SB
Spandana Bala
ServiceNow Developer
Hyderabad · India
Now at · Infosys
ServiceNow · CSA-aligned · Enrolling now
ServiceNow AI Platform Admin
A career-focused, hands-on program: start with platform and ITSM foundations, progress through data, security, automation, CMDB and analytics, then configure, deploy and govern Now Assist and AI agents on the ServiceNow AI Platform.
100K+
alumni community
1,000+
hiring partners
4.8/5
avg class rating
12
partner centres
7
Digital Edify centres
Where our ServiceNow alumni work
Microsoft
Amazon
Salesforce
ServiceNow
Deloitte
Infosys
Accenture
TCS
Wipro
Capgemini
Cognizant
HCL
MicrosoftAmazonSalesforceServiceNowDeloitteInfosysAccentureTCSWiproCapgeminiCognizantHCL
Direct answer
What is a ServiceNow AI Platform Admin?
A ServiceNow AI Platform Admin configures, secures, and operates the Now Platform so AI-powered workflows run reliably in production. Most admin courses end at tables, forms, and update sets. This program ends only when your instance runs governed AI agents — built in AI Agent Studio, monitored, and connected to a measurable business outcome.
The complete platform chain
Twelve links, one owner — end to end.
01CONFIGURE
- •Tables & data model
- •Forms & lists
- •Security & ACLs
- •Update sets
02AUTOMATE
- •Flow Designer
- •Business rules
- •Integrations
- •AI Agent Studio
03OPERATE
- •Monitoring & analytics
- •Release & upgrades
- •Adoption
- •Value
The ownership model
An AI Platform Admin does not personally build every workflow at the same depth.
They know enough across the whole platform to configure, challenge and connect specialist work — and go deep in at least one verified anchor module.
What the admin owns
- •Keeping the instance secure, governed, and upgrade-safe
- •Establishing update sets and gates at every release seam
- •Ensuring AI agents behave safely from pilot through production
- •Escalating the moment risk exceeds authority
And remaining accountable for the integrity of the platform outcome.
Who should join
Built for people moving into AI platform work.
Beginners entering ServiceNow
ServiceNow & system admins
ITSM & service desk analysts
Platform & product owners
Business analysts
Developers adding governance skills
Prior experience: none required. JavaScript appears only where it supports admin-level configuration, security or troubleshooting.
What you will be able to do
Administer the platform — and operate its AI safely.
Administer the platformInstances, tables, forms and data — run on standard platform practices.
Secure every workflowUsers, groups, roles and ACLs designed on least privilege.
Run AI-assisted ITSMIncident, problem, change and knowledge — with CMDB and CSDM context.
Automate with controlFlows, approvals and reusable automation you can troubleshoot.
Operate Now Assist & AI agentsSkills in AI Admin Hub and Skill Kit; agents, tools and triggers in AI Agent Studio.
Govern AI in productionGuardrails, human approvals, AI Control Tower and safe promotion to production.
Course curriculum
ServiceNow AI Platform
01ServiceNow and the AI PlatformBuild a clear mental model of ServiceNow as an enterprise platform for AI, data and workflows.8 TOPICSLAB+
ServiceNow platform purpose, architecture and product ecosystem
Instances, environments, applications, modules and records
From workflow platform to AI platform
Predictive AI, generative AI and agentic AI in simple terms
Now Assist, AI agents, AI Admin Hub, AI Agent Studio and AI Control Tower
Administrator, developer, platform owner, AI steward and process-owner responsibilities
Shared responsibility across platform, security, data, risk and business teams
Personal Developer Instance and lab-environment orientation
LABCreate an instance orientation map and identify the administrative surfaces used throughout the program.
02User Interface, Navigation and Admin ProductivityLearn to work confidently with the platform interface before performing advanced administration.8 TOPICSLAB+
Next Experience navigation and administrator workspaces
Application navigator, menus, modules and favorites
Lists, forms, related lists, filters and breadcrumbs
Search, condition builder and encoded-query awareness
Personalization versus system-wide configuration
Form and list configuration, views and basic branding
Plugins, applications, licensing awareness and feature availability
Safe exploration and documentation of configuration changes
LABConfigure an administrator-focused incident list and form view without disrupting other personas.
