Pioneering AI-driven ITSM: Our Hornbill AI Lab

Martin Stewart - Jun 27, 2024

The infusion of AI into Hornbill Service Manager is an opportunity for us to deliver game-changing value to customers by automating a broad range of currently manual tasks. Our Hornbill AI Lab is a dedicated team of AI experts, using specialist infrastructure to create next-generation service management solutions.

At Hornbill, we’re all about making life at work better for the people who manage and deliver services and support to customers and employees. AI-driven tech is a new way we are doing that.

AI is a core part of Hornbill Service Manager

The goal of our AI Lab team is to infuse AI into every area of the Hornbill product to save you time and make life easier. AI is now a core part of the Hornbill Service Manager cloud solution, and we’re committed to developing broad and deep AI technology across 4 key areas:

Agent efficiency: Tools that augment human capabilities and fully automate common routine tasks that agents have currently have to do every day.
Agent deflection: Empowering service consumers with more and better alternatives to calling the service desk for one-to-one support.
Intelligent automation: Complementing existing workflow-based automations to achieve more widespread end-to-end service automation scenarios—lifting more workload off human agents and allowing instant delivery for customers.
Service experience: Enhancing digital service experiences by infusing AI into the end user experience. This includes a virtual agent that can cover the routine service delivery work, support queries, resolutions, and information request tasks normally covered by people.

Focused on customer value

The number of potential scenarios where AI can either assist people or completely automate tasks is huge. To focus effort on where AI can help our customers the most, we evaluate and prioritize AI opportunities from two perspectives:

Value at scale: Where can AI deliver value by handling the high-volume tasks that many people work on every day? Where can AI be inserted into routine transactions to save time and accelerate the delivery of value to service consumers?
Complexity: What is the “low hanging fruit”? Which features can we ship to customers most quickly? Which of these will be quick and easy for customers to implement? How can we reduce complexity to assist customer adoption?

For us, the AI Lab is where customer challenges meet practical AI-driven solutions. We take a pragmatic approach: experiment, test solutions against the problem, and then validate innovations through our AI Beta group.

Focused on simplicity

Like any other tech, AI must be easy to use, or people won’t use it. If you build something that’s too complex to use, it delivers no value. This is why everything our AI Lab does is designed from both a functional and a usability/adoptability perspective.

Wherever complexity of implementation may become a potential barrier to adoption, we complement the functional technology by working to make it easy for our customers to adopt. For example, for our ML-driven features (those that use the customer’s service management data as a training feed) we’ve developed specialized data analysis tools to automatically evaluate readiness and pinpoint where data must be prepared before use.

100% dedicated AI team

Formed last year, our AI Lab team is distinct from our main development team. It is 100% focused on building new AI-powered functionality - with no technical debt, refactoring, bug fixes, or patches to distract from innovation. The AI Lab team's mission is to inject AI power into every aspect of Hornbill to transform service experiences and service operations. Working closely with the platform, application, and integration teams, the AI Lab team develops new AI-powered functionality that is rigorously tested, integration-tested with Service Manager, and then folded into the main Hornbill Service Manager code stream for release to customers.

Specialist AI development infrastructure

Our expert AI team have created a purpose-built AI infrastructure with specialized processing, container management, and storage capabilities to enable rapid prototyping of new ML models.

This is complemented by a sophisticated set of tools to manage every aspect of the AI Labs infrastructure efficiently: machine learning, the supporting technology stack, security, and the flow of features through the development, training, test, and deployment pipeline.