For brands outsourcing CX operations, trusting the right BPO partner is critical. How can companies balance AI-driven innovation with robust data protection? And how can they avoid hidden security risks while ensuring employees have the right AI tools to work efficiently?
AI and GenAI: A new frontier for data privacy risks
AI thrives on vast amounts of data, but when that data includes customer interactions, transaction histories and personally identifiable information (PII), security becomes a top concern. For brands working with a CX outsourcing partner, ensuring AI is secure by design is integral to protecting both customer trust and compliance.
Key privacy risks in AI-powered CX
- AI systems process massive datasets, increasing the risk of sensitive information being stored or accessed inappropriately.
- If AI models are trained on customer data, what safeguards exist to prevent data from being retained, misused or exposed?
- Generative AI models can create responses that aren’t easily explainable, making it difficult to ensure accuracy and compliance.
- Many AI-powered CX solutions integrate third-party AI tools, creating additional risk points.
Shadow AI: The hidden risk companies shouldn’t ignore
One of the risks in AI adoption is shadow AI — when employees use public generative AI models (such as ChatGPT or Gemini) without IT approval. While these tools are useful, they can pose significant security threats.
- Employees may unknowingly input sensitive information into public AI models that retain or reuse data.
- Shadow AI bypasses regulations like GDPR and CCPA, which require strict control over customer data.
- AI-generated responses can sometimes be inaccurate or misleading, leading to AI hallucinations that can negatively impact CX outcomes.
According to a recent report from Cyberhaven, 73.8% of ChatGPT use at work is through non-corporate accounts. And the percentages for Gemini and Bard are even higher at 94.4% and 95.9%, respectively. The volume of corporate data sent to AI is increasing, but even more notable is the percentage of sensitive data is also increasing — 10.7% in March 2023 vs. 27.4% a year later. The top sensitive data types, according to the report, include customer support ticket information, research and development material, HR and employee records, and financial documents.
To combat shadow AI, companies must provide secure, enterprise-approved alternatives, so employees can work smarter without compromising security.
EverGPT: A secure, enterprise AI tool for CX operations
To address shadow AI risks, Foundever® developed EverGPT, an AI-powered productivity assistant designed to enhance employee efficiency without exposing customer data. By providing a secure, company-approved AI tool, EverGPT ensures employees have the right technology at their fingertips, without resorting to shadow AI. EverGPT is built for security and hosted on Foundever’s private infrastructure. Fully integrated into CX workflows, it streamlines multilingual translation, data summarization and input validation to help teams work more efficiently.
Intelligence in action
EverGPT is just one example of how Foundever leverages its comprehensive AI suite — EverSuite — to power secure, human-centered customer experience transformations. EverSuite AI goes beyond automation to accelerate enterprise transformation, enable intelligent self-service, and close the gap between customer expectations and what brands can deliver. With agent-empowering AI tools, agentic automation, and integrated solutions, EverSuite drives productivity, performance, and engagement, while always prioritizing data security and compliance.
Key compliance considerations for AI in CX
Regulations like GDPR and CCPA set strict requirements for data minimization, encryption and transparency. But AI regulations are constantly evolving. In recent years, GDPR-inspired laws have been adopted in 26 countries and counting. And, with governments worldwide introducing new laws to protect consumer data, businesses must ensure their AI-powered CX solutions comply with current and future standards.
The Future of Privacy Forum recently shared some insights about what to expect in global privacy in 2025.
AI governance beyond GDPR: The EU has moved beyond just data protection to regulate multiple dimensions of the digital economy, including AI governance, online platforms, content moderation and algorithmic transparency. Businesses should anticipate stricter regulations covering AI decision-making, consumer transparency and systemic risks.
Self-determination and AI privacy: Regulatory discussions are increasingly focused on consumer autonomy and control over personal data. The European Data Protection Board (EDPB) has emphasized the need for AI systems to offer users an “unconditional opt-out” and stronger safeguards against the overuse of personal data for AI model training.
AI security and vendor scrutiny: With AI models becoming more deeply integrated into customer interactions, regulators are expected to tighten scrutiny on third-party AI vendors. Companies will need to ensure AI partners comply with international standards, avoiding risks tied to data misuse and security vulnerabilities.
Varying AI compliance speeds across regions: AI legislation is evolving at different paces worldwide. While Europe focuses on implementing the AI Act, Latin America is accelerating AI regulations and APAC countries may moderate their approach. Companies operating in multiple regions must tailor their compliance strategies accordingly.
Cross-border data transfers and AI compliance: The debate over AI-driven data transfers is expected to intensify, influenced by geopolitical tensions and privacy regulations. Companies deploying AI-powered CX solutions across different markets must prepare for new restrictions and evolving international data transfer frameworks.
Choosing a BPO that puts AI security first
Not all CX outsourcing providers have the AI security expertise necessary to protect customer data. Partnering with a BPO that prioritizes AI security and compliance is critical to keeping customer data protected while leveraging AI’s full potential. Executives must ask the right questions before selecting a partner.
What to look for in an AI-ready BPO:
- Secure, enterprise-grade AI tools: Does the BPO provide internal AI solutions to eliminate shadow AI risks?
- End-to-end AI security measures: How does the company handle data encryption, access control and AI model security?
- Regulatory compliance expertise: Does the BPO have AI governance policies that align with GDPR, CCPA and emerging AI laws?
- AI bias and accuracy monitoring: What checks and balances exist to ensure AI-driven CX is fair, accurate and unbiased?
- Clear generative AI adoption roadmap: How transparent is the potential partner’s strategy for adopting and implementing generative AI?
- Data protection and validation: What safeguards are in place to ensure data used for AI model training and security enhancement is properly protected and validated?
- Cyberattack preparedness: How well is the organization equipped to handle increasingly sophisticated cyber threats influenced by generative AI?
- Proactive cybersecurity with AI: What are the company’s plans for leveraging generative AI to enhance cybersecurity measures proactively?
- Empowering employees against cyber threats: How is GenAI integrated into strategies to strengthen employee awareness and defense against cyber risks?
- Security culture: Does the BPO have security awareness built into its company culture, with continuous communication, training and accountability?
Key takeaways for CX leaders
AI is reshaping customer experience, but without strong privacy and security measures, businesses risk losing customer trust and facing regulatory penalties. Choosing the right CX outsourcing partner means ensuring security is built into every layer of AI-driven operations.
For a deeper dive into best practices, key considerations and expert guidance on safeguarding customer trust in an era of heightened cyber threats, read our whitepaper “Securing your customer experience.”