Building AI-Powered Software? Prepare to Answer These 11 Security Questions

You've integrated AI into your product, and your customers are demanding answers around security and privacy. This is understandable, as artificial intelligence becomes a core component of business services, it delivers significant innovation and value. However, this deeper adoption also brings heightened customer scrutiny regarding data handling, model integrity, and overall system security.

Over the past year, we at Pillar Security have worked closely with security and AI teams facing these enterprise adoption challenges, especially in highly regulated industries like financial services and healthcare. 

Drawing from these real-world security reviews and direct customer interactions, we've distilled the most frequent and impactful AI security questions your customers are actually asking. This article outlines practical guidance on how Pillar Security empowers your team to answer each one confidently and comprehensively.

1. How and where is AI used in your product or service? What specific functions or decisions does it power?

Why customers ask: Buyers require a clear understanding of AI's role within your product to accurately assess its potential impact and associated risks. They need to differentiate between AI enhancing non-critical features versus AI autonomously driving important decisions. This transparency is fundamental for building trust, as stakeholders increasingly expect to be fully informed about any AI involvement in the services they use.

How Pillar Helps: To provide the necessary clarity, a forthright and specific explanation of your AI's scope and purpose is essential. Pillar Security directly empowers you to deliver this comprehensive and factual response by:

• Providing Full AI Visibility with AI Discovery: This capability delivers a continuously updated inventory of all AI assets (models, meta-prompts, datasets) across your codebases and data platforms. This allows you to factually state which modules use AI, the types of models employed, and their origins (in-house or third-party), forming the basis for a specific and well-documented answer.
• Detailing AI Functions with AI Telemetry: This feature offers full logging of AI application interactions, including inputs, outputs, and tool calls, enriched with metadata. This enables you to precisely articulate and provide verifiable evidence of the tasks AI handles (e.g., "AI ranks search results," "AI autonomously executes specific user requests") and demonstrates its exact operational influence.

2. What data are your AI models trained on, and how do you ensure the quality and integrity of that training data?

Why customers ask: Customers are rightly concerned about the provenance, quality, and ethical sourcing of the data that shapes your AI models. Poor-quality, biased, or improperly sourced training data can lead to inaccurate, skewed, or discriminatory outputs, posing significant security, compliance, and reputational risks. They will inquire about data acquisition methods, consent, and the potential inclusion of copyrighted or sensitive information.

How Pillar Helps: A robust answer involves clearly identifying training datasets and detailing your rigorous processes for ensuring their quality, integrity, and responsible sourcing, including validation methods. Pillar Security underpins your ability to provide this assurance by:

• Identifying and Inventorying Training Data with AI Discovery: This feature helps you maintain a comprehensive inventory of the datasets used to train your AI models, providing the foundational transparency needed to discuss data origins.
• Ensuring Data Quality and Compliance with AI-SPM (AI Security Posture Management): AI-SPM enables risk detection and scanning of your datasets and data pipelines. This allows you to assess data quality, map the risk posture associated with your training data, and verify compliance with responsible sourcing policies (e.g., consent, copyright, sensitivity). It helps demonstrate that you're actively managing the integrity and ethical considerations of your training data.
• Facilitating Secure Validation with AI Workbench: The AI Workbench offers an isolated environment for safe testing and experimentation with models and data. This supports your validation processes, allowing you to rigorously check training data and models for accuracy and potential biases before deployment, ensuring the data shaping your AI is fit for purpose.

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3. Will any of our data be used to train or improve your AI models, or shared with any external AI services?

Why customers ask: Organizations are highly protective of their proprietary and sensitive data. They demand clarity on whether their information, when processed by your AI, could be incorporated into general training pipelines for your models or exposed to third-party AI providers. These concerns are rooted in maintaining confidentiality, protecting intellectual property, and upholding privacy obligations.

How Pillar helps: Your answer must unequivocally state that customer data remains private, controlled, and is not used for general model training or shared externally beyond specifically contracted and secured services. Pillar Security helps you deliver this critical assurance by:

• Mapping and Controlling Data Flows: AI Discovery identifies all data pathways, while Adaptive Guardrails enforce policies at runtime, ensuring customer data isn't improperly used for training or shared beyond agreed-upon, secure interactions with third-party AI services.
• Providing Verifiable Oversight: AI Telemetry logs data interactions, offering an audit trail to demonstrate that your data handling practices align with your privacy commitments and contractual guarantees.

