AI Coach Frequently Asked Questions

AI Coach is intended for employees at all levels who want to improve workplace effectiveness. This includes individuals developing communication and leadership skills, managers practicing coaching or difficult conversations, and professionals looking to enhance collaboration, feedback, and performance-related discussions.

AI Coach is designed to support employee development by helping learners build self-awareness, set meaningful goals, and strengthen communication, leadership, and interpersonal skills through ongoing, conversational coaching. It delivers personalized guidance based on each learner’s assessments, feedback, goals, and context, offering real-time prompts, reflections, and next steps. By creating a psychologically safe, judgment-free space, AI Coach enables learners to explore challenges, track progress over time, and translate insights into sustained behavior change. It also reinforces effective workplace behaviors and decision-making by helping learners prepare for key moments, reflect on feedback, and stay accountable to their development.

There is no required usage frequency. Learners can engage with AI Coach as often or as little as they find valuable.

AI Coach supports frequent usage, allowing learners to engage in multiple coaching interactions daily, with system limits in place to ensure performance and scalability.

Learners do not see a disclaimer upon entering AI Coach. There is an i icon they can click for disclaimer information. It reads:

Please keep in mind AI can occasionally make mistakes. We value your privacy and ensure your data is handled with the utmost care. Learn more.

Learners engage with AI Coach through a conversational interface using text or voice. The AI Coach responds in real time, guiding the conversation with reflective questions, feedback, and prompts. After each interaction, learners receive insights and suggested next steps to support their development.

AI Coach is not available for mobile experiences right now.

If AI Coach is limited to specific audiences, learners will only see it if they are included. Review your audience configuration and user assignments to ensure access is set correctly.

AI Coach is currently available only in Engligh. Additional languages will be added by the end of August.

To see if it is available in your language, you can check out this table.

Learners can provide feedback directly within the chat by selecting a thumbs up or thumbs down icon on a response. This opens a dialog where they can optionally rate the response and add comments.

Feedback learners submit via the thumbs up/down icon is logged in the conversation logs.

The feedback is periodically reviewed by the Product teams for sentiment, improvements, and potential issues as well as to identify trends. Insights from this feedback are used to enhance the experience, improve, and strengthen AI quality and safety.

No. AI Coach is not designed to provide medical, legal, or mental health advice. It supports professional development and learning through reflection and coaching‑style inquiry only.

AI Coach is not intended for non-workplace or unrelated conversations, nor does it handle or process sensitive personal, financial, or medical data beyond what a learner may voluntarily input. It does not train or fine-tune AI models using customer data, and guardrails prevent inappropriate, harmful, or off-topic interactions to ensure a professional experience.

AI Coach interactions are designed for learner development. Any organizational insights or reporting are anonomized and aggregated. Any feedback provided to managers will be directly shared by learners.

No. AI Coach is not connected to formal performance reviews, the coach will have conversations with learners to prepare for conversations.

No. AI Coach does not provide an assessment directly, grade, or score learners. It is designed to support reflection, goal clarity, and growth rather than evaluation.

AI Coach does not set goals or action plans for learners. It supports reflection and exploration, allowing learners to determine their own focus and next steps.

AI Coach does suggest to learners what they might want to focus on based on role, feedback and conversations.

AI Coach is designed to support continuity across conversations, helping learners build on prior reflections while remaining in control of the experience. Previous conversations will be available under the chat history.

The AI coach will continue to send learners notification to engage unless the access is removed. AI Coach access settings are either turned on for the entire company, or by audience.

Learners can access AI Coach through the Percipio platform 9 dot icon in the top left, or through a direct link.

AI Coach uses relevant learner data—such as goals, feedback, prior interactions, and uploaded documents—to personalize coaching. This data is used solely to support the coaching experience and improve service quality. It is not used to train external AI models or shared with third parties.

AI Coach is enabled at the company level. Once turned on, organizations can control access by granting it to all users or limiting it to specific users or audiences through user settings.

