How a London Consultancy Took AI Rigour to 300 Staff

A leading London transformation consultancy carried its consulting rigour into AI workflows — enabling ~300 staff and moving directors from ad-hoc Claude use to client-ready output.

~300

Staff enabled across functions

Implementation Time

Mel Moeller

Chief AI Officer

GenFutures Lab

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The Challenge

A leading transformation consultancy in London already brought strong consulting discipline — judgment, validation, quality standards and delivery rigour — to its client work. As AI became a growing part of how teams think, analyse and deliver, the firm wanted to apply those same standards to internal AI-enabled workflows, in ways that were practical, responsible and aligned with client expectations — moving from one-off AI use to repeatable habits at scale.

What They Built

GenFutures Lab designed and facilitated a blended AI enablement programme — online modules plus in-person working sessions — to help teams apply AI to internal tasks in grounded, role-relevant ways. The first phase touched around 300 people across multiple functions, with 120 staff in the hands-on in-person workshops, focused on structuring outputs, applying AI to internal workflows, and turning one-off solutions into repeatable habits. A follow-up executive Q&A for directors applied the same structured prompting approach to creating client-ready, branded PowerPoint decks with Claude and building reusable consulting accelerators from messy inputs.

GenFutures Lab framed the work around the consultancy's existing strengths rather than AI for its own sake. The premise was that proven review habits, delivery discipline and quality expectations should carry into AI-enabled workflows. The team designed and facilitated a blended programme — online modules plus in-person working sessions — reaching around 300 people across multiple functions in the first phase, with 120 staff in the hands-on in-person workshops. Sessions were interactive and directly relevant to participants' day-to-day roles, helping teams structure outputs more effectively, apply AI to internal tasks, and move from one-off solutions to repeatable habits. A structured prompting approach ran through every module. Following the first phase, the team delivered a focused executive Q&A for a group of directors — less structured training than hands-on problem-solving around creating client-ready, branded PowerPoint decks with Claude and building reusable consulting accelerators from messy inputs. The directors were already individual AI users; the session gave them a shared reference point and a higher standard of output, building momentum toward wider Claude access and agentic workflows.

AI Role

Claude is used directly by staff to draft and structure internal work — including generating client-ready, branded PowerPoint decks and turning messy inputs into reusable frameworks, playbooks and consulting accelerators — applied within the firm's existing review and quality discipline.

AI Model

Claude

Infrastructure

Integration Points

Impact

~300 people

Enabled across multiple functions in phase one; 120 in person.

Shared prompt library

Cross-functional use cases and repeatable AI workflows established.

Executive buy-in

Directors moved toward wider Claude access and agentic workflows.

Technology Utilized

Implementation Complexity

Time Savings

Best Fit For

Consultancies and professional-services firms that already have strong delivery discipline and want to extend that rigour, judgment and quality control into AI-enabled internal workflows at scale.

Mel Moeller

Chief AI Officer

GenFutures Lab

Former Sky, BBC & HP, is an AI thought leader who helps organizations rapidly adopt AI, drive measurable ROI, scale innovation, and foster AI literacy across diverse industries.

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Industry:

Professional Services

Business Function:

Executive & Strategy

Operations

Company Size:

Project Cost:

Cost not disclosed

Ownership:

Organization Type:

AI Pattern:

AI Workforce Enablement

Value Type:

Time Savings

AI Model:

Frequently Asked Questions

How did a transformation consultancy scale responsible AI use across its teams?

The team designed and facilitated a blended enablement programme — online modules plus in-person workshops — reaching around 300 staff (120 in person) across multiple functions, framed around the firm's existing consulting rigour. A follow-up executive Q&A coached directors on client-ready outputs.

What AI tools and approach were used?

The work centred on AI workforce enablement using Claude, applied through structured prompting rather than a custom build — including generating client-ready, branded PowerPoint decks and turning messy inputs into reusable frameworks and accelerators.

What results did the consultancy achieve?

Outcomes in the first phase were largely qualitative: a shared prompt library, repeatable cross-functional AI workflows, strong engagement across functions, and clear executive momentum toward wider Claude access and agentic workflows. (No quantified metrics were reported.)

How long did the programme take?

It was delivered in phases, beginning with a first phase of online modules and in-person workshops followed by an executive Q&A session; the source does not state a fixed overall duration.

Who is this AI enablement approach best for?

Consultancies and professional-services firms that already have strong delivery discipline and want to extend that rigour and quality control into AI-enabled internal workflows at scale.