process assessment matrix for AI potential, workshop documentation, catalog of initial AI solution concepts.

2. Consultations with IT and Security Departments

    • Prepare consultation materials.
    • Conduct meetings with IT and security teams.
    • Analyze technical and security requirements.
    • Deliverables: Documentation of technical requirements, report from consultations with IT and security departments, list of identified technical limitations and possibilities.
Stage 3
L
Stage 3

Cost-Benefit Analysis

1. AI Project Valuation

    • Collect cost data.
    • Estimate implementation costs for projects.
    • Calculate operating costs.
    • Deliverables: Detailed cost estimate for each potential AI project, a summary of implementation and maintenance costs, cost analysis document.

2. Potential Savings Calculation

    • Define metrics for assessing savings.
    • Analyze historical data.
    • Perform calculations for projects.
    • Deliverables: Methodology for assessing savings, a report analyzing potential savings for each project, a summary of projected financial, and operational benefits.

3. ROI Analysis for Each Project

    • Develop an ROI assessment methodology.
    • Calculate ROI for projects.
    • Conduct sensitivity and risk analysis.
    • Deliverables: ROI assessment methodology tailored, ROI report for each potential project, sensitivity analysis with identification of risk factors, and a report summarizing the cost-benefit analysis.
Stage 4
L
Stage 4

Prioritization and Implementation Plan

1. AI Project Prioritization

    • Develop prioritization criteria.
    • Evaluate projects according to the criteria.
    • Conduct workshops with management.
    • Deliverables: Document with prioritization criteria, project evaluation matrix, ranked list of AI projects.

2. Implementation Strategy Preparation

    • Develop an implementation methodology.
    • Plan the project schedule.
    • Identify resources and dependencies.
    • Develop a risk management plan.
    • Deliverables: AI implementation strategy document, project implementation schedule, resource and dependency plan, risk management plan.

3. Final Report Development

    • Collect and organize the results.
    • Edit the analytical and strategic sections.
    • Prepare visualizations.
    • Deliverables: Comprehensive final report with analysis and transformation strategy, visualizations of key results and recommendations, technical appendices, and supporting documentation.

4. Presentation to the Management Board

    • Prepare the presentation.
    • Conduct the presentation and discussion.
    • Deliverables: Presentation for the Management Board, minutes of the discussion and decisions of the Management Board, document summarizing the approved courses of action.
Stage 5
L
Stage 5

Implementation Planning

1. Development of an Implementation Plan for Selected Projects

    • Detailed project planning.
    • Develop a change management plan.
    • Plan resources, budget, communication, and training.
    • Deliverables: Detailed implementation plans for selected projects, organizational change management plan, resource and budget allocation plan, employee communication and training plan, complete implementation documentation.
Stage 6
L
Stage 6

Piloting, AI Model Selection, and Prompt Engineering

1. Piloting Selected AI Solutions

    • Set up pilot environments for chosen AI solutions.
    • Monitor pilot performance and gather user feedback.
    • Identify and address any issues or bugs.

2. AI Model Selection

    • Evaluate different AI models based on pilot results, accuracy, speed, and cost.
    • Choose the most suitable AI model(s) for each application.
    • Document the model selection process and rationale.

3. Prompt Engineering

    • Develop and refine prompts to elicit the desired responses from AI models.
    • Test prompts with diverse inputs and scenarios.
    • Create a library of optimized prompts for various use cases.
    • Deliverables: Pilot project reports with performance metrics and user feedback, Documentation of selected AI models, including justification and model specifications, A prompt library with optimized prompts for different AI applications.
Stage 7
L
Stage 7

Implementation and Scaling

1. Implementation and Integration

    • Integrate AI solutions with existing IT systems and workflows.
    • Deploy AI solutions to target users and departments.
    • Provide user training and support.

2. Monitoring and Optimization

    • Continuously monitor AI solution performance and identify areas for improvement.
    • Optimize AI models and prompts based on real-world data and user feedback.
    • Ensure data quality and security.

3. Scaling and Expansion

    • Expand the use of AI solutions to new areas of the business.
    • Develop new AI applications to address emerging business needs.
    • Establish a center of excellence for AI to drive innovation and adoption.
    • Deliverables: Deployment plans and documentation for AI solutions, Performance dashboards and monitoring reports for AI applications, A roadmap for scaling and expanding AI adoption across the organization.