From fragmented back office to a clear roadmap for change
A fast-growing international law firm had tried to fix its operations before. It had not worked. SKAI mapped nine operational areas, identified where time and revenue were being lost, and delivered a roadmap that showed exactly what to fix, in what order, and where AI could genuinely help.
A firm that had grown faster than its processes
The client is an international law firm, part of a larger international network. Over the past decade the firm had grown well beyond its original setup. The ways of working had not kept pace. A previous internal hire had not delivered results. The firm came to SKAI with three questions: where is time and money being lost, what do we fix first, and where can AI actually help us?
Everyone was busy, but the work kept piling up
Every department had its own way of working. Recurring tasks were done differently by different people, data lived in separate systems that were never connected, and manual steps had piled up across the organisation. The firm was spending significant time on work that existed only because the underlying processes had never been updated as the firm grew.
Start with understanding, then decide what comes first
SKAI held 13 interview sessions with more than 25 people across all departments. Every major process was mapped from start to finish. The focus was on understanding what was actually causing the most damage, not on finding everything that could be improved.
Every finding was assessed on four factors: time lost per week, revenue impact, whether a fix required coordination outside the firm, and how quickly it could be implemented. This produced a prioritised roadmap handed over with full clarity on effort, dependencies and required decisions. Each initiative was also assessed for where AI could realistically add value once the underlying process was in order.
25 to 40 hours per week identified as recoverable
The diagnostic gave the firm something it had not had before: a clear picture of where time and money were actually going, and a prioritised plan to act on it. The quick wins alone would recover 25 to 40 hours per week. Revenue impact and broader efficiency gains from full implementation were not yet included in that number. The conservative estimate for avoidable overhead was 75,000 to 100,000 euros per year.
The roadmap was structured in three layers. Nine quick wins the firm could start immediately with no new budget. A set of dependencies requiring coordination with the wider group. And three bold moves for leadership to decide on: a redesigned revenue cycle, a firm-wide knowledge hub and a client portal, each with a phased implementation plan.
“This is more than I had expected. Thank you very much.”
— Managing Director, during the final presentationEfficiency is only part of the question
Fixing individual processes is not enough if the systems underneath them are not built for where the firm is heading. Several of the findings required a strategic decision first: which systems stay, which go, and how should they connect going forward. These are not operational choices. They are leadership choices, and they determine whether improvements hold or quietly unravel again.
AI was part of the brief from the start. The diagnostic identified clear opportunities, but in almost every case the data needed to support them was incomplete or spread across systems that did not talk to each other. AI can only accelerate a process that already works. Getting the foundation right is the first step, not an afterthought.
Most firms asking where AI can help are really asking a process question first. Before the technology, comes the decision: are your systems and ways of working ready for where you want to go? That question is worth asking before the next tool gets added.