AI in ITSM & AIOps
capability building,
designed for your organisation.
A custom-built corporate programme for ITSM professionals, ServiceNow practitioners, IT operations engineers, SREs, change/incident/problem managers, IT operations leaders, and senior support engineers driving AI in IT operations. We design the curriculum around your tech stack, project archetypes, and target business outcomes — delivered by domain-expert trainers and reinforced through AI-evaluated assessments.
A modular syllabus, built to be tailored.
Below is our reference curriculum. Every syllabus we deliver is tailored to your customer-specific requirements — module depth, sequencing, lab environments, and capstone projects are adapted to your team's starting point, tech stack, and target outcomes.
- ITSM platform AI: ServiceNow Now Assist, BMC HelixGPT, Atlassian AI, Cherwell AI, Freshservice AI
- AIOps tools: Moogsoft, BigPanda, ScienceLogic, Resolve.ai, IBM Watson AIOps
- Observability AI: Datadog AI, New Relic AI, Splunk AI, Dynatrace Davis AI
- ITIL 4 alignment and the practices most affected by AI
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Demonstrable skills your team will apply on live projects.
Apply AI across the ITSM lifecycle
Incident, problem, change, request, knowledge, service catalog — with platform-specific patterns.
Implement AIOps in production
Event correlation, anomaly detection, automated remediation across the IT operations stack.
Build AI-augmented service desk
Virtual agents, knowledge generation, ticket triage and classification — production-grade.
Pass GSDC AI for ITSM certification
Two attempts; cohort first-attempt pass rate 88%.
Reduce MTTR by 25-40%
Documented MTTR reduction via AI-augmented investigation and runbook patterns.
Lead AIOps strategy in your IT organisation
Equipped to evaluate vendors, design pilots, and scale AIOps programmes.
Where your team is now vs where they'll be after the programme.
Where most teams start
- ·Aware ITSM platforms have AI features but unclear which deliver value vs. which are marketing veneer
- ·Limited fluency with platform AI: ServiceNow Now Assist, BMC HelixGPT, Atlassian AI, Splunk AI, Datadog AI
- ·Cannot evaluate AIOps tools (Moogsoft, BigPanda, ScienceLogic, Resolve.ai) on technical merit
- ·Generic ChatGPT use that doesn't translate to IT operations context
- ·No framework for AI in incident response, problem management, or change risk assessment
- ·Limited fluency with AI for service desk: virtual agents, knowledge generation, ticket triage
Where they'll arrive
- ✓Platform AI fluency across ServiceNow Now Assist, BMC HelixGPT, Atlassian AI, Splunk AI
- ✓AIOps tool evaluation — critical assessment of detection, correlation, automation tools
- ✓AI-augmented incident response — faster MTTR via AI investigation, runbook generation, knowledge surfacing
- ✓AI-augmented problem management — pattern detection, root-cause analysis assistance
- ✓Change risk assessment with AI — change impact prediction, blast-radius analysis
- ✓GSDC AI for ITSM certification — credential aligned to ITIL 4 and ISO/IEC 20000
Built for L&D outcomes, not seat counts.
Prompt discipline, not prompt luck
Learners move from trial-and-error prompting to named patterns such as role prompting, few-shot, prompt chaining, and self-critique.
Reusable team assets
The programme produces Custom GPTs, reusable workflow templates, and a shared prompt library that teams can govern and scale.
Daily productivity workflows
Labs focus on email, reports, slides, meetings, spreadsheets, research synthesis, and role-based business assignments.
Measured time savings
Capstone workflows document recurring task compression, review-cycle reduction, and before/after productivity improvements.
Responsible enterprise use
Learners practise confidentiality, IP, bias detection, verification checklists, and safe-use protocols before adoption at scale.
Sustainment built in
30-day, 60-day, and 90-day check-ins help learners keep pace as ChatGPT features and frontier models evolve.
A four-milestone path from skill gap to client-ready.
Foundation & baseline
Establish a working mental model of ChatGPT, frontier models, tokens, context windows, hallucination risks, and model-selection trade-offs.
Prompt engineering labs
Learners practise CRISPE, SPEAR, role prompting, constraint-led prompting, few-shot prompting, self-critique, and prompt iteration on real work scenarios.
Custom GPTs & workflow automation
Each learner builds reusable GPTs and connects ChatGPT to productivity tools for email, documents, spreadsheets, meetings, and research workflows.
Capstone & sustainment
Learners demonstrate a personal AI productivity system and continue with prompt-of-the-week, model-of-the-month, and 30/60/90-day check-ins.
Want this curriculum aligned to your tech stack and project archetypes?
Why enterprise teams choose the B2B engagement model.
Domain-expert trainers, not professional presenters.
"My job isn't to teach ChatGPT as a tool — it's to help professionals build repeatable AI workflows, verify the output, and reclaim hours from routine work."
Taught by people who've actually shipped the work.
Built for L&D leaders and their learners.
Who this is for
- ·Knowledge workers who want to apply ChatGPT productively in their daily workflows
- ·Business analysts, consultants, marketing professionals, project managers, and individual contributors
- ·Teams that use ChatGPT for occasional drafting but need reliable, business-grade outputs
- ·Managers looking to establish team-wide prompt standards and safe-use protocols
- ·Organisations that want to automate repetitive work across email, spreadsheets, calendars, and documents
Pre-requisites
- ·No coding prerequisite for business and productivity tracks
- ·Basic familiarity with workplace tools such as email, documents, spreadsheets, slides, and meetings
- ·Willingness to bring real recurring tasks into labs for workflow redesign
- ·Enterprise cohorts should align data-handling expectations before learners use company or client information
Trusted by L&D leaders across the world.
"The programme moved our team from random prompting to a repeatable method. The prompt library and Custom GPTs became assets we could actually reuse."
"The most useful part was workflow automation. Learners took their weekly reports, meeting recaps, and research tasks and reduced hours of repetitive effort."
"Responsible use was handled practically. The team finally understood what can be pasted, what must be masked, and how to verify output before sending it."
Questions L&D teams ask before signing.
No, AI will enhance and automate ITIL workflows like incident management, change management, and service requests, but governance, risk decisions, and service strategy still require human oversight.