4. Are the AI’s decisions and outputs explainable or auditable, especially for high-stakes use cases?

Why customers ask: In many critical domains, a lack of transparency and explainability for AI-driven decisions presents significant regulatory, security, and operational concerns. Customers, and increasingly regulators, expect AI outcomes to be interpretable or traceable for accountability, to diagnose issues, and to ensure fairness. They need assurance that your AI isn't an inscrutable "black box," particularly when its behavior is unexpected or has significant consequences.

How Pillar helps: Your response needs to clearly describe your system's explainability features and the tools available for gaining insight, emphasizing comprehensive logging for forensic analysis. Pillar Security enables you to deliver this by:

• Providing Comprehensive Audit Trails with AI Telemetry: This is key. AI Telemetry logs detailed information for every AI decision, including input parameters, outputs, tool calls, and associated metadata. This creates a robust audit trail, allowing for forensic analysis to understand "why the AI did that," crucial for accountability and diagnosing issues in high-stakes scenarios.
• Mapping AI Components for Context with AI Discovery: By inventorying all AI assets (models, meta-prompts), AI Discovery helps provide context to the logs from AI Telemetry, aiding in understanding which components were involved in a decision, a prerequisite for any meaningful explanation.
• Monitoring and Alerting on AI Behavior: While not direct explainability tools, AI-SPM helps identify risks and Adaptive Guardrails monitor AI behavior in real-time. Logs from these systems, integrated with telemetry, contribute to a fuller picture for investigation if an AI acts unexpectedly, supporting the ability to shed light on its behavior.

5. What measures protect our data and privacy when it’s processed by your AI features?

Why customers ask: Customers must be confident that their data remains secure and private throughout all stages of AI processing. This includes assurances about robust encryption (in transit and at rest), strict access controls, effective tenant isolation in multi-tenant environments, and secure data handling practices, especially when interacting with any external AI services. Their primary goal is to prevent data leaks, unauthorized access, or breaches facilitated through your AI features.

How Pillar helps: To confidently address this, you need to showcase robust, consistently enforced security controls. Pillar Security provides the tools to both implement and transparently demonstrate these critical data protection measures by:

• Securing Data in Use: Our Adaptive Guardrails enforce runtime data security policies (like encryption and secure API calls), while RBAC restricts data access to authorized entities, logged by AI Telemetry.
• Proactively Identifying and Remediating Vulnerabilities: Pillar’s tailored AI Red Teaming simulates attacks to discover and help fix weaknesses in your AI systems' data processing and protection measures, including tests for data leakage or improper access, ensuring the robustness of tenant isolation.
• Verifying Security & Compliance: AI-SPM assesses data handling risks against policies and privacy standards, with AI Telemetry providing audit logs for verification.

6. Do you conduct regular security testing or audits specifically for your AI systems?

Why customers ask: Customers expect the same, if not a greater, level of diligence for AI security as they do for traditional software. This includes proactive and ongoing security validation through internal testing, AI-specific vulnerability assessments that considers unique AI attack vectors (like model and data poisoning), and potentially independent third-party audits to verify your security claims and controls.

How Pillar helps: Demonstrating a commitment to continuous AI risk identification and mitigation through a comprehensive security evaluation regimen is crucial. Pillar Security directly supports and enhances your ability to establish and maintain this critical process by: 

• Proactively Identifying and Mitigating AI Weaknesses through AI Red Teaming: Pillar’s Tailored AI Red Teaming rigorously tests your entire AI app stack—models, prompts, tools and downstream services —using dynamic threat modeling and simulated attacks. This uncovers vulnerabilities, verifies security boundaries and permissions, and ensures AI actions and outputs align with your business context, preventing data leaks, system takeover and irrelevant actions.
• Tracking Security Posture & Compliance with AI-SPM: Continuously assesses your AI systems against established security benchmarks, industry best practices, and regulatory requirements, managing risk based on test findings and providing a clear view of your AI security posture.
• Ensuring Comprehensive Test Scope with AI Discovery: Inventories all AI assets (models, data, prompts, APIs) to ensure that all critical components are included in the scope of security testing and audits, leaving no part of your AI ecosystem unchecked.