03Data and Database Fundamentals for AI-Ready AdministrationUnderstand how ServiceNow stores, relates, secures and exposes the data used by workflows and AI.9 TOPICSLAB+
Tables, records, fields, dictionaries and schema maps
Task-table inheritance and extending platform tables
Reference fields, relationships, dot walking and data integrity
Custom tables and scoped application data
Import Sets, Transform Maps and data-quality controls
Structured versus unstructured data
AI grounding, retrieval and the importance of trustworthy source data
Data classification, ownership, retention and sensitive-field awareness
Introduction to Workflow Data Fabric and governed enterprise context
LABBuild a small data-readiness assessment and remediate duplicate, incomplete and poorly classified records.
04Users, Groups, Roles and Access ControlsDesign secure access for people, applications, skills and AI agents.9 TOPICSLAB+
User lifecycle and administrator responsibilities
Group-based role assignment and delegated administration
Role inheritance and separation of duties
ACL anatomy: table, field, create, read, write, delete and execute
Conditions, scripts, debugging and impersonation-based testing
Least privilege and protection of sensitive enterprise data
AI-specific access concepts: invocation access, user identities and role masking
Controlling what an agentic workflow, agent or tool can access and perform
Privileged-role governance for AI administration and skill development
LABSecure an AI-assisted incident scenario using group roles, field ACLs and controlled impersonation tests.
05Platform Configuration, Customization and Scripting EssentialsDevelop the technical fluency needed to configure and troubleshoot an AI-enabled instance.9 TOPICSLAB+
Configuration versus customization
Fields, choice lists, views, related lists and form design
UI Policies, Data Policies and Client Scripts
Business Rules, Script Includes and GlideRecord awareness
System properties, events, notifications and scheduled jobs
Update Sets, application scope and configuration traceability
Choosing declarative configuration before scripting
Upgrade-safe design, technical debt and maintainability
Where scripts may be exposed as controlled tools for AI agents
LABConfigure validation, routing and notification behavior for a service request, then test expected and exception paths.
06ITIL Foundations and Service Management ThinkingLearn the service-management principles that keep automation and AI focused on business value.7 TOPICSACTIVITY+
ITIL 4 Service Value System and Service Value Chain
Guiding principles and continual improvement
Four dimensions of service management
Key practices and ServiceNow process alignment
Value streams, outcomes, risks, controls and metrics
Human accountability in automated and AI-supported processes
Selecting use cases that improve services rather than add novelty
ACTIVITYEvaluate an AI use case using value, feasibility, data readiness, risk and human-oversight criteria.
07ITSM Administration and AI-Assisted Service OperationsConnect platform administration with the service processes where Now Assist and AI agents create day-to-day value.8 TOPICSLAB+
ITSM architecture and core applications
Incident lifecycle, categorization, priority and assignment
Service requests, catalog items, approvals and fulfilment
SLAs, notifications, escalations and service-desk experience
AI-assisted summarization, resolution-note generation and reply recommendations
AI Search, self-service and virtual-agent experiences
Measuring deflection, handling time, resolution quality and user experience
Preventing automation from bypassing ownership and escalation controls
LABConfigure and test an AI-assisted incident journey from intake through resolution and closure.
08CMDB, CSDM and Context for Enterprise AIBuild the service and configuration context required for better operational decisions and grounded AI responses.8 TOPICSLAB+
Configuration Items, classes, attributes and relationships
CMDB Health, completeness, correctness and compliance
Business services, service offerings, application services and infrastructure
CSDM domains and practical adoption principles
Relating incidents, problems and changes to affected services and CIs
Using service context to improve AI routing, impact analysis and recommendations
Ownership, attestation, reconciliation and data stewardship
Common CMDB mistakes that weaken AI outcomes
LABModel a business service and trace how a failing CI influences an AI-supported incident and change decision.
09Incident and Request AdministrationConfigure high-volume operational processes that provide strong foundations for AI adoption.7 TOPICSLAB+
Intake channels and standardized data capture
Assignment rules, lookup rules and decision logic
Priority, impact, urgency and major-incident controls
Catalog item variables, approvals and fulfilment tasks
Knowledge suggestions and self-service enablement
Human approval points for high-impact AI actions
Test cases for normal, exception, unauthorized and low-confidence outcomes
LABBuild a controlled fulfilment flow in which AI recommends an action but a human approves privileged execution.
