# operational risk Published articles for operational risk. This is one page of public article previews, not the complete archive. Follow Next page to continue. Summaries are not the original full articles. ## Why agentic AI starts with legacy modernisation DevFeed: [Why agentic AI starts with legacy modernisation]() Original publisher: [Read original article]() Author: Suzanne Angell Published: 2026-08-21T09:33:00Z Content type: opinion Language: en Sources: [Scott Logic]() Topics: [Artificial Intelligence](), [AI Agent](), [legacy](), [legacy systems](), [data](), [Processes]() Tags: [agentic-ai](), [agents](), [ai-agents](), [artificial-intelligence](), [data](), [governance](), [integration](), [legacy](), [legacy-modernisation](), [operational-risk](), [processes](), [risk-management]() ### AI overview The article argues that organisations must address fragmented data, brittle processes, and outdated architectures before they can realise the full value of agentic AI. It explains that legacy systems may remain operationally critical, while accumulated technical, process, and organisational debt can prevent agents from accessing reliable information and executing workflows consistently. ### Source excerpt Organisations are increasingly excited by the potential of agentic AI, but many overlook the legacy obstacles that stand in the way. In this post, I explore why successful AI adoption depends on tackling fragmented data, brittle processes and outdated architectures, and why modernisation is often the most important step towards unlocking value from intelligent agents. ## Unlocking Safer, Faster Experimentation for a Global Tech Leader DevFeed: [Unlocking Safer, Faster Experimentation for a Global Tech Leader]() Original publisher: [Read original article]() Author: Kristin Kaeding Published: 2025-07-18T22:18:00Z Content type: article Language: en Sources: [8th Light Insights]() Topics: [Development](), [systems](), [Deployment](), [iteration]() Tags: [architecture](), [cross-functional-teams](), [delivery-and-practice](), [development](), [engineering](), [operational-risk](), [platform-innovation](), [workflows]() ### AI overview A case study describes 8th Light's seven-week assessment for a Fortune 100 consumer technology company whose growing experimentation pipeline was slowed by manual approvals, fragmented workflows, and unclear ownership. The work combined human-centered design, technical architecture, organizational strategy, and the Double-Diamond process to define a more scalable, self-service experimentation platform. ### Source excerpt Why It Matters At 8th Light, we help enterprise teams remove friction, foster alignment, and build tools that scale with confidence. This project exemplifies what happens when human-driven design meets technical rigor: major time and cost savings. By focusing on systems thinking, user needs, and resilient architecture, the organization created a path forward that supports both immediate impact and long-term innovation. This story is one of many showing how that approach delivers lasting results. The Challenge: A Strong System Slowed by Scale A Fortune 100 consumer technology company built a powerful experimentation pipeline -- one that fueled product innovation across its digital ecosystem. As the platform grew, so did its complexity; manual approvals, fragmented workflows, and inconsistent tools created friction that slowed development cycles and added risk. Rather than patch over the pain points, the company sought a bold transformation to reduce this risk: to turn a solid foundation into a modern, scalable, and self-service experimentation platform. The Goals Accelerate the end-to-end experimentation pipeline Reduce manual bottlenecks and operational risk Align cross-functional teams around shared metrics and ownership Unlock safe, scalable innovation at speed Our Approach: Human-Centered Meets Technically Grounded 8th Light was brought in to lead a seven-week high-level assessment, blending human-centered design with technical architecture and organizational strategy. We followed the Double-Diamond Process to move from discovery to delivery: Problem Discovery Problem Synthesis Solution Discovery Solution Synthesis The TimelineWeeks 1-2: Solving the Friction We kicked off with deep interviews across engineering and product leadership. These conversations uncovered systemic blockers -- ranging from delays in approvals to lack of experiment ownership. Weekly playback sessions helped align stakeholders and refine the focus on the end-to-end experimentation lifecycle.