7. Do you use any third-party AI services or open-source models, and if so, how do you vet their security and reliability?

Why customers ask: Customers are increasingly aware of AI supply chain risks. They are concerned about potential data exposure to external providers, vulnerabilities embedded in open-source models, and the cascading risks from upstream dependencies. Understanding your vetting process for these components is crucial for them to assess the overall security of your AI offering.

How Pillar helps: Transparency regarding your AI supply chain and rigorous vetting processes is key. Pillar Security empowers you to confidently disclose this information and provide robust assurance by:

• Discovering All AI Components with AI Discovery: Provides transparency into your AI supply chain, inventorying third-party services and open-source models used within your systems.
• Assessing Third-Party Risk with AI-SPM: Evaluates the security and reliability of external AI components by scanning for known vulnerabilities and assessing their compliance with security best practices, including their track records and data protection agreements.
• Securing and Monitoring Interactions with Adaptive Guardrails & AI Telemetry: Enforces secure data handling policies when interacting with third parties and monitors their behavior for anomalies or deviations from expected conduct.
• Proactively Testing Integrations with AI Red Teaming: Identifies weaknesses in how third-party components are integrated into your system, ensuring that vulnerabilities in one component don't compromise the entire application.

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8. If your AI system can take actions autonomously, what guardrails ensure it cannot perform unauthorized or harmful operations?

Why customers ask: The prospect of autonomous AI agents making decisions and taking actions raises legitimate concerns about potential damage, misuse of resources, unauthorized operations, or unintended consequences. Customers need strong assurances that such AI autonomy is strictly bounded by robust safety mechanisms and oversight.

How Pillar helps: Your answer must clearly demonstrate that AI autonomy is carefully managed and safely constrained within well-defined boundaries. Pillar Security helps you articulate and implement these crucial safeguards by:

• Defining and Enforcing Action Limits with Adaptive Guardrails: Restricts AI agent actions to a narrow, approved scope based on predefined policies. Sensitive operations can be configured to require human approval or operate under stricter controls.
• Isolating Operations with Sandbox Environments: Provides controlled, isolated environments (sandboxes) for agentic systems to operate, enforcing least-privilege access to data and system resources to minimize potential impact from unintended actions.
• Monitoring Agent Behavior with AI Telemetry: Offers real-time oversight and detailed logging of agent actions, enabling rapid detection of and response to unexpected or potentially harmful behavior.
• Testing Agent Defenses with AI Red Teaming: Proactively identifies and helps fix vulnerabilities that could allow agents to bypass controls or perform harmful actions through simulated attacks specifically targeting agentic AI systems.

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9. How do you monitor your AI systems in real time to detect anomalies or misuse?

Why customers ask: Continuous oversight of AI systems in production is essential. Customers need assurance that you have mechanisms for the swift detection of operational issues, such as performance degradation, the emergence of unintended biases, critical errors, or signs of active attacks like adversarial inputs, prompt injections, or data exfiltration attempts orchestrated through the AI.

How Pillar helps: To provide this assurance, your answer must describe robust real-time monitoring and alerting capabilities. Pillar Security empowers this through its integrated solutions by:

• Enforcing Real-time Policy and Detecting Threats with Adaptive Guardrails: Pillar’s Adaptive Guardrails utilize risk detection and data classification engines to enforce safety and security policies during runtime interactions. They are designed to identify and block known threats, malicious inputs, and policy violations in real-time.
• Dynamically Adapting Defenses: The guardrails are not static; they continuously evolve by learning from red teaming exercises, insights from usage logs (via AI Telemetry), and Pillar’s threat intelligence feeds. This ensures defenses adapt to new threats and shifting application behaviors.
• Providing Context-Aware, Application-Specific Monitoring: Guardrails can be tailored to the unique context and business intent of each AI application, ensuring that monitoring is relevant and protection is optimized for specific functionalities and risk profiles.
• Capturing Detailed Logs for Anomaly Detection with AI Telemetry: AI Telemetry provides comprehensive logs of all AI interactions (inputs, outputs, tool calls, system behavior). This rich data can be analyzed by anomaly detection systems or reviewed by security teams to identify deviations from normal operational patterns that might indicate misuse, an attack, or an emerging issue.