10Problem Management and AI-Assisted Root-Cause WorkUse platform data and AI assistance to identify patterns while preserving analyst judgment.7 TOPICSLAB+
Reactive and proactive problem detection
Problem, problem task, known error and workaround records
Incident clustering and trend analysis concepts
Root-cause investigation, evidence and hypothesis validation
Knowledge and change relationships
Appropriate and inappropriate uses of generative output in diagnosis
Quality checks for AI-generated investigation summaries
LABAnalyze recurring incidents, create a problem record, document a validated workaround and initiate a controlled change.
11Change Enablement, Risk and Human ApprovalAdminister change workflows that balance velocity, reliability and AI-enabled recommendations.7 TOPICSLAB+
Standard, normal and emergency change models
States, transitions, approvals and Change Advisory Board processes
Risk, conflict and schedule assessment
Unauthorized-change controls and post-implementation review
AI-generated summaries, plans and risk recommendations
Mandatory human review for high-impact or irreversible actions
Auditability and evidence retention for AI-assisted decisions
LABConfigure a change model with risk-based approvals and test an AI recommendation against an administrator-defined control checklist.
12Knowledge, AI Search and Grounding ReadinessPrepare trusted knowledge so Now Assist, search experiences and AI agents can produce more useful results.8 TOPICSLAB+
Knowledge bases, categories, roles and ownership
Article authoring, templates, review, approval and retirement
User Criteria and controlled knowledge access
Findability, titles, metadata, feedback and article quality
Knowledge readiness for generative AI and retrieval
Preventing inaccessible or sensitive knowledge from leaking into responses
Content freshness, conflicting answers and source traceability
Knowledge gaps identified through unsuccessful searches and conversations
LABBuild a governed knowledge base, publish an article through review and test retrieval with authorized and unauthorized personas.
13Integrations and Workflow Data Fabric FoundationsConnect internal and external context without losing governance or operational control.8 TOPICSLAB+
REST, SOAP, webhooks and Integration Hub concepts
Connections, credentials, spokes and reusable actions
Import, synchronization and error-handling patterns
Workflow Data Fabric: connected, contextualized and governed data
Structured and unstructured enterprise sources
Zero-copy concepts and when data should remain in its source system
Data provenance, access, quality and freshness for AI consumption
Introduction to governed tool access through Action Fabric, MCP and agent-to-agent patterns
LABDesign a secure integration and context map for an AI agent that needs ServiceNow and external-system information.
14Flow Designer and Intelligent AutomationMove from deterministic automation to controlled agentic execution.8 TOPICSLAB+
Triggers, actions, data pills, conditions and flow logic
Subflows, custom actions, approvals, notifications and error handling
Reusable components and operational logging
Deterministic, probabilistic and hybrid workflow patterns
Deciding whether to use a rule, flow, Now Assist skill or AI agent
Exposing approved flows and actions as tools
Human-in-the-loop and human-on-the-loop controls
Rollback, idempotency and prevention of repeated execution
LABBuild a hybrid workflow that uses deterministic validation, AI-assisted interpretation and a controlled fulfilment action.
15Reporting, Analytics and AI Value MeasurementCreate visibility into service operations, platform health and AI adoption.9 TOPICSLAB+
Reports, dashboards and Performance Analytics concepts
Indicators, breakdowns, targets and scheduled collection
Data quality and misleading-metric risks
Operational AI measures: adoption, completion, fallback, escalation and exception rates
Quality measures: groundedness, correctness, relevance and user feedback
Risk measures: blocked content, unauthorized attempts and policy exceptions
Consumption and value measures
Generative AI Controller usage and activity awareness
Executive, admin, service-owner and governance views
LABCreate an AI operations dashboard and write an evidence-based monthly service review.
16Now Assist and AI Admin HubActivate, configure and support generative AI capabilities on the ServiceNow AI Platform.9 TOPICSLAB+
Now Assist architecture, subscriptions, eligible applications and skills
AI Admin Hub navigation, account information and readiness views
Installing, activating, editing and archiving skills
Skill configuration for common ITSM use cases
Default and target model awareness
User data usage policies, domain considerations and privacy
Usage analysis and administrator troubleshooting
Diagnosing unavailable, inactive, poorly configured or low-quality skills
Deployment channels including Now Assist panel, context menu, Virtual Agent, flows and UI actions
LABActivate and configure a Now Assist skill, validate it with representative records and document a production-readiness decision.
