AI in USE #32 ✨: From Copilots to Cyber Guardians: AI at the Core of Modern Operations
🔍 How AI is quietly transforming workflows, automating decisions, and defending digital frontiers
Welcome to the latest edition of AI in USE, where we bring you the most compelling examples of artificial intelligence transforming industries. This week, we’re spotlighting how AI is reshaping the way organizations work, think, and protect themselves—all while raising important questions about autonomy and trust 🤖🔐🧠
Here’s what’s inside:
🧠 A global bank is giving thousands of employees an AI copilot—could this be the future of knowledge work?
🤖 A bold new approach to automation is taking shape—where AI watches how you work and builds the workflows for you.
🚨 And finally what happens when AI defends your network like an immune system—but evolves on its own?
👇 Dive into the full stories below to see how these innovations are unfolding in the real world.
🏦 Standard Chartered – Tailored AI Assistant for Banking Operations
Organization Type: Corporate
AI Purpose: Augment
Type of AI Model: Generative AI
AI Application Type: Operations
Targeted Industry: Banking and Financial Services
Target Group (AI User): Employees
Use Case Description:
SC GPT is Standard Chartered’s internal generative AI assistant, built on Azure OpenAI’s GPT models. While the underlying model is off-the-shelf (likely GPT-4), the solution is tailored through interface design, prompt templates, and workflow integrations specific to functions like marketing, risk, software development, and customer service. The tool addresses inefficiencies in routine work and improves employee productivity by acting as a secure, role-specific AI copilot.
Key Features:
Role-specific prompt templates (e.g., marketing copy, risk summaries, code generation)
Integrated with MS Teams and internal portals
Document summarization and drafting
Internal Q&A planned via retrieval-based access to 11,000+ documents
Local teams can build domain-specific mini-apps
Results:
30–40% reduction in time spent on repetitive tasks
One process cut from 8 months to a few days (~39,000 hours saved)
Early signs of improved output consistency and employee satisfaction
Broad functional uptake validated enterprise-wide deployment
Launch Date: March 2025
Retrieve the case and more (including their sources) on the AI in USE website
🔀 {Agentic AI} Orby Generative Process Automation
Organisation Type: Start-up
AI Purpose: Automate
Type of AI Model: Generative AI
AI Application Type: Operations
Targeted Industry: Multi-industry
Target Group (AI User): Operations managers, Finance professionals, Legal teams, Business analysts
Use Case Description:
Orby AI addresses the inefficiencies of traditional Robotic Process Automation (RPA) by introducing Generative Process Automation (GPA). It uses Large Action Models (LAMs) that observe user behavior, learn workflows, and autonomously generate automations without requiring explicit programming—making process automation accessible even to non-technical business users.
Unlike traditional RPA, which relies on manually scripted, rule-based logic and is often brittle in the face of interface or data changes, Orby AI uses a hybrid of neural and symbolic reasoning to understand the intent behind tasks and adapt dynamically. It handles both structured and unstructured data, continuously learns from user interactions, and autonomously generates AI agents that can complete complex, context-sensitive business processes. This makes it suitable for automating finance audits, legal contract reviews, or multi-step workflows across tools.
Key Features:
Observes and learns from user behavior in real-time
Generates automations using symbolic + neural reasoning
Integrates AI agents for tasks like data analysis and customer interaction
Autocomplete for process creation
Adaptive continuous learning
Results:
Significant time and cost savings in finance auditing and legal contract review
Improved ROI on automation initiatives
Strategic shift from task execution to workflow innovation
Launch Date: June 2023
Retrieve the case and more (including their sources) on the AI in USE website
🔐 Darktrace Self-Learning Cybersecurity Platform
Organization Type: Scale-up
AI Purpose: Automate
Type of AI Model: Unsupervised / Reinforcement learning
AI Application Type: Risk management
Targeted Industry: Multi-industry
Target Group (AI User): IT security managers, IT administrators
Use Case Description:
Darktrace’s ActiveAI Security Platform uses self-learning AI to detect, investigate, and autonomously neutralize novel cyber threats across IT and OT environments. Unlike traditional tools trained on generic data, it builds a unique model per organization — learning what’s “normal” in real time and spotting subtle behavioral anomalies. This "digital immune system" approach, powered by a hybrid of unsupervised learning, probabilistic models, and graph-based clustering, makes Darktrace especially effective at identifying zero-days, insider threats, and advanced persistent attacks. The platform also includes Cyber AI Analyst, which mirrors a human analyst’s workflow to automate incident investigations.
Key Features:
Self-learning AI that customizes per customer environment
Cyber AI Analyst for automated narrative-driven investigations
Cross-domain threat correlation (cloud, email, OT, network)
Proactive threat path modeling using MITRE ATT&CK knowledge base
Autonomous real-time threat mitigation
Results:
Identifies 74% of threats missed by traditional tools
Reduces false positives by 60%
Cuts triage time by 92%
Improves cyber resilience for 85% of organizations
Launch Date: April 2024
Retrieve the case and more (including their sources) on the AI in USE website
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🔗 Visit our website AI in USE to explore the full library of AI use cases and discover how AI is transforming industries across the globe:
✨ We hope these AI use cases spark inspiration!
💬 Let us know which one intrigued you the most—your feedback helps us grow!
Disclaimer: This content was (obviously 😉) built with the assistance of AI.
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