Prepilot

Your ‘no regrets’ pilot kicks off with a Design Thinking Ideation session. Driving the scope of the pilot shaped by the value and aims.

1-2months

Identify and appoint resourced based on competencies needed to meet OKRs. Launch and complete pilots, establish value proofs.

2-6months

Transition pilot use case to production, having established a dedicated performance evaluation and ethical monitoring capability.

6-12months

Scale value created by the GEN AI initiative by supporting additional use cases and optimising both its performance and ethical capabilities.

Organisational Design

Agile Team (Prototyping Use Case #1+)

Light customization 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

• Scrum Master

• Data Specialist/Scientist

Centre of Excellence: Infrastructure & Ops Provisioning

Provision the necessary processing power Meeting constantly evolving regulatory conditions – establishing good practice prior to scale-out (launch of additional pilots)

A third group is formed who are responsible for provided the necessary highly powerful (resource intensity) platform.

Centre of Excellence:  Data Integrity & Governance

Responsible for constantly evolving regulatory conditions – establishing good practice prior to scale-out (launch of additional pilots)

Responsible for ensuring trust, unbiased, fairness and alignment with constantly emerging regulatory guidance.

• Ensuring rust and transparency is built-in right from the start.

• An iterative approach enables the models to reflect the constantly changing 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 guidelines on appropriate tools and practices for that must be applied through the GEN AI life cycle.

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

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

Discovery to Value Creation

Creativity Potential

Unlock creative potential

• 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 

• extensive customer validation

Validation Efficiencies

Rapidly validate new ideas and concepts

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

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

• capture valuable customer intelligence 

• Find suitable solutions for some of the more pressing ethical consideration.

• Maintaining governance controls and limiting financial risk

Continuous and Incremental Value Creation

Shorter and more frequent delivery cycle

• Accelerate the speed the organisation creates value from their Gen AI investment

• Effective prioritization of requirements 

• Quickly securing market share generates income earlier 

• bring about greater operational and commercial efficiencies to the organisation earlier than traditional plan-based ways of working 

Critical Success Factors

Product Backlog (baseline)

• Foundation and LLM Selection

• 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

• Creativity Potential