AI Security and Risk Management Corporate Training
Identify, assess, and control the risks AI introduces across your models, pipelines, and products.
Edstellar, a corporate training company, delivers corporate training that helps your security and risk teams manage AI risk end to end. Employees threat-model AI systems, test adversarial robustness, design defense controls, and map them to governance needs. Every module pairs concepts with guided labs, so your team practices risk assessment on realistic AI pipelines and leaves ready to secure AI in production.
Instructor-led group trainingVirtual / on-site / off-site10 languagesDelivered inEnglish, Spanish, Mandarin, German, Arabic, Portuguese, Hindi, French, Japanese, Italian100+ countriesWe have delivered inUnited States, United Kingdom, India, Canada, Germany, France, Netherlands, UAE, Saudi Arabia, Singapore, Australia, Japan, Brazil, South Africa and 90+ more countries
How we build an AI risk-ready security team
EDSTELLAR CYBERSECURITY CAPABILITY MODEL
Assess AI risk exposure
Skill checks map your team's AI threat awareness, modeling fluency, and control maturity.
Set shared risk standards
One shared playbook for AI threat modeling, control design, and review.
Practice in guided labs
Labs cover threat modeling, adversarial testing, and governance controls.
Measure the lift
Lab reviews benchmark each analyst's AI risk assessment capability.
Scale across teams
One standard rolls out across security, GRC, and engineering functions.
Need more than one program?Get a group quote
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Program Overview: What is AI Security and Risk Management?
AI Security & Risk Management is Edstellar's instructor-led technical program for security teams, risk managers, and engineers responsible for AI systems. Participants learn the AI risk landscape, threat modeling for AI systems, adversarial attacks and defenses, governance controls, and secure deployment with monitoring. The program builds end-to-end capability from risk assessment through production hardening.
Training is hands-on from the first module. Participants threat-model AI systems, demonstrate evasion and poisoning attacks in guided labs, and design preventive and detective controls with instructor coaching on every exercise. Labs cover attack trees for ML pipelines, control mapping, and incident response playbooks for AI. The program closes with a capstone where each team runs a full AI risk assessment and hardening sprint on a realistic pipeline.
Security teams are deploying AI systems faster than their defenses can keep up, leaving models exposed to evasion, data poisoning, and extraction attacks. This program teaches teams to inventory AI risks, model threats across the ML pipeline, and implement prioritized controls with audit-ready evidence. Every technique is practiced in labs, so the learning transfers to production systems.
The capstone is a full team sprint against a realistic AI pipeline: assess, attack, harden, and present residual risk. Your organization ends up with people who have actually broken and fixed an AI system, not just read about it.
Six modules and 24 hours: the AI risk landscape, threat modeling for AI systems, adversarial attacks and defenses, AI governance and compliance controls, and secure AI deployment and monitoring. Every module pairs concepts with a guided lab, so each technique is practiced. It closes with a capstone risk assessment and hardening sprint the team runs against a realistic AI pipeline.
What's Included in this Workshop for Your Enterprise Teams
- 1
AI threat landscape briefings
Map how attackers target models, data, and pipelines.
- 2
Threat modeling workshops
Model risks across AI systems and ML pipelines.
- 3
Adversarial testing labs
Probe evasion, poisoning, and extraction attacks.
- 4
Control design exercises
Build defense controls mapped to governance needs.
- 5
Capstone hardening sprint
Assess and harden a realistic AI pipeline as a team.
- Instructor-led delivery across virtual, onsite, and hybrid
- Guided labs in every module with instructor coaching
- Capstone AI risk assessment and hardening sprint
- Flexible scheduling around your calendar
- Lab guides and reusable templates included
- Group size and batches set along with you
Build your team's skills. Anywhere in the world.
Real-world use cases
from day one
Instructor-led training
for your teams
Delivered globally
in 100+ countries
Enterprise Training Solutions Customized for Your Company
One partner for instructor-led corporate training, delivered the way your teams work.
