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Research you can act on
Guides and research on getting value out of AI in regulated, document-heavy organisations. Written by the people who build and deliver the software, so the frameworks come from engagements rather than from summarising other people’s reports.
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42 pages · Strategy
The Executive’s Complete Guide to Enterprise AI Strategy
A strategic framework covering assessment through to implementation: building the business case, sequencing a roadmap, measuring ROI, managing risk, and handling the organisational change that decides whether any of it sticks.
Inside: strategic assessment and opportunity identification · building the investment case · implementation roadmaps and milestones · governance and risk frameworks · organisational readiness and change management.
Request the guide →The library
Shorter, more focused pieces on the problems that come up most often.
AI Governance & Compliance Framework
Establishing AI governance that satisfies regulators without stopping delivery: decision rights, model and vendor policy, data handling, audit, and where the human approval boundary sits.
Request this paper →The State of Enterprise AI Adoption
Where organisations actually are with AI as against where announcements suggest: what’s in production, what stalled at pilot, and the patterns that separate the two.
Request this paper →Scaling AI: From Pilot to Production
The engineering work between a promising proof of concept and a system the business depends on: integration, observability, cost control, model independence and handover.
Request this paper →Document Automation in Regulated Industries
Where document capture, extraction and workflow automation pay back fastest, and how to keep the process defensible when someone asks why a decision went the way it did.
Request this paper →Prefer the short version?
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