Phase 2: Strategy

Turning Audit Findings into a Transformation Plan

The Strategy phase translates the honest picture from the Audit into a concrete, actionable transformation roadmap. Every engagement is different, but the strategic framework is consistent: design the target state first, then determine the path to get there.

This phase typically runs 4–8 weeks, depending on organizational complexity.

Target Operating Model Design

Most transformation efforts fail because they try to automate the current state rather than design a better future state first.

We begin by designing your Target Operating Model — how your organization should function when AI is embedded as a core operational capability. This involves:

• Redesigning key workflows end-to-end, not patching individual steps
• Defining new role structures as AI handles repetitive cognitive tasks
• Identifying which decisions should be AI-assisted, AI-augmented, or AI-automated
• Mapping the data flows required to support the new model

Technology Architecture Blueprint

The Architecture Blueprint specifies the AI systems required to achieve the target operating model. This is not a vendor evaluation — it is a capability map.

We document which AI capabilities are needed (classification, generation, prediction, extraction), what data is required to power them, and how they integrate with existing systems.

Change Management Planning

Technology is 20% of transformation. The other 80% is change management.

Our Change Management Plan addresses: how you will communicate the transformation to staff, how you will identify and develop AI Champions across the organization, how you will handle resistance, and what support structures need to be in place before deployment begins.

Investment Model

The Investment Model shows the expected return on the transformation investment, modeled as a range (conservative to optimistic). We include implementation costs, productivity gains, risk-adjusted timelines, and break-even analysis.

We do not promise outcomes we cannot support with data. Every projection is documented with its assumptions.

Deliverables

Transformation Roadmap. A phased, 12–36 month plan for AI integration across the organization. Prioritized waves, dependencies, and success milestones.

Target Operating Model. The future-state design of your key operational workflows, role definitions, and decision-making structures.

AI Architecture Blueprint. The technical specification for AI capabilities needed, data requirements, and integration points.

Change Management Plan. Stakeholder communication strategy, training approach, AI Champions program, and resistance management playbook.

Investment Model. ROI projections, cost modeling, and break-even analysis for the full transformation program.

What Makes a Remolda Roadmap Different

Most AI roadmaps are filed within six months. They fail because they were built on aspiration rather than assessment, they ignored change management, they modeled unrealistic timelines, and nobody was accountable for execution.

Our Strategy phase produces a roadmap that is built to be executed — grounded in Audit findings, calibrated to your actual organizational capacity, and designed with change management integrated at every phase rather than bolted on as an afterthought.

The Investment Model

Every initiative in the roadmap is modeled for cost and return. Implementation costs, integration costs, training costs, and ongoing operational costs on one side. Time savings, error reduction, capacity recovery, and revenue impact on the other. The cumulative model shows when the program breaks even and what the 3-year return looks like.

This is the document your CFO, board, or Treasury Board analyst needs to approve the investment.

Governance Design

AI transformation requires governance — but the wrong governance model creates bureaucracy that kills momentum. We design governance frameworks that are proportionate to risk: lightweight approval for low-risk tools, rigorous assessment for high-impact AI systems, and clear escalation paths for issues that arise during implementation.

What Comes Next

The Strategy phase produces the blueprint. Phase 3: Implement turns the blueprint into deployed AI capability — in focused waves that deliver measurable results within each wave while building toward the broader transformation vision.

What Happens During This Phase

Weeks 1–2: Target Operating Model Design. We facilitate working sessions with your operational leadership to design the future-state operating model — how key workflows should be redesigned around AI capability, how roles should evolve, and where the boundaries between AI-automated, AI-assisted, and fully human work should fall. This is design work, not documentation work: we are building the target you will implement toward, not describing the current state.

Weeks 2–4: Architecture Blueprint and Technology Assessment. Based on the target operating model, we specify the AI capabilities required: what types of AI (classification, generation, extraction, prediction), what data each capability requires, how each capability integrates with existing systems, and what the build-versus-buy decision is for each component. Where vendor selection is required, we produce a vendor shortlist with evaluation criteria. For government clients, this includes matching capabilities to approved procurement vehicles.