Request a Training Quote- Customized Training Delivery
- Scale Your Training: Small to Large Teams
- In-person Onsite, Live Virtual or Hybrid Training Modes
- Plan from 2000+ Industry-ready Training Programs
- Hands-On Labs on Live Infrastructure, Led by Industry Experts
AI Security and Risk Management Course Topics and Program Outline
Six modules take your team from AI risk fundamentals to a capstone hardening sprint, with guided labs in every module.
Built by Edstellar with AI security practitioners
Built by practitioners who assess and secure AI systems in production, shaped around your stack and use cases.
Skill checks baseline your team's AI risk awareness, threat modeling fluency, and governance maturity before training begins.
Live instruction covers the AI risk landscape, attacker tactics, and control frameworks across 3.5 focused hours.
Guided labs build threat modeling, adversarial testing, and control design skill across 8 hours of supervised practice.
Your team runs a full AI risk assessment and hardening sprint in a 5-hour capstone, reviewed against security standards.
From AI risk fundamentals to a capstone hardening sprint, every control is practiced in guided labs.
Delivered as
Delivered as a hybrid program of live instruction and guided labs, scheduled around your team's calendar in flexible batches.
Catalog AI-specific risks across a sample model inventory.
learna)AI-specific risk categories and failure modes
b)Threat actors targeting models, data, and pipelines
c)Regulatory expectations for AI risk management
d)Building a model inventory for risk coverage
Threat-model an ML pipeline end to end in a guided workshop.
practicea)Threat modeling method for AI systems
b)Mapping data flows and trust boundaries
c)Attack trees for ML pipelines
d)Prioritizing risks by exploitability and impact
Run evasion and poisoning attacks against lab models, then apply defenses.
practicea)Evasion attacks against classifiers
b)Data poisoning and backdoor risks
c)Model extraction and inversion
d)Defenses: hardening, detection, and response
Draft control mappings and audit evidence for a sample AI use case.
applya)AI risk registers and treatment plans
b)Designing preventive and detective controls
c)Mapping controls to governance requirements
d)Audit-ready documentation and evidence
Instrument monitoring and incident response for a deployed lab model.
applya)Secure deployment patterns for AI services
b)Monitoring model behavior and drift
c)Detecting attacks against production models
d)Incident response playbooks for AI
Assess, attack, and harden a realistic AI pipeline as a team sprint.
applya)End-to-end AI risk assessment
b)Demonstrating attacks on the pipeline
c)Implementing prioritized controls
d)Presenting residual risk and roadmap
Customize this program tailored to your team?
Tell us your training needs: what your team already works with, the level they’re at, and the topics you want them to focus on. We’ll adjust the modules, duration and hands-on labs, and send you a customized outline for your group.
Key Skills and Outcomes Your Team Will Gain
Seven job-ready outcomes your team will demonstrate by the end of the program. Each competency is practiced in guided labs and reviewed in the capstone sprint.
Describe AI-specific risks
Explain AI failure modes, threat actors, and regulatory expectations in plain terms for stakeholders.
Threat-model AI systems
Map data flows and trust boundaries to find attacker paths across training and inference.
Test adversarial robustness
Run evasion, poisoning, and extraction attacks against models in safe lab environments.
Design AI security controls
Build preventive and detective controls matched to the risks your assessment surfaced.
Map controls to governance needs
Connect technical controls to governance requirements with audit-ready evidence.
Monitor deployed AI securely
Instrument drift detection and incident response for models running in production.
Lead an AI risk assessment
Run an end-to-end assessment and present residual risk and a hardening roadmap.
Teams that Benefit from this AI Security and Risk Management Group Training
This group training is built for security, risk, and engineering teams accountable for AI systems who want rigorous risk management without slowing delivery. Content adapts to each cohort's roles, stack, and experience, so every batch practices the workflows it owns, from threat modeling to control design.
Prove AI controls to auditors and regulators.
Build the risk registers, control mappings, and evidence packs that make AI governance defensible.