10. What is your incident response plan if an AI-related security incident occurs?

Why customers ask: AI systems introduce novel attack surfaces and can be implicated in complex security incidents (e.g., model poisoning, adversarial attacks leading to harmful outputs, data breaches via exploited AI vulnerabilities, misuse of agentic capabilities). Customers need confidence that you possess a well-defined, tested, and AI-aware incident response (IR) plan to effectively manage such events, including clear communication protocols.

How Pillar Helps: A comprehensive answer will detail your IR plan's phases, emphasizing AI-specific considerations and procedures. Pillar Security helps you articulate and support a robust IR plan by:

• Enhancing Detection & Alerting with AI Telemetry & Adaptive Guardrails: AI Telemetry provides rich logs of AI interactions, while Adaptive Guardrails can flag and block anomalous or malicious behavior in real-time, providing early warnings crucial for rapid incident detection.
• Rapid Scoping and Analysis with AI Discovery & Telemetry: In the event of an incident, AI Discovery allows you to quickly identify all affected AI assets (models, datasets, prompts). AI Telemetry provides the detailed audit trails necessary for forensic analysis to understand the incident's scope, entry point, and impact.
• Containment Support via Adaptive Guardrails: Guardrails can be dynamically updated or configured to help contain an ongoing AI attack by blocking malicious inputs, restricting compromised AI agent actions, or isolating affected services.
• Informing Eradication and Recovery: Insights from Pillar's tools (e.g., identifying a poisoned dataset via AI-SPM findings or a compromised model version via AI Discovery) help ensure that the root cause is addressed during eradication and that systems are restored to a secure state.
• Post-Incident Learning & Hardening: Data from AI Telemetry and findings from AI-SPM and Red Teaming exercises can be used post-incident to refine security controls, update models, and improve the overall resilience of your AI systems against future attacks.

11. Are you compliant with relevant AI-related regulations and industry security standards, and how do you maintain that compliance?

Why customers ask: Adherence to regulatory requirements and industry standards is non-negotiable, especially in a rapidly evolving AI landscape with emerging frameworks like the EU AI Act and established ones like the NIST AI RMF. Clients need assurance that your AI practices are legally sound, ethically responsible, and will not expose them to compliance risks or liabilities.

How Pillar Helps: Demonstrating robust and ongoing compliance processes is paramount. Pillar Security helps you establish, maintain, and showcase this compliance by:

• Continuous Compliance Monitoring with AI-SPM: AI Security Posture Management allows you to assess your AI systems against specific regulatory frameworks (like NIST AI RMF, ISO 42001 controls relevant to AI) and internal policies. It helps identify compliance gaps and tracks remediation efforts.
• Evidence Collection and Reporting with AI Discovery & AI Telemetry: AI Discovery provides a comprehensive inventory of AI assets, and AI Telemetry offers detailed logs of AI operations and data handling. This information is crucial for generating compliance reports and providing auditors with verifiable evidence of your security and governance practices.
• Enforcing Policies Aligned with Regulations via Adaptive Guardrails: Adaptive Guardrails can be configured to enforce specific policies mandated by regulations, such as data usage restrictions, consent mechanisms, or fairness criteria, ensuring operational compliance.
• Supporting Data Governance and Privacy: Pillar's features help manage and protect data throughout the AI lifecycle, aligning with data privacy regulations like GDPR or CCPA by controlling data access, monitoring usage, and ensuring data isn't used for unapproved purposes.
• Facilitating Risk Management: By identifying vulnerabilities (AI Red Teaming), assessing risks (AI-SPM), and providing visibility (AI Discovery, AI Telemetry), Pillar Security supports the risk management processes that are foundational to most AI regulations and security standards.

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Building Trust in an AI-Powered Future

As AI systems become more powerful and pervasive, the demand for transparency, security, and accountability will only intensify.

Pillar Security is committed to empowering organizations like yours to navigate this complex landscape with confidence. Our unified suite of AI security solutions provides the visibility, control, and assurance needed to not only answer your customers' toughest questions but also to build more secure, resilient, and trustworthy AI-powered products and services.

Ready to strengthen your AI security posture and confidently address customer inquiries? Contact us today to discuss how we can help you secure your AI innovations.