Yes. When learners use AI Coach, analytics appear in two places. Within a dedicated AI Coach dashboard and within feature usage reports. These reports tracks how long the learner interacts with the AI, login, goal setting and the assessment aggregated data. Admins can also access content usage by going to any other dashboard and filtering by audiences with access to AI Coach.

Admins can use the AI Coach emails to alert learners that they have access. The email directs learners to engage with the AI Coach and has options to send reminders to those who have not signed in.

AI Coach can be accessed through a direct link, LMS users will get access to Percipio through AI Coach.

Yes. You can hide content that you do not want your learners to see. Follow the instructions for Hiding individual content items.

You can upload up to three documents as knowledge sources for AI Coach, such as performance evaluations, company overviews, or leadership competencies. These inputs help tailor coaching responses to the organization’s context.

To ensure we can provide benchmarking data we are not allowing these questions to be customized. Site admins can control if managers and colleagues can be invited for feedback,if manager feedback is seperated out, and a minimum number of colleagues required to invite if learners request feedback.

For consistancy we are not allowing these questions to be customized, the Site Admin can control if learners are asked to complete the pulse checks and how often. They also have control of if the learner can invite a manager for this pulse check feedback.

Learners may receive email and in-platform notifications to prompt key coaching actions, such as starting or continuing a conversation, reviewing feedback, reflecting on progress, catching up on an overdue goal, or preparing for important moments (e.g., performance reviews). Notifications are designed to encourage ongoing engagement and keep learners on track with their development.

• Feedback learners submit via the thumbs up/down icon is logged in the conversation logs.

  The feedback is periodically reviewed by the Product teams for sentiment, improvements, and potential issues as well as to identify trends. Insights from this feedback are used to enhance the experience, improve, and strengthen AI quality and safety.

• Any data that you share helps Skillsoft improve the service. For example, we use your feedback to increase the effectiveness of AI safety policies.
• Skillsoft has a process for improving AI Coach, which includes review of conversations reported as being low quality. This helps us identify common types of problematic responses and how the AI Coach might improve.
• Only limited Skillsoft employees can access and review conversation data.

AI Coach does not collect or store user IP addresses, nor does it collect location data, or any personal information (PII) from the learner unless the learner inputs it as part of their conversations. Skillsoft network security separately logs IP addresses for the purposes of addressing security risks, such as Distributed Denial-of-Service (DDOS) attacks and intrusion detection. Learn more about how we protect your privacy by reviewing our Privacy Notice - Skillsoft.

Skillsoft always logs the AI side of the conversation, time stamps, AI options used during the conversation, ratings, feedback, if guardrails are triggered, and other non-user specific data for reporting and analytics.

Skillsoft only logs the learner side of the conversation if the admin setting: AI optimization and improvement is enabled and the learner has not turned it off on their side. Skillsoft also collects the learner side of the conversation if the learner provides feedback and checks the box to share the conversation.

Learners can opt out of having their side of the conversation shared with Skillsoft, even if it is enabled for your company:

1. With the open, select Settings.

2. Turn off: Allow Skillsoft to collect, store, and analyze my conversations in order to improve the .. This setting is on by default for companies using the US data center and off by default for companies using the EU data center. Admins can change the default behavior of this setting for the learner.

3. Select Save.

• All data entered is encrypted in transit and at rest.
• The information that the learner enters into passes to the Large Language Model (LLM) .
• The LLM does not store any conversation data. Skillsoft has MS Azure OpenAI prompt moderation exception so no Generative AI inputs or outputs are logged or reviewed by Microsoft. Similarly, no data from AI Coach is distributed to third parties or is available to train any models.
• Skillsoft stores AI conversation data in authenticated and encrypted AWS storage.
• AI Coach does not collect or store personal data from users unless they enter the information as part of the conversation.

• Feedback learners submit via the thumbs up/down icon is logged in the conversation logs.

  The feedback is periodically reviewed by the Product teams for sentiment, improvements, and potential issues as well as to identify trends. Insights from this feedback are used to enhance the experience, improve, and strengthen AI quality and safety.