Workflow friction
- Scattered AI risk ownership
- Thin audit evidence
- Shifting regulatory demands
How the program helps
- Audit-ready AI control evidence
- Mapped governance requirements
- Defensible risk registers
Practice use cases
- Control mapping labs
- Evidence workshops
- Risk register drills
Harden the AI systems you ship.
Learn where AI pipelines break under attack and build the defenses that hold up in production.
Workflow friction
- Untested model defenses
- Blind spots in ML pipelines
- Late-stage security reviews
How the program helps
- Hardened AI pipelines
- Tested adversarial defenses
- Secure deployment patterns
Practice use cases
- Adversarial testing labs
- Hardening exercises
- Pipeline reviews
Respond to AI-targeted attacks.
Recognize attacks against models and data, and run response playbooks built for AI incidents.
Workflow friction
- Unfamiliar AI attack patterns
- Missing AI runbooks
- Slow cross-team handoffs
How the program helps
- AI-aware detection playbooks
- Faster AI incident triage
- Coordinated team response
Practice use cases
- AI attack simulations
- Runbook walkthroughs
- Tabletop exercises
Build risk into the ML lifecycle.
Shift risk left with threat modeling and controls embedded from experimentation through deployment.
Workflow friction
- Security as an afterthought
- Untracked model inventory
- Inconsistent control adoption
How the program helps
- Risk-aware ML workflows
- Embedded security controls
- Smoother security reviews
Practice use cases
- Threat modeling labs
- Control design sprints
- Inventory workshops
Cohorts train as a cross-functional workforce, with each small group aligned on shared risk and review standards.
Prerequisites: This program benefits security engineers, GRC professionals, and ML platform teams responsible for AI systems. Basic security concepts help but are not required, and no prior adversarial ML experience is needed. Content adapts to each cohort's tools, models, and governance context.
Security Analyst to AI Security Risk Leader
Tracks how practitioners progress from AI risk fundamentals to leading assessments and control programs across the program's learn, practice, and apply phases.
A program that grows with security careers, from first AI risk assessment to confident leadership of AI security reviews.
Mixed cohort, or several teams at once?
We can tailor the training to different teams, roles, and experience levels within the same program.
Certificate of Training Completion.
On successful completion, employees receive an Edstellar course completion certificate, recognizing their commitment to ongoing learning and professional development. It validates the skills they have built and motivates them to keep growing and contribute to organizational success.
Earned, not attended. Awarded on completion of all hands-on labs and the capstone project.
Training Delivery Modes: Virtual, Onsite and Hybrid
Live instruction with guided labs in every module, available across hybrid, onsite, and virtual formats to fit your team's schedule.
Hybrid Training
Instructor-led sessions mix onsite and virtual delivery with guided labs throughout. Teams practice threat modeling, adversarial testing, and control design with coaching at every step.
- Live instruction across onsite and virtual sessions
- Guided labs with instructor coaching and reviews
- Real AI risk workflows with hands-on practice
- Flexible scheduling without losing live interaction
Onsite Training
Instructor-led training at your offices, with labs set up on your network and tooling. The instructor works alongside the team in threat modeling workshops and the capstone sprint.
- Instructor-led training at your offices
- Labs set up on your network and tooling
- In-person coaching and reviews
- Exercises tuned to your AI stack and workflows
Live Virtual Training
Live virtual sessions on Zoom or Teams with screen-shared walkthroughs, breakout labs, and real-time reviews. Your team gets the same guided labs and capstone sprint from anywhere.
- Live virtual sessions on Zoom or Teams
- Screen-shared walkthroughs and breakout labs
- Real-time review with the instructor
- Same guided labs as onsite, from anywhere
Need a training format that works for your team?
Full days, half days across weeks, or split by module. Tell us the delivery window and we schedule the cohort around it.
Learn from industry experts.
Every session is led by a practitioner who has run monitoring for models in production, not a generalist working from slides.
