
Phase 2 – Solution Design can be activated independently at any point in the journey. Some clients enter this phase with a prioritized opportunity already defined; others use it to reinforce, redesign, or validate an existing solution. In broader transformation programs, it sits within the full AIxBu™ methodology as the bridge between opportunity definition and execution.
The goal of this phase is to design the end-to-end solution with flexibility and rigor — ensuring business viability, operational clarity, and risk control. The AIxBu™ team works alongside you to tailor the design to your specific context before moving forward.
At any stage of an organization’s journey, clarity on the problem to solve and the business objective to achieve is foundational. Without a clear understanding of the “what” and the “why,” even the most technically sound design risks becoming irrelevant.

“A well-designed solution solves the right problem — not the most technically interesting one.”
This step defines how the process should function once the solution is in place — covering roles, activities, decision points, information flows, and performance metrics.
Comparing the current state with the desired future state to identify gaps and transformation priorities.
Identifying where AI can optimize, automate, or augment specific tasks within the process.
Defining who owns what within the redesigned operating model.
Mapping how data and information will move across the process and what integrations are required.
Establishing the metrics that will measure success and performance in the new model.
Process design is the critical bridge between strategy and execution. Within AIxBu™, it is applied adaptively — meeting organizations where they are and helping them define how to operate more effectively at each stage of their transformation.
This step defines what data is needed, where it comes from, how it is processed, and what technology capabilities — assessed without vendor bias — are required to enable the solution.
Required data sources
Data model and necessary transformations
Data quality and governance strategy
Required analytics or AI capabilities
Functional definition of what is needed, not specific products
Evaluation of options: build vs. buy vs. partner
Integration considerations with existing systems
Vendor-neutral selection criteria: cost, scalability, support, maturity
Technology is a means, not an end. It is selected to serve the solution — which is itself designed collaboratively and flexibly, shaped by the organization's real context and constraints.
A structured set of criteria to assess design maturity and readiness to advance to prototyping or implementation, calibrated to the organization's pace and priorities.
This phase exists to ensure rigorous design discipline — preventing rework, cost overruns, and the risk of building solutions that are technically sound but commercially irrelevant. The depth and scope of this work adapts to context: it applies equally to new initiatives, the optimization of existing solutions, and full-scale transformation programs.
Solution Design