10 real-life Business Process Automation examples for IT
10 real-life Business Process Automation examples for IT
The IT function is responsible for service reliability, system access, change management, and support across a constantly evolving application estate.
The best automations reduce ticket handling, environment maintenance, account provisioning, monitoring response, and repetitive engineering work, but they have to be built with operational guardrails because mistakes can cascade quickly across the organisation.
Duolingo deploys GitHub Copilot across its 300-strong engineering team to accelerate development across more than 400 microservice repositories. Developers new to a codebase gain at least 25% speed improvement, while code review turnaround time has dropped by 67%.
Use Case
AI-Assisted Code Generation and Review
Tools
GitHub Copilot
Input
Active codebase context, developer prompts, and pull request diffs across 400+ microservice repositories.
Process
GitHub Copilot analyses the surrounding codebase context and surfaces autocomplete suggestions, boilerplate completions, and code review feedback inline within the developer's IDE.
Output
Contextually aware code suggestions, completed functions and pull request feedback delivered directly within the developer workflow.
Outcome
Developer speed increases by 25% for those new to a repository and 10% for experienced contributors with median code review turnaround cut from 9.6 days to 2.4 days and pull request volume rising by 70%.
SaaS and Software Products
IT
Accenture's Enterprise GitHub Copilot Deployment
Accenture rolled out GitHub Copilot to 50,000 developers across its global software delivery operations. The deployment resulted in an 84% increase in successful build rates and a 26% increase in pull requests completed per week, as measured in a randomised controlled trial alongside Microsoft and academic researchers.
Use Case
AI-Augmented Software Delivery at Scale
Tools
GitHub Copilot
Input
Developer prompts, existing codebases, and task context entered by Accenture's software engineers across client delivery and internal development projects.
Process
GitHub Copilot analyses in-IDE codebase context and generates real-time code completions, function suggestions, and commit-ready code across Accenture's global development workforce.
Output
AI-generated code completions and function suggestions integrated into developer workflows, supporting faster pull request cycles and higher build success rates.
Outcome
Successful build rates increased by 84%, weekly pull request completion rose by 26%, and developer throughput improved measurably, enabling Accenture to deliver client projects faster with the same headcount.
Equinix deployed its Equinix Fabric Intelligence platform to apply AI to its global interconnection network, dynamically optimising routing for AI inferencing workloads and improving performance across its 273 data centres in 77 markets.
Use Case
AI-Driven Network Interconnection Optimisation
Tools
Internal Tools
Input
Real-time traffic flows, latency metrics, and workload characteristics across Equinix's global Fabric network spanning 273 data centres, alongside customer workload patterns and infrastructure utilisation data.
Process
AI models analyse network telemetry and workload demands to dynamically optimise routing decisions and capacity allocation, prioritising low-latency paths for AI inferencing workloads and balancing traffic across the interconnection platform.
Output
Optimised routing configurations and capacity recommendations applied in real time across the Equinix Fabric network, with enhanced support for distributed AI training, inference, and data sovereignty requirements.
Outcome
Equinix reports improved inferencing workload performance and network efficiency, reinforcing its position as a distributed AI infrastructure platform for hyperscale and enterprise customers building AI applications across its global ecosystem.
IT Infrastructure and Hosting
IT
Spotify's Honk Coding Agent
Spotify built Honk, an internal AI coding agent integrated with Claude Code, that automatically generates pull requests for code migrations and ad hoc engineering tasks across its entire codebase, enabling engineers to direct changes via Slack rather than writing code manually.
Use Case
AI-Powered Codebase Maintenance and Feature Development
Tools
Claude Code & Claude
Input
Natural language prompts from engineers, submitted via Slack or GitHub Enterprise, describing migrations, refactors, bug fixes or new features.
Process
Honk routes the prompt through a multi-agent architecture - a planning agent gathers context, then a Claude Code agent writes the diff, applies linting via MCP, and evaluates output quality using an LLM judge.
Output
Reviewed pull requests opened automatically against target repositories, ready for engineer approval and direct deployment to production.
Outcome
Spotify reports 60–90% time savings on complex migrations and has merged over 1,500 AI-generated pull requests, with senior engineers shifting from writing code to directing AI agents.
Consumer Internet Platforms
IT
DXC Technology's AI-Powered Security Operations Centre
DXC Technology deploys AI-driven automation across its global Security Operations Centres, replacing manual alert triage with machine-learning models that detect, investigate, and contain threats autonomously. The result is a 60% reduction in alert fatigue and a 50% decrease in mean time to detect and respond.
Use Case
Automated SOC Threat Detection and Response
Tools
7AI
Input
Security event logs, network telemetry, endpoint alerts, and threat intelligence feeds from across DXC's global IT environment
Process
AI agents automatically classify and prioritise alerts, correlate indicators of compromise, and execute predefined containment actions without human intervention.
Output
Automated incident triage decisions, threat containment actions and escalation of genuine high-priority incidents to human analysts
Outcome
Alert fatigue reduced by over 60%, mean time to detect and respond cut by 50% and proactive risk mitigation.
