Overview

A global commodities trading firm operating under tight regulatory scrutiny engaged us to help them explore how artificial ntelligence could  support their operations in a way that enhanced efficiency without compromising regulatory or reputational safeguards. While they recognised the urgency of keeping pace withAI developments, they were equally aware of the reputational, operational, and compliance risks of moving too quickly or without clear purpose.

Their key concern:
“We know we can’t afford to be left behind on AI—but we also can’t afford tomove forward without knowing where it will deliver real business value, and how to manage the risks.”

Challenges

Background Context:

The client’s primary objective was to understand how AI could create real value in their business without jeopardising compliance or operational control. They had no internal AI function and no prior roadmap for adoption. Their leadership wanted to explore AI opportunities—but only if they aligned with measurable business benefits and didn’t introduce risk.

Specific Challenges:

- A lack of internal clarity on where AI could be safely and productively used.
- Concern over data fragmentation, access, and security—especially in a regulated environment.
- Desire to modernise without compromising their brand or obligations to shareholders, regulators, or customers.
- The board and leadership team felt they didn’t have the information needed to make confident decisions.

Previous Attempts:

There had been no prior structured attempt to explore AI adoption. The client recognised this was a gap and proactively sought strategic guidance to become informed and make sound decisions.

Solution

Initial Planning:

We scoped a strategic consultancy engagement. The goal was clarity—not code. Through collaborative discovery sessions, interviews across key departments, and alignment with board-level stakeholders, we sought to understand both the current landscape and future ambitions.

Proposed Solution:

Rather than focusing on specific technologies from the outset, our proposal centred around providing an AI readiness assessment, a strategic framework for evaluating use cases, and a prioritised roadmap that considered feasibility, risk, and ROI.

This approach was chosen to ensure any future implementation would be grounded in business value, aligned to regulation, and not led by hype or internal pressure.

Implementation Process:

- Conducted detailed interviews across six departments to uncover inefficiencies, gaps, and opportunities.
- Mapped potential AI use cases against business objectives and risk factors.
- Provided a high-level roadmap to begin with strengthening the data foundation before considering pilot use cases.

We maintained close collaboration with the client, especially around stakeholder engagement, to ensure the final outputs reflected both operational detail and strategic value.

Customisation and Innovation:

This was a highly tailored consultancy engagement focused on business model alignment, not technology delivery. The framework we developed balanced innovation with control—enabling the client to take first steps safely, strategically, and with internal consensus.

Results

Quantifiable Results:

- Identified six meaningful areas where AI could reduce inefficiencies or improve accuracy, aligned with regulatory expectations.
- Provided a decision framework that clarified where to invest and what groundwork (data, process, governance) was needed before doing so.

Qualitative Results:

-The client left the engagement with board-level clarity on what AI meant forthem—not just technically, but strategically.

- Instead of reacting to external pressure, they now had an internal roadmapand a confident message for stakeholders.

- The engagement helped turn uncertainty into strategic confidence.

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Post-Implementation Support:

We provided a clear set of recommendations for next steps, including a prioritised roadmap and data governance actions.The client can now proceed at their own pace, with guidance available as needed.

Long-Term Impact:

The organisation is now positioned to explore AI with confidence, in a way that safeguards its reputation and enhances business performance. The roadmap is phased, risk-aware, and fully owned by internal stakeholders.
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Client Perspective & Reflections

The client valued the clarity, professionalism, and business-first framing of the engagement. The timeline was respected, and communication throughout was open and pragmatic. Their internal stakeholders appreciated that the work empowered them to make informed decisions, rather than pushing technology for technology’s sake.

If asked to recommend the project to others, they’d describe it as a process that delivered “strategic clarity with risk-aware realism”—helping them understand that AI adoption should start with the right questions, not the quickest answers.

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