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    Capita's Governance Insights for Scaling Agentic AI Effectively

    As businesses scale their AI capabilities, Capita underscores the imperative of embedding governance from the beginning to ensure reliable and efficient AI operations. Discover the pivotal lessons learned from their extensive journey in AI adoption.

    capita.comSeptember 6, 20262 min read

    Key Facts

    • Capita processes 20M NHS claims/year, showcasing efficiency in high-volume environments.
    • 30-40% reduction in case management costs indicates significant financial performance improvement.
    • Governance frameworks prevent duplication, enhancing innovation and operational efficiency.
    • 88% faster dispute resolution reflects competitive advantage through effective AI orchestration.
    • AI integration saved 1,000 hours in recruitment, highlighting strategic operational benefits.

    Summary

    Summary

    Capita, a leading provider of critical services across public and private sectors, faced the challenge of effectively governing a growing estate of AI agents. To address this, they implemented a robust governance framework and orchestration model, resulting in significant improvements in operational efficiency and productivity.

    Background

    Capita operates in the service industry, supporting millions of citizens and customers through various operations, including transport, healthcare, and local government services. With over 40 years of experience, the company manages complex services, such as processing 20 million NHS eyesight service claims annually and collecting £1.5 billion in council tax. Before deploying AI, Capita recognized the need to establish governance and orchestration to manage their AI tools effectively.

    Challenge

    The primary challenge Capita aimed to solve was the lack of clear governance and visibility over their expanding AI estate. As they adopted more AI agents, issues such as unclear ownership, duplicated efforts, and difficulty in assessing risk and value emerged.

    Solution

    Capita developed a comprehensive governance framework that included the ability to discover, catalogue, and govern AI agents across multiple platforms. They utilized MuleSoft Agent Fabric as their enterprise control plane to maintain a central registry of agents, ensuring consistent governance and security. Additionally, they established the Forward Deployed Orchestrator™ model, embedding AI expertise within operational teams to enhance service delivery and ensure ongoing value from AI systems.

    Results

    The implementation of these governance and orchestration strategies led to a 25% increase in operational capacity and 30-40% reductions in case management costs. In their recruitment operations, Capita saved over 1,000 management and recruitment hours within four months and reduced candidate screening time by 43%. Furthermore, they achieved an 88% faster dispute resolution rate.

    Key Insights

    1. Visibility is crucial for effective governance of AI systems.
    2. Governance can accelerate innovation by reducing duplication and enhancing collaboration.
    3. Orchestration is essential for coordinating AI agents within operational processes, requiring both technical and process expertise.

    Customer Testimonial

    No direct quote is available from the source material.

    Entities Mentioned

    Companies

    Capita

    Products

    Copilot
    Agent Assist

    Technologies

    MuleSoft
    Agentic AI
    Forward Deployed Orchestrator

    People

    Tiina Stephens

    Organizations

    Transport for London
    NHS

    Key Concepts

    Governance of AI
    Visibility in AI management
    Orchestration of AI agents
    AI adoption challenges
    Operationalizing AI
    Trust and accountability in AI
    Innovation through governance
    AI capability evolution

    Definitions

    Agentic AI
    A type of AI that operates autonomously to perform tasks and make decisions within defined parameters.
    Orchestration
    The coordination of agents, systems, data, and people within operational processes to ensure effective service delivery.
    Governance
    The framework of policies and controls that guide the management and oversight of AI systems.
    MuleSoft
    A technology platform that enables organizations to connect applications, data, and devices through APIs.
    Forward Deployed Orchestrator
    A model that embeds AI expertise within operational teams to enhance service delivery and value from AI.

    Use Cases

    • Processing NHS eyesight service claims
    • Collecting council tax for local authorities
    • Enhancing customer experiences with Agent Assist
    • Reducing candidate screening time in recruitment
    • Improving operational capacity in case management
    • Scaling AI adoption across multiple teams

    Frequently Asked Questions

    What is the importance of governance in AI?

    Governance is crucial for ensuring that AI systems are managed effectively and can be trusted. It helps establish clear ownership, reduces duplication of efforts, and ensures compliance with regulations.

    How can organizations achieve visibility in their AI systems?

    Organizations can achieve visibility by developing frameworks to discover and catalog AI agents across platforms. This includes maintaining a central registry and applying consistent governance controls.

    What role does orchestration play in AI deployment?

    Orchestration is essential for coordinating the interactions between agents, systems, and people. It ensures that AI operates effectively within live processes and enhances overall service delivery.

    What are the benefits of using Agentic AI?

    Agentic AI can significantly improve efficiency by automating tasks, enhancing customer experiences, and reducing operational costs. It allows organizations to scale their capabilities while maintaining governance.

    How does Capita support AI adoption?

    Capita supports AI adoption by providing governance frameworks, operational expertise, and innovative solutions like Copilot and Agent Assist. Their approach focuses on embedding accountability and transparency from the start.

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