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Last Updated as of: May 1, 2025

AI in ExecOnline Products

Last Updated as of: February 11, 2025

At ExecOnline, our product development is driven by a commitment to strong performance, robust security, and strict data privacy. As artificial intelligence (AI) becomes an increasingly important tool, we understand that our clients may have questions about our new AI-powered features launched in 2025. This document outlines our privacy and security measures related to AI technologies, emphasizing our commitment to transparency.

Overview of AI at ExecOnline

ExecOnline leverages a combination of proprietary AI tools and reliable third-party services, including AWS Bedrock and Anthropic’s Claude. We collaborated with a voluntary group of customers, all of whom met our high standards for data privacy, security, and processing agreements, to build some of our AI technology. When using external services like Bedrock or Claude, no customer data or internal information is submitted for third-party model training.

AI-Driven Features and Providers

Our dedication to secure, privacy-centric AI remains unwavering as we continue to innovate for our customers. Below is a list of AI technology providers associated with each AI-driven feature offered by ExecOnline:

AdminStudio
  • EXO AI Advisor: AWS Bedrock; Claude by Anthropic
  • Support Chat: Intercom AI
Learning app
  • AI Project Feedback: AWS Bedrock; Claude by Anthropic
  • Personalized Program Recommendations: ExecOnline ML; LightFM
  • Support Chat: Intercom AI

ExecOnline ML refers to our custom Machine Learning (ML), which is not model-driven and instead operates using a rules-based approach, relying on predefined statistical methods that produce consistent results given the same input.

AI Model

Our AI operates using data specific to each client or user, delivering tailored insights and recommendations that address the unique requirements of each organization. We uphold stringent data privacy and security protocols throughout the process, guaranteeing that customer data is never shared or used for training external models.

Model Details

  • Integrated AI Ecosystem: ExecOnline leverages pre-built, enterprise-grade AI services from AWS Bedrock and Anthropic’s Claude to deliver powerful functionalities. Rather than training our own models, we integrate these state-of-the-art services to generate data-driven insights that enhance both administrative and learner experiences.
  • Tailored Recommendations and Feedback: Program recommendations and action plan evaluations are generated through advanced natural language processing and analytics offered by our integrated providers. By tapping into the capabilities of AWS Bedrock and Claude, the system delivers detailed, personalized recommendations and feedback that helps admins meet their enterprise goals and learners understand their strengths and areas for improvement. This approach provides actionable insights without the need for our own model training process, ensuring rapid and reliable output that evolve with the user.
  • Data Privacy and Isolation: Our approach prioritizes strict data separation and privacy. All client-specific data is processed within each organization’s secure environment, ensuring that sensitive information remains isolated and is never used to train cross-client models. This maintains robust security and compliance while still leveraging the advanced analytics capabilities of our AI partners.
  • Cloud-Enabled Scalability and Security: By using AWS Bedrock’s resilient, scalable cloud infrastructure, in combination with Anthropic’s advanced language model capabilities, our AI system delivers consistent performance and reliability. This ensures that both program recommendations and assessments are delivered with high accuracy and responsiveness, underpinned by industry-leading security and compliance standards.
  • Opt-Out: Enterprises have the option to opt out of AI-driven features at any time. This flexibility is built into the platform so that each organization can tailor the AI interactions to meet their internal policies and preferences.

Privacy and Security Measures

We prioritize the privacy and security of our users’ data. Our AI systems are built with robust security measures to protect sensitive information. We adhere to strict data privacy regulations and best practices, ensuring that all data is handled responsibly and securely with a comprehensive security program.

Specific Measures

  • Data Processing Agreements (DPAs): We have DPAs with each sub processor, including our AI systems.
  • Encryption: Data is encrypted in transit and at rest.
  • Regulatory Compliance: We comply with all applicable laws and standards governing AI development and deployment, including GDPR.
  • Third-Party Audits: We prioritize the integrity of reviews by working with independent consultants.
  • Annual Training: Above compliance we require all employees and contractors to complete relevant education and training.
  • AWS Environment: Strict access controls and IAM policies with multi-factor authentication, as well as continuous monitoring.
  • Data Segmentation: Data is segmented and logically separated from other customers’ data.
  • Pipeline Controls: Governance for output to subcontractors. 
  • Logical Separation: We use logical separation techniques to ensure data is not commingled.
  • Cloud Instance: Data models and data only exist in our cloud instance, secured by AWS and Bedrock.
  • Best Practices: We incorporate best practices into the AI supply chain, including providers and deployers and protection of data and models.

Transparency and Explainability

We are committed to being transparent about how our AI systems work and the data they use. We fully document all our features in our help center and strive to explain our implementations clearly. We enable stakeholders to understand and evaluate system outputs and always allow our customers to opt out of our AI features, empowering them to make informed choices about their engagement with our AI systems.

AI Model Validation and Testing

We rigorously validate and test our AI models to ensure their accuracy, reliability, and fairness. Our validation processes include testing under various scenarios to identify and mitigate potential biases and errors. We establish robust procedures for output validation and continuously monitor our AI systems to maintain high standards of performance and trustworthiness.

Responsible Data Stewardship

We are responsible stewards of our clients’ data. In most cases, we have passed our clients’ independent security programs and maintain ISO standards. We comply with all applicable laws and standards governing AI development and deployment. Our privacy policy provides detailed information on data usage and protection.