17AI Skill Kit, AI Agent Studio and Agentic WorkflowsConfigure reusable AI skills and autonomous workflows within clear boundaries.12 TOPICSLAB+
Prompt anatomy: instructions, inputs, context, constraints and output format
Creating, cloning, testing, evaluating and publishing custom skills
Skill roles and separation between authoring, publishing and activation
AI agent, tool, trigger, agentic workflow and orchestrator concepts
Creating and configuring an agent in AI Agent Studio
Platform tools, AI actions, flows, scripts, knowledge and external tools
Multi-agent collaboration and handoffs
ACLs, user identity, role masking and approval design
AI Guardian and prompt-injection protection concepts
Test datasets, expected outcomes, negative testing and red-team scenarios
Operational safeguards, including prevention and stopping of runaway repeated triggers
Promotion, monitoring, feedback and retirement
LABBuild and test an AI agent that triages a recurring service issue, retrieves authorized knowledge, proposes an action and escalates privileged execution for human approval.
18AI Control Tower, Governance and Production OperationsManage AI as a governed enterprise capability rather than a collection of experiments.11 TOPICSLAB+
AI strategy, ownership and operating-model foundations
AI Control Tower purpose, personas and navigation
AI asset inventory: systems, models, datasets, prompts, skills, agents and workflows
Asset owners, AI stewards and lifecycle states
Risk classification, controls, approvals and evidence
Regulatory and organizational policy alignment
ServiceNow and third-party AI asset visibility concepts
Usage, performance, value and compliance monitoring
Incident response for unsafe, incorrect or runaway AI behavior
Change control, versioning, rollback and decommissioning
Multi-instance promotion strategy and operational handover
LABRegister and assess an AI use case, map its assets and dependencies, assign ownership, define controls, and conduct a go-live governance review.
Want this as a document? Get the full module-by-module syllabus with lab descriptions.
Capstone project
Autonomous IT Service Operations — from idea to governed go-live.
The business challenge
A fictional enterprise receives a high volume of repetitive incidents. Knowledge is fragmented, routing is inconsistent, resolution notes vary in quality and privileged fulfilment actions require strong control. Leadership wants better service speed without compromising data security, auditability or human accountability.
Your role
You act as the ServiceNow AI Platform Administrator responsible for platform readiness, configuration, security, testing, governance and operational handover.
Acceptance criteria
- •Users can access only the records and functions appropriate to their roles
- •AI outputs reference approved context and remain within the defined use case
- •Privileged or high-impact actions require explicit control or approval
- •Failures, low-confidence outcomes and prohibited requests follow safe fallback paths
- •Administrators can trace actions, review usage and stop unsafe behavior
- •The solution includes measurable service, quality, risk and adoption outcomes
Twelve required deliverables
01Current-state problem and stakeholder summary
02AI use-case assessment and success measures
03Data, knowledge, CMDB and application-readiness checklist
04User, group, role and ACL design
05Deterministic workflow with exception handling
06Now Assist skill configuration or documented simulation
07AI agent and agentic-workflow design
08Human-approval and escalation controls
09Functional, security, negative and quality test evidence
10AI asset inventory and governance record
11Operations dashboard and support runbook
12Go-live, rollback and continual-improvement plan
Tools you'll master
The ServiceNow AI Platform stack, end to end.
Product access depends on the applications, plugins, subscriptions and roles available in the training environment. Where a licensed enterprise capability is unavailable, learners use instructor demonstrations, design simulations and evidence-based configuration exercises.
Hands-on labs & portfolio evidence
You don't watch videos. You leave with workplace evidence.
Every module ends in a lab, and every lab produces an artifact you can show an employer — eleven capabilities, eleven pieces of proof.
Platform administration
Instance configuration workbook and change log
Security
Role matrix, ACL test evidence and least-privilege review
Data readiness
Data-quality and AI-readiness assessment
ITSM
Configured incident / problem / change / knowledge scenario
CMDB / CSDM
Service and CI relationship model
Automation
Flow with approvals, error handling and audit trail
Now Assist
Skill activation and validation report
Custom AI skill
Prompt, test set, evaluation and release decision
Agentic AI
Agent, tool and workflow design with guardrails
Governance
AI asset inventory, risk assessment and control mapping
Operations
Dashboard, support runbook and improvement backlog
Your instructor
Taught by engineers who shipped agentic AI to production.
MK
Manikanta Kona
Founder, Digital Edify · Enterprise AI Architect
ServiceNow · Now Assist · AI Agent Studio · ITSM / ITOM / HRSD / CSM
"ServiceNow at enterprise scale is where AI agents earn their keep — Now Assist plugged into the Service Desk, AI Agent Studio orchestrating ITSM, ITOM, HRSD, and CSM as one fabric. That's the bar I teach to, every class."