• Any data that you share helps Skillsoft improve the service. For example, we use your feedback to increase the effectiveness of AI safety policies.
• Skillsoft has a process for improving AI Coach, which includes review of conversations reported as being low quality. This helps us identify common types of problematic responses and how the AI Coach might improve.
• Only limited Skillsoft employees can access and review conversation data.

Yes. All data entered is encrypted in transit and at rest.

Third party LLM providers do not log or have access to inspect any AI inputs or outputs. Skillsoft only stores conversation data in authenticated and encrypted AWS storage. Only limited Skillsoft employees can access and review conversation data.

Skillsoft stores this data per the terms in your contract. Skillsoft can delete log data upon request.

The STT uses the same service as Microsoft Teams (Azure speech services) to convert spoken input into text. to The audio that the user speaks is sent from their browser directly to the Azure cognitive speech service. The Azure speech service transforms the audio to text and returns it to the user's browser where it is entered into the text input box. After transforming the audio to text, the audio is not stored and is deleted after processing.

Microsoft does not log or save the input or output from the cognitive speech services.

For more information, see:

• Azure Data and privacy for speech to text
• Azure Data, privacy, and security for text to speech

• The information that the learner enters into passes to the Large Language Model (LLM) .
• The LLM does not store any conversation data. Skillsoft has MS Azure OpenAI prompt moderation exception so no Generative AI inputs or outputs are logged or reviewed by Microsoft. Similarly, no data from AI Coach is distributed to third parties or is available to train any models.
• Skillsoft stores AI conversation data in authenticated and encrypted AWS storage.
• AI Coach does not collect or store personal data from users unless they enter the information as part of the conversation.

Yes, it is possible to delete per user and per organization upon request. Reach out to our Support team for assistance.

• SME evaluation: Experts assess outputs based on correctness, appropriateness, and contextual relevance, ensuring responses align with best practices.
• Continuous monitoring: AI Coach detects runtime anomalies and triggers alerts if issues arise, allowing the responsible team to address them promptly.
• Guardrails and qualitative testing: Built-in safeguards filter out inappropriate or off-topic inputs, ensuring consistency in conversational flow.
• Hallucination detection: AI Coach flags responses that deviate from expected topics.

Because AI Coach outputs are context-specific and dynamic, SME-driven assessments and real-time monitoring are essential for maintaining response quality.

AI Coach is designed with built‑in guardrails that govern tone, boundaries, and behavior. It avoids prescriptive advice, pressure, or judgment and is designed to handle uncertainty responsibly.

We have concurrent GenAI model prompting for every user input to test for inappropriate inputs. If we discover inappropriate inputs, we stop the conversation and inform the learner. The GenAI model also has it's own guardrails to flag inappropriate input which we also monitor. If we discover inappropriate input from that perspective, we also stop the conversation and inform the user.

One guardrail checks if the conversation is inappropriate. If the conversation is inappropriate, we stop the conversation and let the learner know their response is inappropriate.

Another guardrail checks if the user made an unrelated comment. If it is the first occurrence of unrelated content, we will ask the learner to redirect the conversation back to the topic at hand. If the learner continues down the unrelated path, we stop the conversation.

The guardrails allow for a learner to have a conversation provided they are working in a professional manner and are addressing the issue at hand.

We either warn learners and guide them back on-topic, to be more professional, or we stop conversations that cross the boundaries set by the guardrails.

Skillsoft applies enterprise‑grade AI safety practices, including content filtering, behavior boundaries, and continuous monitoring to ensure interactions remain professional, respectful, and appropriate for learning and development.

In our ongoing efforts to enhance AI Coach, we are primarily focused on reducing false positives, where the guardrail flagged an incident when it shouldn't have. False positives unnecessarily block conversations and hinder the user experience.

We also make our best efforts to minimize false negatives, where the incident doesn't trigger the guardrail and should have. Our goal is to catch most inappropriate or off-topic content without overly tripping the guardrails. This balancing act requires us to prioritize the reduction of false positives over false negatives to ensure a smoother and more effective conversation flow.

