Enterprise AI Sandbox: Testing and Piloting GenAI

Run safe experiments and pilots before production deployment.

Pillar

Technology – Platforms, Tools, Infrastructure & Productivity

Overview

This course guides participants through establishing and managing an enterprise AI sandbox environment dedicated to safely experimenting with Generative AI models and solutions. Learners will understand how to design pilot projects, evaluate AI outputs, and mitigate risks before full-scale production rollout. The course emphasizes controlled testing, iterative development, and stakeholder collaboration to accelerate innovation while ensuring compliance and security.

Learning Objectives

Participants will be able to:

• Set up and configure AI sandbox environments for testing GenAI applications

• Design pilot projects and proof-of-concepts with clear objectives and success criteria

• Evaluate AI model performance, reliability, and ethical considerations

• Manage data security and compliance in sandbox settings

• Communicate pilot results effectively to business and technical stakeholders

Target Audience

• AI project managers and solution architects

• Data scientists and ML engineers

• IT governance and risk management professionals

• Innovation leads and business sponsors

Duration

20 hours over 4 days (5 hours per day)

Delivery Format

• Hands-on sandbox setup and configuration

• Case study-based pilot design workshops

• Group discussions on risk and compliance

• Feedback and presentation sessions

Materials Provided

• Sandbox environment access or simulation tools

• Pilot planning templates and checklists

• Evaluation and reporting frameworks

• Security and compliance guidelines for AI pilots

Outcomes

• Capability to establish safe AI experimentation spaces

• Improved pilot project success rates and risk mitigation

• Enhanced cross-functional collaboration on AI initiatives

• Clear processes for transitioning pilots to production

Outline / Content

Day 1: Introduction to AI Sandbox Environments

• Purpose and benefits of AI sandboxes

• Technical and organizational requirements

Day 2: Designing and Running GenAI Pilots

• Defining pilot objectives, scope, and metrics

• Data preparation and sandbox configuration

Day 3: Evaluation and Risk Management

• Assessing model performance and ethical impact

• Managing data privacy and security in pilots

Day 4: Reporting, Stakeholder Communication, and Scaling

• Documenting pilot outcomes and lessons learned

• Planning production rollout and continuous improvement