Over the past year, we’ve embedded AI across the discovery phase of our client work. What used to take months now reliably happens in under four weeks – and in some cases, less than two. The shift has been less about “cutting corners” and more about spending time where it matters most.

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Where AI Changes the Game

• Market intelligence, compressed: Instead of manually piecing together trends and competitor moves, we now run AI-driven scans across markets in real time. This reduces weeks of effort to days, while still giving our team the raw material to ask sharper questions in workshops.
• Stakeholder intake before day one: Automated forms and AI-assisted summarisation let us capture goals, blockers, and expectations before the first meeting. By the time we sit down with stakeholders, we’re already working with a baseline understanding – making early conversations more productive.
• Turning raw research into usable insights: AI helps synthesise interview transcripts, survey data, and existing reports into digestible insights. Instead of our consultants spending days collating notes, they spend time interrogating patterns, validating themes, and challenging outliers.
• Faster clarity on segments and pain points: Using clustering models on existing datasets, we can surface user groups and their primary frustrations earlier. This means we reach the “who” and the “why” of the problem space in days, not weeks.
• Visualising solution spaces sooner: Generative tools allow us to mock up solution concepts early. It’s not about showing “final” designs – it’s about helping clients see possibilities earlier, align on priorities, and avoid missteps down the line.
• Prototyping at the pace of questions: With AI-enabled prototyping and design tools, we can test multiple directions quickly. The aim isn’t to replace design or engineering, but to accelerate the moment where ideas become tangible enough to discuss, refine, and validate.

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Why We Don’t Let AI Run the Show

Faster isn’t automatically better. AI is not a solution to every problem; rather, its best utilisation within discovery is a key consideration where we add value. At every stage, our consultants probe the AI outputs:

• Does this reflect the client’s actual context?
• What nuance might be missing?
• Where should we dig deeper before making a recommendation?

This balance keeps strategy – not technology – at the centre of the work.

The Impact

• Discovery cycles reduced from months to under 4 weeks
• Select engagements completed in under 2 weeks
• Earlier client alignment on validated opportunities

The value isn’t just in speed. Clients leave discovery with a strategy that is both evidence-driven and deeply thought through – a foundation that accelerates delivery without sacrificing quality.

Conclusion

AI doesn’t replace discovery. What it does is strip away the lag between information gathering, analysis, and validation. This reinforces the human value of consulting, emphasizing AI as an accelerator rather than a replacement. That means more time spent on the parts of discovery that actually drive value: asking sharper questions, challenging assumptions, and shaping strategies that stand up in the real world.

For our clients, this shift shows up in three ways:

1. Earlier alignment – Instead of waiting weeks to see findings or first concepts, clients see ideas take shape in real time. This creates momentum and reduces the risk of late-stage surprises.
2. Richer option-space – With AI helping us explore more scenarios in less time, we can present a broader range of viable paths – not just the obvious ones. Clients get to compare, contrast, and choose with confidence.
3. Sustained strategic depth – Any AI-generated output needs validating and contextualising within the organisation and customer landscape. The nuance of organisational context, the politics of decision-making, and the creativity of design thinking are never left to algorithms.
   
   

The result is discovery that feels faster and lighter, but not thinner. Clients leave this phase not just with documented insights, but with a clear, validated path forward that has been pressure-tested by both data and experience.

At Fabric Group, we believe this is what the future of consulting looks like: AI at the front line of efficiency, and human expertise at the centre of judgment and strategy.

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