Our testing dataset encompasses a broad range of content categories to thoroughly test AI Coach performance across various sensitive, inappropriate, unprofessional, or off-topic themes it may encounter in real-world interactions. By exposing AI Coach to this diverse set of test cases, we can systematically assess the robustness and reliability of its behavioral guardrails.

The primary categories covered in our testing dataset include:

• Threatening: This category includes statements or language that could be perceived as threatening or indicative of impending harm, ranging from subtle threats to explicit declarations of intended violence.
• Sexual: Test cases in this category cover sexually charged language and themes, from subtle innuendos to overt descriptions of sexual acts.
• Hate: This category tests responses to language expressing prejudice, bias, or hostility towards specific groups based on protected attributes, spanning from casual stereotyping to overt slurs and hate speech.
• Harm: Test cases involve language that could be interpreted as encouraging or glorifying self-harm, suicide, or violence towards others.
• Harassment: This category assesses ability to detect and respond to language that aims to demean, humiliate, or intimidate others, ranging from subtle insults to blatant verbal harassment.
• Violence: This category focuses on language involving graphic depictions of violence, gore, or physical harm, distinct from outright threats.
• Bias: This category tests handling of subtle expressions of bias and prejudice, such as stereotypical assumptions, microaggressions, or language reflecting unconscious biases.

We look for both direct input, where the problematic nature of the content is clear and explicit, which could include:

• Overt insults, slurs, or derogatory language directed at individuals or groups
• Explicit threats of violence, harm, or abuse
• Unambiguous expressions of bias, hatred, or discrimination
• Graphic or detailed descriptions of sexual acts, violence, or illegal activities

And indirect input, where the problematic nature of the content is implied, subtle, or contextually dependent, which could include:

• Veiled or implicit threats that rely on innuendo or suggestion
• Backhanded compliments or microaggressions that subtly demean or stereotype
• Sarcasm, jokes, or memes that mock, belittle, or promote harmful attitudes
• Seemingly innocuous statements that, in a specific context, could enable or encourage problematic behavior

By evaluating AI Coach responses to both direct and indirect articulations of problematic content, we gain a more comprehensive view of its language processing capabilities and its robustness in handling a wide spectrum of potential user inputs.

This dual focus on content and articulation mode enables us to refine guardrails to detect and mitigate harm across a broad range of interaction styles and contexts. The insights gleaned from this analysis also inform our ongoing efforts to enhance ability to engage in thoughtful, contextually aware dialogue. By understanding the subtleties of how problematic content can be expressed, we can develop more sophisticated strategies for addressing these issues in a nuanced, adaptive manner.

We don't attempt to address jailbreaks because in the event of an adversarial attack, the generated output would only be visible to the affected learner and would not have any bearing on the experiences or outcomes of other learners. The localized impact of such an attack minimizes the overall risk to our platform and its users.

Because AI Coach provides subjective analysis of conversations, it is not answering specific questions or stating facts. Extensive testing has not revealed significant issues with outputs. Users are warned that responses might not be accurate, and they should use their own judgment when reviewing the response.

Each scenario has a detailed description that includes guidance which guards the conversation to detect and prevent bias and inappropriate responses.

In addition, AI Coach uses the LLMs default content filtering and adds additional tests and guards to detect and minimize inputs that might stimulate bias or other inappropriate responses. Skillsoft does extensive QA testing including automated and manual review of flagged conversations, and has continuous feedback loops with learners and admins to identify and correct issues.

Because AI Coach provides subjective analysis of conversations, it is not answering specific questions or stating facts. Extensive testing has not revealed significant issues with outputs. Users are warned that responses might not be accurate, and they should use their own judgment when reviewing the response.

While it is not zero, it is low and extensive testing has not revealed issues that have raised concerns.

It is improbable could produce any hallucinations or bias based on demographics because doesn't capture any demographics information, such as country, gender, or age, and all learners use the same AI model version.