Goldman Sachs becomes the first major bank to deploy Cognition Devin, an agentic AI software engineer, to handle complex multi-step coding tasks including legacy code modernisation and test generation across its 12,000-strong developer team.
Use Case
Autonomous Software Development and Code Modernisation
Tools
Cognition Devin
Input
Internal codebase tasks and developer prompts defining the scope of engineering work, including legacy systems requiring migration to modern programming languages.
Process
Devin, an agentic AI from Cognition Labs, autonomously navigates codebases, writes and tests code, and resolves bugs end-to-end with human review of outputs.
Output
Completed code changes, documentation, and test suites submitted for human engineer review and deployment.
Outcome
Goldman Sachs expects Devin to increase developer productivity by three to four times compared with previous AI coding tools, freeing engineers from drudge work such as legacy migration.
Corporate and Investment Banking
IT
PwC's Agent OS Multi-Agent AI Orchestration Platform
PwC launches Agent OS, a patent-pending enterprise AI operating system that connects and orchestrates over 250 AI agents across tax, assurance, and advisory workflows. The platform delivers productivity improvements of 20 to 50 percent across software development, finance, and marketing functions.
Use Case
Enterprise AI Agent Orchestration
Tools
OpenAI & Google Cloud
Input
Business process triggers and workflow tasks across functions including tax, audit, software development, finance, and marketing are submitted to the agent network.
Process
Agent OS routes tasks to the appropriate specialist AI agents, coordinating across major cloud providers, LLM vendors, and enterprise platforms such as Salesforce, SAP, and Workday, under a unified governance layer.
Output
Completed workflow outputs including drafted documents, analysed data, and processed transactions, delivered up to ten times faster than traditional methods.
Outcome
Productivity gains of 20 to 50 percent achieved across key business functions, with over 31 million generative AI interactions logged internally and the platform now deployed for enterprise clients globally.
Management and Strategy Consulting
IT
Goldman Sachs' AI Coding Assistant Rollout
Goldman Sachs deploys GitHub Copilot and Google Gemini Code Assist to more than 12,000 developers, achieving productivity gains of 20% and up to 55% on specific coding tasks. The rollout is integrated into the firm's centralised GS AI platform, where all generated code passes the same quality checks as manually written code.
Use Case
Enterprise-Scale AI Code Assistance
Tools
GitHub Copilot & Google Gemini Code Assist
Input
Developer prompts, existing codebase context, and task descriptions entered by engineers across Goldman Sachs' software development lifecycle.
Process
GitHub Copilot and Gemini Code Assist analyse codebase context and provide real-time code suggestions, completions and refactoring support, integrated within the firm's GS AI internal platform.
Output
AI-generated and completed code suggestions surfaced inline within developer IDEs, passing through the firm's standard automated quality and compliance checks.
Outcome
Developer productivity improves by an average of 20%, with gains of up to 55% on specific tasks, enabling the firm's 12,000-plus engineers to redirect capacity towards complex architecture and higher-value work.
Corporate and Investment Banking
IT
IBM Consulting Advantage AI Services Platform
IBM Consulting deploys its Consulting Advantage platform to its 160,000 consultants, providing role-based AI assistants for strategy, business analysis, and software development tasks. An application development and testing pilot delivered productivity improvements of up to 50 percent.
Use Case
Role-Based Consultant AI Assistant Deployment
Tools
IBM Watson
Input
Consultants submit day-to-day task requests spanning strategy use case prioritisation, user persona design, code generation, and application testing across client engagements.
Process
Role-trained IBM Consulting Assistants, powered by IBM watsonx and accessible via a conversational interface, apply proprietary methods and industry knowledge, with consultants able to toggle across multiple generative AI models.
Output
Task-specific outputs including prioritised use case assessments, UX personas, generated and converted code, and test results, drawn from IBM's collective institutional knowledge.
Outcome
Application design, development, and testing pilot achieved up to 50 percent productivity improvement, with the platform scaling across 160,000 consultants to accelerate consistent client delivery.
This automation enables Vodafone to scale its security operations through a robust SOAR framework, utilising n8n to orchestrate threat intelligence, fraud detection, and incident response. By automating the triage of security alerts and the scanning of malicious data, the system has drastically accelerated threat response times from hours to minutes while delivering significant cost avoidances.
Use Case
Security Orchestration, Automation, and Response (SOAR)
Tools
n8n
Input
Security alerts, threat intelligence feeds, monitoring data, and incident tickets from cybersecurity infrastructure
Process
Workflows orchestrate data flows across security tools to perform automated threat detection, IP geolocation, and fraud detection. Reusable modular components are utilised across teams to standardise alert triage and accelerate the creation of new security workflows.
Output
Automated threat analysis reports, classified incident data with activity tags, and instant notifications via email or Slack
Outcome
5,000 person-days saved and £2.2 million in avoided costs since August 2024, with ongoing savings of approximately £300,000 per month