Problem Clarity First, GenAI Solution Second

What is the starting point for creating GenAI value?
GenAI value starts with clarity about the problem being solved. Without this, efforts tend to drift towards interesting technology rather than meaningful outcomes. A clearly defined problem acts as a foundation for everything that follows, shaping decisions around design, feasibility, ownership, and success measures. It ensures that GenAI is applied with purpose, rather than as an experiment in search of a use case.

Why do many GenAI initiatives fail early?
Most GenAI initiatives fail not because the technology is insufficient, but because the surrounding conditions are not ready. Weak problem definition, lack of alignment between stakeholders, unclear ownership, and gaps in data or processes all limit progress. In many cases, teams move too quickly into building solutions without first establishing whether the problem is real, relevant, or solvable in a scalable way.

What does a strong problem statement look like?
A strong problem statement clearly defines what is happening, who is affected, why it matters, and what outcome is expected. It connects the issue to a tangible business impact, such as delays, inefficiencies, risk exposure, or reduced quality. Importantly, it does not start with the technology. Instead, it focuses on the underlying challenge and the improvement required, which then informs whether GenAI is the right solution.

How can you distinguish between vague and actionable problems?
Vague problems are often broad and lack clear ownership or measurable impact. They describe symptoms rather than root causes and make it difficult to define success. Actionable problems, in contrast, are specific and grounded in real workflows. They identify who is affected, what is not working, and what needs to improve. This level of clarity enables better decision-making and increases the likelihood of delivering meaningful value.

What conditions need to be in place for success?
Successful GenAI initiatives depend on more than just the idea itself. They require reliable and accessible data, clear ownership and accountability, alignment across stakeholders, and the right infrastructure and processes to support development and adoption. GenAI often exposes weaknesses in these areas, so addressing them early is critical to avoid delays or failure later in the process.

How can teams assess whether to move forward?
Before moving into development, teams should apply a structured decision framework. This involves confirming that the problem is real and clearly defined, ensuring that ownership is established, and assessing whether the solution can scale safely and deliver measurable impact. This approach helps prioritise the right use cases and prevents time and resources being spent on initiatives that are unlikely to succeed.