Extensive Quality Assurance testing has not revealed significant issues with outputs. This simulator provides subjective analysis of conversations. It is not answering specific questions or stating facts. Each scenario has a detailed description that includes guidance which guards the conversation.

AI Coach utilizes the built-in LLM guards and adds additional guards which review and evaluate the user inputs for off-topic, abuse, and misuse. If these are detected, the user will be alerted, and the conversation will be halted and require editing or restarting.

Users are warned that responses might not be accurate. Users must acknowledge prior to using AI Coach that they should use their own best judgment.

Because AI Coach provides subjective analysis of conversations, it is not answering specific questions or stating facts. Extensive testing has not revealed significant issues with outputs. Users are warned that responses might not be accurate, and they should use their own judgment when reviewing the response.

Please submit feedback so we can review and improve any rare mistake that may occur.

AI Coach leverages non-zero temperature to create variety in the conversation. Extensive testing indicates the conversations stay on topic and feedback is appropriate.

Individual coaching conversations are completely confidential and are never shared with managers, HR teams, or organizational leadership. Employees can choose to voluntarily share specific goals with their manager for input and guidance, but that is always their decision. Colleague feedback is always anonymous, and your organization only receives high-level, aggregated insights that surface development trends across the workforce, never individual-level content. This approach protects psychological safety, which is essential for employee engagement and program adoption.

Individual coaching conversations are not shared with managers, HR teams, or organizational leadership. The only exception is goal feedback, which learners can choose to share with their manager voluntarily. Colleague feedback is always anonymous, and manager feedback visibility is disclosed upfront. Additionally, AI Coach does not use individual learner data to train its underlying model. One learner's coaching conversations do not influence another learner's experience.

AI Coach uses generative AI in an ethical and responsible way through the implementation of appropriate guardrails, widely recognized as important for AI systems.

In addition, AI Coach uses the LLMs default content filtering and adds additional tests and guards to detect and minimize inputs that might stimulate bias or other inappropriate responses. Skillsoft does extensive QA testing including automated and manual review of flagged conversations, and has continuous feedback loops with learners and admins to identify and correct issues.

AI Coach is developed and hosted on AWS and does not use other ChatGPT consumer products. The features utilize the security capabilities of Microsoft Azure:

• Encryption: The LLM automatically encrypts the user's data. The encryption protects their data and helps customers meet organizational security and compliance commitments.
• Data Security: The LLM offers us the ability to do regional deployments to ensure EU hosted data is processed in EU and North America hosted customers data is processed within North America.
• Limited Access Review: Modified Abuse Monitoring - The LLM does not store any conversation data. Skillsoft has MS Azure OpenAI prompt moderation exception so no Generative AI inputs or outputs are logged or reviewed by Microsoft. Similarly, no data from AI Coach is distributed to third parties or is available to train any models. Skillsoft only logs conversations based on opt-in/out or explicit sharing when reporting feedback within the AI simulator.

Additional security layers help to mitigate biases in training data, promote fairness, reduce the spread of false information, and prevent offensive or inappropriate responses through the interactions that learners have with .

Every time a conversational scenario takes place, the system is monitoring for abuse, correct context, and scenario accuracy. For example, if a learner were to initiate an off-topic or inappropriate conversation with would guide the learner to only make appropriate statements. The learner can then resume or restart the conversation. Striking this balance is crucial to avoid overly restrictive measures while maintaining responsible deployment.

Data is encrypted in flight with TLS 1.2+ and encrypted at rest per FIPS 140-2.

The data is persisted within the FedRAMP authorization boundary where limited and authenticated access is required.

The current models that are used are Commercial off-the-shelf (COTS) models. The models are created by the LLM and hosted by with enhanced data security and content filtering for safety. They do not list all the data that was used for training.

AI Coach utilizes multiple custom prompts that act in parallel to conduct, guide, guard, rate, and evaluate the conversations. We monitor feedback and periodically QA test the system.

No, we do not train or fine-tune AI models used by AI Coach with any user inputs.

No, but it does use OpenAI models of which the core foundation model is similar to ChatGPT.