Asjad
Risk Management Trainer in New Delhi
14+ years of Experience
Rohat
Risk Management Trainer in Erbil
11+ years of Experience
Muhammad
Risk Management Trainer in Rawalpindi
12+ years of Experience
Satyanarayana
Cybersecurity Fundamentals Trainer in Hyderabad
7+ years of Experience
Ivan
Cyber Security Trainer in Bengaluru
9+ years of Experience
Madhumetha
CompTIA Security+ Trainer in Chennai
9+ years of Experience
Yasir
Cybersecurity Trainer in Anantnag
11+ years of Experience
Trainers are matched to your stack and delivery window at scheduling. We confirm your assigned trainer, with a full profile, before the program is booked.
Frequently Asked Questions
Share your team size, timelines, and delivery preference, and we will send a detailed per-group quote with batch options.
Yes. Book a discovery call and we will map your AI footprint, risk maturity, and goals to a tailored training plan.
Yes. Live virtual sessions run on Zoom or Teams with the same guided labs and instructor coaching as onsite delivery.
Yes. The instructor runs the full program at your offices, with labs set up on your network and tooling.
The program runs 24 hours across six modules, closing with a 5-hour capstone risk assessment and hardening sprint.
Question not answered here?
Put it in the request. A training specialist answers it directly, within one business day.
Where this Training Fits in Your Team's learning path.
Managing AI security risk comes after governance, because your team needs agreed policies and accountability before it can assess and treat risks. With the risk picture clear, you can then protect specific LLM applications and test those protections through red teaming.
Why Choose Edstellar as Your AI Security and Risk Management Corporate Training Provider
When comparing providers, Edstellar is the training partner teams choose for AI security expertise and 5+ years of corporate training experience. Our method pairs briefings with guided labs, so capability is demonstrated, not just described.
EXPERT TRAINERS
YEARS DELIVERING
ORGANIZATIONS TRAINED
CERTIFIED
Tailored
Every cohort's labs, examples, and exercises are tuned to your AI platforms, model pipelines, and risk register.
Proven Methodology
A learn, practice, apply arc moves your team from AI risk concepts to a live capstone hardening sprint.
Practice-Based Learning
Guided labs in every module build threat modeling, adversarial testing, and control design skill.
Expert Trainers
Practitioners who assess and secure AI systems in production lead every session.
Global Scale
One consistent program rolls out across security, GRC, and engineering teams in every region.
Measurable Outcomes
Lab checkpoints and the capstone assessment show exactly which AI risks your team can now manage.
Also from Edstellar
Talent assessments
Psychometric, behavioral, leadership and 360-degree assessment.
→Training needs analysis
Needs analysis, gap identification, and a training roadmap.
→L&D consulting
Learning strategy, content, technology and ROI measurement.
→OD consulting
Org design, succession planning and cultural change.
→Managed training services
Training outsourcing, vendor management, logistics and administration.
→Coaching solutions
Executive and manager coaching that keeps skills in use.
Start an RFP shaped to your needs.
Answer three quick questions about team size, scope, and how often you need the program run, then send the request from the last step. Everything you choose travels with it, so you only fill this in once.
How many team members need training?
AI Security & Risk Management Training Packages & Pricing
Where L&D holds an annual budget, license packages price the whole year at once instead of raising a purchase order per workshop. Hours and licenses are pooled across teams, programs and locations, so unused capacity is not stranded in one department.
Starter
120
trainee licenses64 hours of group training
Tailored for SMBs
Growth
320
trainee licenses160 hours of group training
Ideal for growing SMBs
Enterprise
800
trainee licenses400 hours of group training
Designed for large corporations
Custom
Unlimited
trainee licensesDuration set by the rollout
Multi-region and multi-year
Training Packages & Pricing
Choose the training format that works for your team. Pricing is customized based on your requirements, cohort size, and delivery needs.
Request AI Security and Risk Management Training for Your Team
Share your team size, AI platforms and models, governance context, and timelines to receive a tailored training plan and quote. Book a discovery call to discuss your goals.