In preparation for the initial meetings, we start by reviewing key documentation.
We will also try to define the Key Stakeholders and the Delivery Team. Key Stakeholders typically include leaders from Tech, AI and Data, Operations, Compliance, HR and any other relevant function (e.g. Transformation, Strategy, etc, if they exist). Members of the Delivery Team are typically ambitious, motivated and open team members from the following functions; engineering, data science or analytics, operations and sales or marketing.
We will also distribute a brief questionnaire for stakeholders to complete before the meeting. This can help identify priorities, concerns, and current AI maturity levels across different departments. It will also enable us to propose a clear framework for assessing the company’s AI readiness and to ensure alignment between stakeholders’ perceptions, potential and reality.
Client documentation requested (if available):
Decisions needed:
The first meeting will be a kickoff session and the main agenda points are:
In this meeting, we will debate the primary objectives of the engagement, which will direct our ongoing R&D and advice. We will also establish the best communication channels.
Attendees:
Decisions needed:
This will be an in-depth workshop to understand your highest priority business functions and processes, as well as your current data, AI and technology capabilities, challenges, and goals. We aim to identify areas of opportunity and lay the groundwork for the AI strategy we will develop together.
We will also consider external benchmarking and change processes in subsequent workshops.
Attendees:
Decisions needed:
We will assess your existing infrastructure, architecture, data assets and tools to understand where improvements or enhancements are needed. This will include reviewing data accessibility, data quality, storage, and integration points with current systems.
Client documentation requested (if available):
Based on the discovery and data review, we will craft a tailored AI and data strategy. This will include both short-term and long-term objectives, aligned with your business strategy and the available resources.
We’ll also create a detailed AI and data roadmap, which will consider your business objectives, internal and external resource allocation, and budgets.
Initially, we’ll produce a long list of potential projects to be considered for prioritisation, then distil that list to a short list based on suitability for automation, expected business impact, expected development effort and blast radius. The roadmap will ensure a phased approach for measurable results and will also cater for architectural projects needed to facilitate the AI and data projects.
We will also produce a capability gap analysis, a change management strategy including cultural (reward based on improving AI), training requirements, ethical AI issues and how to monitor them, and plans for AI maintenance and sustainability.
Client documentation requested (if available):
Decisions needed:
We will work with the Key Stakeholders and Delivery Team to agree on delivery-focused roles and responsibilities, ensuring everyone understands the strategy and their part in its execution.
Client documentation requested (if available):
We will support and oversee the design and implementation of any architectural changes required to facilitate the AI and data projects.
Client involvement:
We will work with the available resources, whether internal or external, to scope, design and build small-scale pilot project(s), or Proof-of-Concept(s) (PoCs), that can build confidence, capability and help refine the overall AI strategy. These PoCs will be designed to demonstrate the value of AI solutions while minimising risks.
Decisions needed:
We will regularly review the progress of AI initiatives, address any challenges, and make necessary adjustments. This ensures the projects stay on track and deliver the intended outcomes.
Client documentation requested (if available):
We’ll provide regular reports on project status, key metrics, outcomes, and any insights gained. These reports will help guide decision-making and ensure transparency throughout the engagement.
As business objectives evolve, so too will the AI and data strategy. By continuously reviewing the performance of previous projects, we’ll identify key insights that inform adjustments to the overall approach. This ensures the strategy remains aligned with shifting priorities and emerging opportunities. Regular performance reviews and feedback loops will allow us to adapt both the roadmap and individual initiatives, ensuring continued relevance and value across all efforts.
This documentation details the process for engaging a Fractional AI Officer, outlining a four-phase approach: Kickoff, Strategy Development, Execution, and Strategy Evolution. It covers the necessary preparations, meetings, documentation, and deliverables for each phase, aiming to help organizations define and implement their AI strategy effectively.
The Fractional AI Officer process involves four main phases: Kickoff process, Strategy development, Execution phase, and Strategy evolution.
Client documentation requested includes: Stakeholder questionnaire, High-level business objectives and annual business plan, Company vision and values, Organisational structure chart, list of stakeholders and resource allocation, Current communication tools being used, Technology architecture diagrams, Existing AI and data initiatives or projects, Relevant assurance, consultancy reports or technology audits, and Current data governance policies.
The main agenda points for the kickoff meeting are: To introduce the Fifty One Degrees team to key stakeholders within your organisation and inform them on current AI trends and opportunities, Review any perceived risks identified from AI adoption within the business, and Identify broad opportunities for automation, and potential benefits (e.g. improved customer experience, operational efficiency, reduce risks).
During the Data & infrastructure review, we will assess your existing infrastructure, architecture, data assets and tools to understand where improvements or enhancements are needed. This will include reviewing data accessibility, data quality, storage, and integration points with current systems.
Strategy & roadmap development involves crafting a tailored AI and data strategy with short-term and long-term objectives, aligned with business strategy and resources. It also includes creating a detailed AI and data roadmap, a capability gap analysis, a change management strategy, and plans for AI maintenance and sustainability.