How Generative AI improves operations in Service integration and Management (SIAM) in multivendor IT environments

Generative AI is everywhere, but how does it actually improve service management in organisations that operate in complex, multi-vendor environments? In this article, I will explore practical use cases that are already delivering real business value and tangible benefits for businesses.

Why use GenAI in SIAM?

Service integration and management (SIAM) has traditionally involved a significant amount of manual work: handling incidents, processing change requests, managing operations, and digging through outdated manuals, not to mention the jungle that operating in a multivendor environment is.

Operational processes, operations and roles handle repetitive tasks that have already been resolved elsewhere or reported multiple times, but there is no consistent model for preventing these issues from reoccurring. Information isn’t up-to-date and the tools for searching for it, or ways to utilise it, have been limited and often require manual labour. All this continues to eat up valuable time.

Up until now the highest level of automation has been tracking events on various network devices and servers, bundling similar tickets according to categorisation, and utilising integrations for transferring information between systems, or even replacing humans with robotic process automation (RPA) in repetitive tasks in the processes. Even though some of these aspects have been improved by automation, it is the arrival of Generative AI that is now transforming how we plan, execute, and manage services.

The one thing behind this shift in processes and the transformation we are talking about is the use of AI Agents. Technology platforms such as OpenAI, Microsoft, and ServiceNow have integrated AI Agents into their backbone, which enables companies to take significant steps toward increased productivity and improvement in Service management.

At Sofigate, we’ve seen how GenAI-powered tools like our BT Standard Assistant Otso, AI-powered service integration agents, and other no-code AI solutions are simplifying service operations. These agents are easy to deploy, they don’t require programming skills, and they can be tailored with little guidance.

An AI agent can for example:

accurately answer questions based on specific content
guide and assist in a specific matter in a recommended way
write functional application code
break down large tasks into manageable phases
build an entire control diagram
phase the implementation of a large or small entity or process
provide a workload estimate for implementation phases

What are the practical use cases of GenAI in service management?

One of the most frequently asked questions, and the hot topic of service management that everyone is thinking about is the practical implementation of Gen AI. It’s easy to say that AI will diminish workload and improve productivity, without presenting any practical examples. So where does the real value of Gen AI lay?

Luckily, we have several practical examples of how Gen AI can be used with tangible results.

Designing operating models: Otso provides guidance for creating operating models, processes and roles for an organisation’s operating environment based on best practices and models (BTS, ITIL, SAFe, DevOps).
Proactive incident management: AI analyses performance data, suggests fixes, books resources, and drafts customer comms, sometimes even predicting when a service failure might happen.
Incident resolution: AI automatically diagnoses and routes tickets, proposes solutions, creates resolution plans, and generates post-incident summaries.
Change management: After an incident, AI helps plan changes, run test scenarios, and estimate impact on the operating environment.
AI orchestration: All the above-mentioned tasks can be distributed across multiple AI agents, all coordinated through a central orchestrator.

Get started with what you have

The tools needed for this transformation often already exist in organisations. Platforms, such as the above-mentioned Microsoft Copilot, ChatGPT, ServiceNow’s GenAI features, and free tools like Otso, are already widely in use. It’s therefore fairly easy to get started without a huge new investment.

A more practical approach to the first steps of starting has been discussed in my colleague Hanna Vannesluoma’s blog: Generative AI for SMEs: Why the time to act is today.

The benefits for organisations are significant, as is easy to see from these figures:

80% improvement in task automation and self-service
99% customer satisfaction (up from 80%)
600 knowledge articles created using Now Assist
89 agent hours saved per month with summarisation tools
Up to 10 minutes saved per request, with 83% of calls deflected
50% faster incident resolution time

Start your AI journey today

The best way to start improving your Service Integration and Management (SIAM) is by assessing the maturity of your multi-vendor ecosystem: operating model, processes, roles, and responsibilities. Then all that is left to do is to choose a process that needs improving and get to it!

What is the most critical success factor? Involving the right people: the ones who are familiar with your operations and data, who understand the big picture.

With the right tools, data, people, and mindset, you can turn GenAI into a real productivity driver.

Let’s make it happen. Together.