Prepilot

Your ‘no regrets’ pilot kicks off with an ideation Design Thinking session. Discovering the scope of the pilot that is shaped by the value and aims.

1-2months

Identify and appoint resources based on the competencies needed to meet the Pilot OKRs. Establish proof of concepts and validate competencies.

2-6months

Transition pilot use case to production, as the team embarks on a robust performance evaluation and ethical monitoring strategy.

6-12months

Scale value created by the GEN AI initiative through the implementation of additional use cases and optimising both its ethical capabilities.

Organisational Design

GEN AI Pilot Team (Prototyping Use Case #1)

Light customisation of the Client’s own data. Focus on a specific low-risk Use Case . Update the pre-trained models as part of an iterative process.

Team consisting (minimum): Product Owner, Data Specialist/Scientist, Automation SME, Governance SME and a Hardware Specialist

Centre of Excellence: Infrastructure & Ops Provisioning

Ensuring the provisioned infrastructure is capable of meeting the high demand of the use cases and the COE establishing good practices prior to scale-out. Including, where needed cloud infrastructure to meet variable processing demand.

Centre of Excellence:  Data Integrity & Governance

Dedicated COE that is responsible for constantly evolving the organisations regulatory defintion in response to the performance of the pilot.

Ensuring trust, unbiased, fairness, explainability of the GEN AI solution.

An iterative approach enables the models to reflect the constantly changing technology landscape and ensuring strong data rules.

Ethics committee

Form a committee that holds responsibility for ensuring organisational and regional GEN AI mandates are applied. Achieved through establishing three core practices:

Methodology - Publish tools and practices for that must be adhered through the GEN AI life cycle.

Adoption - Over see the introduce of these methodologies across the organisation.

Governance - Continually evaluate how the core practices are being adopted and provide guidance where improvements are required.

Discovery to Value Creation

Creativity Potential

Discover the true potential of GEN AI

• rapidly verify new concepts and assumptions in a controlled manner. 

• Identify and exploit previously unforeseen potential of Gen AI technology

• focused and rapid research cycles strengthen a business case 

• shaping a clear implementation path towards a healthy return on investment 

• validate the suitability of its current competencies, processes, and tools prior to scale-out

Validation Efficiencies

Rapidly validate new ideas and concepts

• quickly validate both technical and commercial capabilities for Gen AI implementation and

• Ensure suitable solutions are found to ethical factors and challenges as part of

• Constantly capture and analysis customer feedback across data, automation, usability and ethical factors

• Ensure the team employs a tight governance and financial management

Continuous and Incremental Value Creation

Lean development life cycle

• A clear and prioritisation mechanism

• Accelerate GEN AI return on investment

• Quickly securing market share generates income earlier 

• Constantly adapt the ways of working to meet the capabilities of:

  • GEN AI technology

  • internal capabilities

  • external landscape as appropriate

Critical Success Factors

Product Backlog (baseline)

• Foundation and LLM selection

• Establish Ethics & Governance Committees

• Pilot Objectives. & Key Results

• Stakeholder Management

• DevSecOps Strategy

• Communication Plan

• Colocation Space (Teams & Squads) Provisioning

Value Creation Life Cycle

• Early Value Realisation & Technology Suitability

• Validation Efficiencies

• Continuous Investment in a Lean delivery cycles

• Team capability & engagement

• Suitable & accurate KPIs

• Creativity potential & risk tolerance

GEN AI Commercial Readiness for Product Management

The MONETICAL GEN AI Commercial Readiness Assessment covers the following core characteristics of the initiative: AI ethics & regulation, AI initiative OKR & KPI, AI Stakeholders, AI post deployment and AI use cases.

GEN AI Technology Readiness for Product Management

The MONETICAL GEN AI Technology Readiness Assessment covers the following core characteristics of the initiative: foundation & LLM, ethical capabilities and data governance, privacy and security factors, human oversight and technical capabilities.