15 yrs
SERVICENOW
2,400+
LEARNERS
4.8 /5
RATING
Manikanta is the founder of Digital Edify and brings 15 years of enterprise platform architecture from AT&T, Salesforce, Cox Communications, and Broadcom — where he led ITSM, ITOM, HRSD, and CSM rollouts for Fortune-500 banks, telcos, and insurers. Most recently he architected production Now Assist + AI Agent Studio deployments that replaced traditional triage tiers with autonomous case-handling.
His classes get you two things other programs don't give you: a founding architect who's shipped enterprise ServiceNow + AI from inside the Fortune 500, and a curriculum rewritten every release (currently Zurich) — so when hiring managers ask about CMDB Workspaces, AI Agent Studio sub-flows, or ITOM Visibility, you've already built it. M.S. in Engineering, Purdue University.
RK
Ravi Krishna
Chief Technologist, Digital Edify · ITOM Lead
ITOM · AIOps · CMDB · Discovery · Event Management · MID Server · DevOps
"ITOM is where ServiceNow stops being a ticket tool and starts being the nervous
system of the enterprise — Discovery feeding a CMDB you actually trust, Event Management that's quiet
on purpose, and AIOps + Now Assist resolving incidents before on-call gets paged. That's what I teach."
10 yrs
ITOM & OPS
1,800+
LEARNERS
4.8 /5
RATING
Ravi is Chief Technologist at Digital Edify, where he leads the ITOM and operations-engineering practice. After 8 years building and running production DevOps pipelines, he stepped into the Chief Technologist seat to wire AIOps, Now Assist, and Discovery into the way operations teams actually work — CMDB that stays accurate through change windows, Event Management that filters noise before it hits humans, and Service Operations Workspace that on-call engineers don't fight with.
His ITOM modules are built from real outage post-mortems, not slide decks. Expect to leave with working Discovery patterns, Event Management rule packs, MID Server topology, and a CMDB you can stake an SLA on. Ten years at Digital Edify, eight of them shipping DevOps in production — Hyderabad-based, hands-on, and known for the unglamorous parts of ServiceNow that everyone else skips.
HIRING PARTNERS · INDUSTRY VOICES
What ServiceNow employers say about Digital Edify grads.
Real feedback from talent leaders at ServiceNow Elite Partners and the firms hiring our ServiceNow + AI Agents graduates.
Digital Edify grads ramp 40% faster on Now Assist projects than typical hires. Best ServiceNow training pipeline in India.
Aakash Mehta, Partner Programme Lead, ServiceNow
We've onboarded 80+ Digital Edify alumni in 18 months. Lowest ramp time we've seen for ServiceNow plus AI agent practices.
Anita Sharma, Senior Manager, Deloitte
The ServiceNow programme is comprehensive — admin, developer, plus AI agent flows. Grads come pre-trained for enterprise.
Rahul Bhatt, Solutions Lead, Mphasis
Their ITSM + Now Assist track produces engineers who write production-grade Flow Designer flows on day one. Genuinely rare.
Deepak Pillai, Senior Architect, TCS
What sets Digital Edify apart is the AI Agent Studio layer baked into the ServiceNow track. Our enterprise clients ask for exactly this profile.
Suresh Menon, Practice Lead, Accenture
Their CSA + CAD prep is rigorous, and the project deployment on a real PDI is what closes interviews for us.
Vikram Iyer, Director, Infosys
Digital Edify's ServiceNow grads close incidents twice as fast in the first 90 days. Our internal metrics back this up clearly.
Lakshmi Nair, VP Engineering, Wipro
Best ServiceNow + AI Agents pipeline we've sourced from in India. Their projects are production work, not toy code.
Karthik Subramanian, Engineering Director, Cognizant
Strong HRSD and Employee Center foundation. Their ServiceNow grads need almost zero ramp time on enterprise engagements with us.
Arun Joshi, Practice Director, Capgemini
We've placed 40+ Digital Edify alumni across our ServiceNow and watsonx-on-Now teams. Strong fundamentals, sharp on the agent stack.
Sanjay Verma, Talent Director, IBM
ITOM + Predictive Intelligence is exactly the talent gap we've been struggling to close. Digital Edify is filling it for us reliably.
