The situation

Bright Edge Accounting is a mid-sized firm with 28 staff serving a mix of SME and family-owned business clients. The firm has built a strong reputation on responsive, personalised service — partners know their clients by name, and that relationship-driven approach is central to how the practice operates.

But growth is creating pressure. Partners are spending significant portions of their week on routine drafting — client letters, engagement summaries, compliance correspondence, and advisory follow-ups. Work that requires judgement at the review stage, but not necessarily at the drafting stage. The volume has increased steadily as the client base has grown, and there’s no sign of it slowing.

At the same time, several staff members have started using AI tools independently. Some are getting useful results; others are pasting client information into free, publicly available tools with no understanding of where that data goes or how it’s stored. There are no firm-wide guidelines, no agreed platforms, and no shared approach. In a profession where confidentiality is a core obligation — and a regulatory one — this is a growing and unmanaged concern.

The firm isn’t resistant to change. The partners can see the potential of AI to free up capacity and improve consistency. But they’re time-poor, unsure where to start safely, and wary of investing in something that disrupts more than it delivers. What they need is a practical, contained starting point that demonstrates value without introducing risk.

The specific challenges

• Routine drafting consuming senior time. Partners and senior staff spend an estimated 6–8 hours per week on first-draft client communications — engagement letters, advisory summaries, compliance updates — that follow predictable patterns but still require manual effort each time.
• Shadow AI use with no confidentiality safeguards. Several staff members are using publicly available AI tools to draft correspondence and summarise documents. There are no guidelines on what information can be shared, no approved platforms, and no oversight. In a profession built on client trust and regulatory compliance, this is an unmanaged risk.
• Capacity constraints limiting new client intake. The firm has a pipeline of prospective clients but limited capacity to onboard them. Senior time is the bottleneck — not capability or reputation. Freeing even a few hours per week of partner capacity would directly support the firm’s growth objectives.
• No shared framework for evaluating AI tools. Individual staff are making independent decisions about which tools to use and how. Without a shared approach, the firm can’t ensure consistency, quality, or compliance across the team.

Where we’d start

Client communication support using the firm’s own templates. This is a contained, low-risk use case that addresses the most immediate capacity constraint: routine drafting that follows established patterns.

We’d focus here because it connects directly to the firm’s priorities — freeing senior time, managing confidentiality risk, and demonstrating practical value quickly. Rather than proposing a broad AI strategy, we’d start with something the partners can see working within weeks: a tested prompt library built around the firm’s actual templates and communication standards, with clear guidelines on what’s safe to use and what isn’t.

How we’d work with Bright Edge

Discovery (week 1)

We’d begin with a focused discovery session with the partners and two to three senior staff. The goal is to understand where senior time is being consumed, which communication types follow repeatable patterns, and what the firm’s current confidentiality obligations and compliance requirements look like.

We’d also map the shadow AI use that’s already happening — not to critique it, but to understand the risk profile and identify what needs to be addressed in the guidelines. This gives us a clear picture of the firm’s starting point and priorities.

Duration: 1 week, with sessions scheduled around partner availability.

Design (weeks 1–3)

Drawing on what we learn in discovery, we’d design a tested prompt library tailored to the firm’s most common communication types — engagement letters, advisory follow-ups, compliance correspondence, and client summaries. Each prompt would be built around the firm’s existing templates and tone, so the output sounds like Bright Edge, not like a generic AI tool.

Alongside the prompt library, we’d draft practical guidelines covering approved tools, confidentiality boundaries, and quality review expectations. These guidelines would be co-designed with the partners to make sure they’re workable, clear, and owned by the firm — not imposed from outside.

Duration: 1–2 weeks, working iteratively with partners to refine outputs.

Delivery (weeks 3–4)

A small-group coaching clinic with staff, structured around real tasks from the firm’s day-to-day work. Staff would practise using the prompt library on actual communication types (using anonymised client data), refine their prompts in real time, and leave with a workflow they can apply immediately.

Partners would receive a separate one-to-one session focused on reviewing AI-assisted outputs efficiently and understanding where human judgement remains essential. This is practical, hands-on work — not a lecture on AI trends.

Duration: Half-day workshop plus individual 1:1 sessions, scheduled to minimise disruption to client work.

Review (post-delivery)

We’d check in at 30 and 60 days to assess adoption, capture what’s working, and refine the prompt library and guidelines based on real-world use. This is where the firm builds lasting confidence — seeing the tools deliver consistent value over time, not just in a workshop setting.

Duration: 30 and 60-day post-delivery check-ins, with email support available between sessions.

What the firm would gain

• Tested prompt library — tailored to the firm’s templates, tone, and most common communication types, ready to use from day one
• Confidentiality and safe-use guidelines — clear, practical rules on approved tools, data boundaries, and quality review expectations
• Staff confidence — practical skills built through hands-on exercises using the firm’s actual work, not abstract examples
• Partner clarity — a clear understanding of where AI adds value, where human judgement remains essential, and how to review AI-assisted outputs efficiently
• Immediate capacity release — a practical pathway to reclaim senior hours currently spent on routine drafting
• A framework for evaluating future AI use cases — so the firm can expand confidently as comfort and capability grow

This scenario is a composite example based on sector research and common organisational challenges. We maintain strict confidentiality for all client work.