Securing the Introduction of AI on Your E-Commerce Website

With the rise of digital engagement, users are increasingly favoring a conversational agent integrated directly into e-commerce platforms. Studies show that 80% of e-commerce businesses already use or plan to deploy chatbots to assist their customers. According to Gartner, 85% of customer interactions could be handled by AI by 2025. These tools can drive:

▪️ 36% of product recommendations via chatbot

▪️ 20% reduction in cart abandonment

▪️ 70% higher customer engagement through conversational assistants

Risks and Threats

Introducing AI chatbots on e-commerce sites, while improving the customer experience, also creates new risk vectors:

1️⃣ Data leakage: storage of logs and personal data with potential for exfiltration or exposure

2️⃣ Prompt-injection attacks that allow an attacker to influence the AI’s behavior

3️⃣ Malicious use: creation of fake chatbots or phishing via smishing, deepfakes, disinformation campaigns

4️⃣ False sense of trust: users may inadvertently share sensitive information

The Thales Response: Reasserting Control Over Your AI Assets

To help e-commerce players secure and govern their AI initiatives, Thales offers full control of the AI lifecycle - from asset management to cyber risk management - through:

1️⃣ Inventory & Classification of AI Assets

📌 Regain governance over integrated AI models (chatbots, recommendation engines, etc.)

📌 Leverage Watsonx.governance to centralize and inventory all models, pipelines, and dependencies

2️⃣ Analysis of AI Risks & Threats

📌 Identify front-end applications at risk of manipulation (via prompt injection, RAG attacks, etc.)

📌 Evaluate compromise scenarios—exfiltration, response tampering, code injection - using Guardium AI Security

3️⃣ Implementing Security Controls

📌 Secure proxy & prompt filtering: safeguard the chatbot entry point via Watsonx.governance

📌 Continuous model monitoring: detect AI anomalies (prompt injection, statistical drift) using Guardium

📌 Access management & logging: ensure traceability of requests and actions, and audit all changes

4️⃣ Testing, Validation & Hardening

📌 Simulate AI attack scenarios (e.g., malicious injection, chatbot-driven phishing)

📌 Run endurance and regression tests covering paraphrasing, filter bypass, and code injection

5️⃣ Governance & Compliance

📌 Define and enforce AI policies in line with GDPR, NIS2, etc.

📌 Automate reporting on usage, access and incidents

📌 Establish a periodic review cycle for AI models and their risk profiles

This comprehensive framework lets e-commerce businesses fully leverage AI’s advantages while securing their platforms and protecting customer data.