Efficiently Develop the Organisation's First AI Agent

Months 1 - 3 (Pilot)

Our AI Agent Pilot program templates, provides easy to follow advice, ensuring your first AI Agent Pilot is a success. Spanning 8weeks the AI Agent Pilot program ensures critical success factors such as AI ethics, large language models, Agent frameworks, human-in-the-loop processes, and the underlying data management factors are all considered, ensuring the AI Agent is in service of a strategic goal and not technology pandering.

MONETICAL is constantly expanding the breadth & depth of the consulting advice contained in its Initiative program and will create new ones as advances are made in all the key areas of Generative AI. In particular, providing advice on how teams can create ever-more powerful solutions as AI tools become more sophisticated & their reasoning capabilities accelerate, creating an opportunity for these AI Agents to solve increasingly more complex problems. Starting with the aims of combining several AI Agents, each with a speciality, MONETICAL will continue to provide expert advice as our Clients seek to create solutions for more complex & specific business use cases.

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 definition in response to the performance of the pilot.

Ensuring trust, unbiased, fairness, explainability of the Generative 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.

Methodology - Publish tools and practices for that must be adhered through the Generative 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 Generative AI

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

• Identify and exploit previously unforeseen potential of Generative 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 Generative 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

Critical Success Factors

Product Backlog (baseline)

• Foundation and LLM selection

• Establish Ethics & Governance Committees

• Pilot Objectives. & Key Results

• Stakeholder Management & Comms Plan

• DevSecOps Strategy

• 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

Verification to Value

Months 3 - 6 (Operationalise)

Transition Pilot AI Agent into production.

Dedicated and detailed consulting advice ensures the cross-discipline team engages effectively with additional organisation functions (e.g. support, ethics and operations) to ensure effective validation, monitoring and governance structure are operational.

• Ensure correct tool selection for production (e.g. user interfaces, evaluation frameworks, & continuous improvement mechanisms) 

• Ethic verification (adhering to industry & country AI regulations)

• Dashboard enabling human supervisors to monitor AI system outputs and intervene as needed.

• System-level features handle AI model failures gracefully with redundancy and failover options.

• Active AI-specific cybersecurity systems

Continuous and Incremental Value Creation

Months 6 onwards (Scale-out)

Building on the success of the AI Agent Pilot and operationalise success, consulting advice is provided in the form of a dedicated Initiative Program.

Step-by-step advice on how to operationalise (extensions, functions, & data stores) where access to external systems is required using APIs, and scale-out additional AI Agent in a effective and ethical manner following tailored governance frameworks.

Adopting Lean development methodology to constantly adapt to meet the capabilities of constantly:

• developing Generative AI technology

• expanding internal Generative AI capabilities

• evolving operational and commercial landscape

Back-up by:

• a data-driven clear prioritisation mechanism

• an ability to accelerate return on investment

• an efficient customer feedback loop

• robust data showing ethical adherence