Anjali Desai, Practice Head, LTIMindtree
Their ServiceNow track delivers consultants who navigate ITSM, IntegrationHub, and Flow Designer on customer engagements unsupervised.
Ramesh Iyer, Senior Manager, Tech Mahindra
Hired 25+ Digital Edify graduates for our ServiceNow practice. Strong scripting, strong platform depth, sharp on the agent layer.
Geetha Pillai, Talent Acquisition Lead, Cyient
Digital Edify grads who blend Now Assist with Azure OpenAI land production-ready on day one. Rare combination, well-trained.
Priya Reddy, Talent Lead, Microsoft
Program certifications
An Agent‑Ready credential, not a participation trophy.
Digital Edify · Institute Certificate
Agent‑Ready ServiceNow Engineer
Presented to
Spandana Bala
For the successful design, build, and production deployment of an AI agent on the
ServiceNow Now Assist + AI Agent Studio platform, evaluated against the 2026 Agent‑Ready rubric and
CSA / CAD competencies.
Manikanta Kona
CEO · Digital Edify
AGENT
READY
2026
READY
2026
01
Industry‑recognized
Co‑branded with the ServiceNow Elite Partner ecosystem and mapped to CSA, CAD and CIS —
names that hiring managers already scan for on resumes.
02
Project artifact included
Every certificate carries your project project name, the partner org, and a link to the
deployed Now Assist + AI Agent Studio artifact — proof, not a promise.
03
Enhanced skill validation
Graded against the 2026 Agent‑Ready rubric: ITSM design, Flow Designer build, Now Assist
deployment, safety and monitoring. No pass/fail — a level 1‑5 band.
04
Verifiable on a public URL
Each credential has a public verification page recruiters can check in 10 seconds — no PDF
back‑and‑forth.
Why learn with Digital Edify
Platform depth and AI depth, in one program.
Beginner-first structurePlatform fundamentals come before advanced AI administration.
Role-based curriculumEvery module connects to observable administrator responsibilities.
Hands-on learningLearners configure, test, troubleshoot and document — not merely watch demonstrations.
AI plus platform depthNow Assist and AI agents connected with security, data, CMDB, ITSM and automation.
Governance by designRisk, privacy, access, human approval and operational controls are embedded throughout.
Portfolio-focused outcomesLabs and the capstone produce evidence you can discuss in interviews and project reviews.
Job roles
Roles this program prepares you for.
ServiceNow Platform Administrator
Own instance configuration, access, data quality and upgrade-safe changes.
ServiceNow AI Platform Administrator
Run Now Assist, AI agents and governance across the AI Platform.
Now Assist Administrator
Activate, configure and troubleshoot generative AI skills in AI Admin Hub.
ServiceNow AI Operations Analyst
Monitor AI usage, quality, risk and consumption; keep agents behaving safely.
ServiceNow ITSM Administrator
Administer incident, problem, change, request and knowledge processes.
AI Governance / Control Tower Analyst
Inventory AI assets, classify risk and manage lifecycle and compliance.
Platform Support Analyst
Support users, triage platform issues and maintain operational health.
Junior ServiceNow Consultant
Translate requirements into governed platform and AI configuration.
Platform Product Analyst
Connect platform capability to service outcomes and adoption.
AI Enablement Specialist
Help teams adopt AI features with training, guardrails and evidence.
What employers should see in your portfolio: that you can take a use case from idea to governed operations — assess readiness, configure the platform, protect data, test normal and unsafe scenarios, measure outcomes, document support procedures and communicate trade-offs.
Job placement support
Your first ServiceNow offer isn't a lottery ticket. It's a built process.
GitHub, LinkedIn, resume — and most importantly, warm intros into ServiceNow Elite Partners. Our
placement team works your search like an account, not a helpdesk.
01 / GITHUB PROFILE
A portfolio, not a graveyard.
Guidance on building a GitHub that showcases your Update Sets, Now Assist + AI Agent Studio project, Flow Designer flows, and a working PDI link — reviewed 1:1, not via template.
02 / RESUME PREP
Rewrite, don't proofread.
A one-page resume rebuilt around the ServiceNow modules you implemented (ITSM, HRSD, ITOM), the agent you deployed, and the business outcome. Reviewed by engineers who've read 10,000+ resumes.
03 / LINKEDIN + INTROS
Where most opportunities actually live.