Weeks 3–5: Change Management Plan and Investment Model. We develop the change management plan — stakeholder communication strategy, training approach, AI Champions programme design, and resistance management playbook. Concurrently, we build the Investment Model: implementation costs by wave, productivity gains modeled from comparable deployments, risk-adjusted timelines, and break-even analysis. Both are developed in parallel because the change management approach affects the timeline assumptions in the Investment Model.

Weeks 5–6: Roadmap Development and Governance Design. We sequence the AI capabilities from the architecture blueprint into implementation waves, balancing quick wins (to build organizational momentum) against foundational dependencies (data infrastructure that must precede higher-value AI applications). We design the governance framework proportionate to the risk profile of the planned deployments.

Weeks 6–8: Stakeholder Review and Roadmap Finalization. We present the strategy package to your leadership team for review and decision. We facilitate a structured working session that surfaces concerns, incorporates input, and produces a leadership-aligned roadmap — not a document that reflects our view of what should happen, but one your leadership has genuinely endorsed and is prepared to resource.

Client Involvement

The Strategy phase is collaborative by design — a Remolda-only strategy that your leadership has not shaped is a strategy that will not be implemented.

Leadership team: Two to three working sessions of 2–3 hours covering target operating model design, wave prioritisation, and roadmap review. Senior leadership input is most critical in the first week (to align on the target state vision) and in the final two weeks (to review and endorse the package).

Department managers: Input sessions to validate workflow redesign assumptions and stress-test the feasibility of proposed AI applications in their specific contexts.

IT leadership: Architecture review sessions to confirm integration feasibility, data readiness assessments, and infrastructure requirements before they are committed to the roadmap.

Finance and procurement: Review of the Investment Model and, for government clients, early engagement with procurement advisors to confirm that planned capabilities can be acquired through available vehicles within the anticipated timeline.

Common Challenges

Challenge 1: Prioritisation conflicts. Different parts of the organisation have different views on what should come first. Remolda addresses this through the Priority Matrix from the Audit phase, which provides an evidence-based framework for prioritisation conversations — shifting the discussion from "whose priority wins" to "what does the data say about impact and feasibility."

Challenge 2: Scope inflation. As the strategy takes shape, stakeholders frequently want to add more to Wave 1 than the organization can realistically execute. Remolda addresses this by modeling the implementation capacity requirements for each proposed scope and presenting a clear comparison between "ambitious but feasible" and "overpromised and likely to fail" roadmap options. The right answer is always a roadmap the organization can execute, not one that looks impressive on paper.

Challenge 3: Investment approval delays. Strategy phase deliverables are frequently required to support an investment approval process — a Treasury Board submission, a board approval, or a capital budget request — and delays in those processes can stall momentum. Remolda addresses this by designing the Investment Model and Transformation Roadmap specifically to address the questions that approvers ask, and by offering to support the approval presentation as part of the engagement.

Output: What You'll Have

At the conclusion of the Strategy phase, your organisation holds five documents ready for executive endorsement and implementation:

• Transformation Roadmap: A phased 12–36 month implementation plan with prioritised waves, dependencies, success milestones, and resource requirements per wave.
• Target Operating Model: Future-state design of key operational workflows, role definitions, and decision structures — the target you are building toward.
• AI Architecture Blueprint: Technical specification of required AI capabilities, data requirements, integration points, and build-versus-buy recommendations.
• Change Management Plan: Stakeholder communication strategy, training approach, AI Champions programme design, and resistance management playbook.
• Investment Model: ROI projections, cost modeling, and break-even analysis — the document your CFO, board, or Treasury Board analyst needs to approve the investment.

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Further reading: How to Build an AI Strategy | Digital Transformation vs AI Transformation