MS Azure OpenAI uses default content filters for safety to prevent inappropriate inputs and responses.

AI Coach is developed and hosted on AWS and does not use other ChatGPT consumer products. The features utilize the security capabilities of Microsoft Azure:

• Encryption: The LLM automatically encrypts the user's data. The encryption protects their data and helps customers meet organizational security and compliance commitments.
• Data Security: The LLM offers us the ability to do regional deployments to ensure EU hosted data is processed in EU and North America hosted customers data is processed within North America.
• Limited Access Review: Modified Abuse Monitoring - The LLM does not store any conversation data. Skillsoft has MS Azure OpenAI prompt moderation exception so no Generative AI inputs or outputs are logged or reviewed by Microsoft. Similarly, no data from AI Coach is distributed to third parties or is available to train any models. Skillsoft only logs conversations based on opt-in/out or explicit sharing when reporting feedback within the AI simulator.

The Skillsoft Percipio Platform is a multi-tenant system where all tenants share the same services and resources. Customer data is isolated with tenant keys and/or S3 buckets.

Yes. The Skillsoft Platform has been FedRAMP authorized since March 4, 2022. A Significant Change Request (SCR) for the technologies supporting the feature of the platform was signed by our Third Party Assessment Organization (3PAO), Booz Allen, on January 18, 2024 following a review by our FedRAMP sponsor, USDA. uses AI services from the US Microsoft Commercial Cloud, which is also FedRAMP authorized.

You can find Skillsoft's FedRAMP authorizations at:

• Skillsoft Platform Package: FR2118043605
• Microsoft Azure Commercial Cloud: F1209051525

Yes. AI Coach adheres to EU AI Act, GDPR, and NIST AI Risk Management Framework. We also engage with third-party auditors to validate alignment with applicable laws and best practices.

Not at this time..

AI Coach supports both X-Frame-Options and Content-Security-Policy security headers to prevent click-jacking attacks.

AI Coach follows the learner’s lead while providing gentle structure to support thoughtful reflection and forward movement within learning and development conversations.

AI Coach recommends relevant Percipio content during coaching conversations and within the platform based on the learner’s goals, skills, and context. These recommendations are embedded directly in the chat, making it easy for learners to access targeted resources—such as courses, videos, books, similations and benchmarks—and apply them within their goals.

AI Coach is not a chatbot. It is a dedicated coaching environment governed by an , International Coaching Federation (ICF)-aligned meta-behavior system that shapes how the coach shows up across every employee interaction over time. It remembers each learner's goals, progress, and communication preferences, builds on prior conversations, and deepens its challenge to the learner as trust grows. Rather than delivering quick answers or templated prompts, it guides employees through structured reflection and helps them develop their own insights and action plans. The result is a coaching experience that drives sustained behavior change, not one-off engagement.

AI Coach expands your coaching reach rather than replacing human coaching. Skilled human coaches bring depth, presence, and relational capability that AI is not designed to replicate. AI Coach is built for personalized, always-on development support: helping employees set goals, build accountability, practice critical skills, and reflect between formal coaching engagements. It makes high-quality coaching accessible to every employee in your organization, including those who would not typically have access to a human coach due to cost or availability. AI Coach can be used alongside Skillsoft's 1:1 individual coaching and group coaching offerings, or on its own.

AI Coach is a feature of the Skillsoft Platform, which conforms to WCAG 2.1 A and AA accessibility standards with some exceptions noted in its VPAT Conformance Report.

No, AI Coach will not be launched with voice feature. Once this launches we will not save audio recordings. Audio is only in memory until it is transcribed to text and then the audio is immediately discarded.

Skillsoft AI Coach is built using advanced large language model technology selected to meet enterprise requirements for reliability, safety, and scalability. We focus on the coaching experience and outcomes rather than exposing underlying model specifics.

Yes. AI Coach uses generative AI to support reflective conversations, goal clarity, and learning experiences in a structured and responsible way.

Learners can access Skillsoft’s standard support channels for assistance with platform functionality and access.