Profile tuning plus direct warm introductions into the ServiceNow Elite Partner network — Infosys, TCS, Deloitte, Accenture, Cognizant, NTT Data, Capgemini. You leave with recruiter contacts, not a generic "good luck."
ServiceNow alumni
Hundreds of ServiceNow careers launched — here are eight.
NV
Naveen Vedala
ITSM Consultant
Hyderabad · India
Now at · TCS
TA
Tejashwini Addla
HRSD Specialist
Hyderabad · India
Now at · Deloitte
TD
Tharunesh Dillikar
ServiceNow Architect
Seattle · United States
Now at · ServiceNow
MM
Mujahed Mohammed
Lead ServiceNow Engineer
Hyderabad · India
Now at · Accenture
BK
Bhargav Kumar Murala
Now Assist Developer
Hyderabad · India
Now at · Capgemini
SL
Sai Manasa Leburi
ITOM Engineer
New York · United States
Now at · NTT Data
RD
Rahul Dhamma
AI Agent Studio Engineer
Hyderabad · India
Now at · Cognizant
Our locations
Come chat with us — over coffee, or over Zoom.
One flagship campus in Hyderabad, plus online ServiceNow classes running on Indian and US timezones.
Flagship campus
Hyderabad
2nd Floor, Hitech City Road · Above Domino's · Opp. Cyber Towers, Jai Hind Enclave ·
Hyderabad, Telangana
Call
+91 8142998866
US desk
+1 256 388 7766
Hours
Mon–Sun · 7 AM–9 PM
Online class
Global
Weekend and evening ServiceNow classes running on IST and PST. Every online class ships
the same three production projects and Now Assist + AI Agent Studio project as the on‑campus track.
Timezones
IST & PST
Format
Live + 1:1 mentorship
Admissions
ENROLLING NOW
FAQ
Questions we actually get — answered honestly.
Straight answers on prerequisites, the platform, certifications, and placement. If something's missing, book a 20-minute advisor call — no slides, no pitch.
What is a ServiceNow AI Platform Administrator?
A ServiceNow AI Platform Administrator manages the platform foundations and operational controls that allow enterprise AI capabilities to work safely. Responsibilities may include platform configuration, access, data and knowledge readiness, Now Assist skill activation, AI agent administration, monitoring, troubleshooting, governance and production support.
Is this course suitable for beginners?
Yes. The program begins with ServiceNow navigation, data, users, roles, security and ITSM foundations before introducing Now Assist, AI skills, agents and governance.
Do I need coding experience?
No. The course introduces only the scripting concepts needed to understand configuration, access, automation and troubleshooting. Most learning uses administrator and low-code capabilities.
Is this only a Now Assist course?
No. Now Assist is one important part of the program. Learners also study platform administration, ITSM, CMDB/CSDM, knowledge, Flow Designer, analytics, AI Agent Studio, AI Control Tower, Workflow Data Fabric concepts, security and production operations.
What is the difference between Now Assist and an AI agent?
Now Assist provides generative AI capabilities such as summarization, content generation and recommendations within ServiceNow experiences. AI agents can pursue goals through multiple steps, use approved tools and collaborate within an agentic workflow. In practice, agents may use Now Assist skills as part of their work.
What is AI Admin Hub?
AI Admin Hub is an administration experience used to review, activate, configure, analyze and troubleshoot eligible Now Assist skills and related settings.
What is AI Agent Studio?
AI Agent Studio is the ServiceNow experience for creating, configuring, testing and managing AI agents and agentic workflows, including their tools, triggers and access controls.
What is AI Control Tower?
AI Control Tower provides centralized visibility and governance across AI systems and assets. It helps organizations manage lifecycle, ownership, risk, compliance, performance and value across models, prompts, datasets, skills, agents and workflows.
Will I build an AI agent?
Yes. Subject to training-instance licensing, learners configure and test an agentic use case in AI Agent Studio. If a capability is not licensed in the learner instance, the same outcome is taught through instructor demonstrations and detailed design-and-testing simulations.
Does the course cover AI security?
Yes. Learners work with least privilege, ACLs, identities, role masking, human approvals, data protection, prompt-injection awareness, negative testing, logging, operational safeguards and incident response.
Still have a question? Talk to an advisor — no slides, no pitch.
One million AI‑native professionals by 2027.
Let's put you in that number.
Book a 20‑minute advisor call. We'll map your current role to the right program, talk honestly about timelines, and walk you through a real class's project.
