In this webinar we take an unflinching look at the risks of AI — not to discourage adoption, but to equip organisations with the knowledge to deploy artificial intelligence responsibly, effectively, and in compliance with applicable regulations.
The Main Risks of Generative AI
Generative AI models are powerful, but they come with inherent risks that every organisation deploying them must understand:
1. Hallucinations
AI models can generate plausible-sounding but factually incorrect information — known as "hallucinations". In customer-facing applications, this can lead to misinformation, damaged customer trust, and even legal liability.
2. Bias and Discrimination
AI models trained on historical data can perpetuate and amplify existing biases. In HR applications, this can lead to discriminatory outcomes in recruitment or performance evaluation. In customer care, it can result in unequal service quality for different demographic groups.
3. Privacy and Data Protection
The use of AI systems raises significant questions under GDPR and other privacy regulations. What data is being processed? Where is it stored? Who can access it? Is personal data being used to train models?
4. Security Vulnerabilities
AI systems can be targets for adversarial attacks — attempts to manipulate AI responses through carefully crafted inputs. In enterprise deployments, this represents a genuine cybersecurity risk.
The EU AI Act: What Companies Need to Know
The EU AI Act came into force in 2024 and represents the world's most comprehensive AI regulation. The webinar covers the key implications for companies deploying AI systems:
- Risk classification: high-risk AI systems (HR, credit scoring, biometric identification) face strict compliance requirements
- Transparency obligations: users must be informed when they are interacting with an AI system
- Human oversight requirements: for high-risk applications, meaningful human review must be maintained
- Prohibited applications: certain AI uses are banned outright (social scoring, real-time biometric surveillance in public spaces)
Responsible AI Deployment with Crafter.ai
Crafter.ai is designed with responsible AI principles built in. The platform addresses the risks of AI through:
- RAG architecture: retrieval-augmented generation grounds AI responses in verified company documentation, dramatically reducing hallucination risk
- Human-in-the-loop: configurable escalation paths ensure human agents review sensitive interactions
- GDPR compliance: data residency in the EU, no training on customer data, full audit trails
- Conversation logging: complete records of AI interactions for audit and quality review
FAQ: Risks of AI
How can companies minimise AI hallucination risk? The most effective technique is Retrieval-Augmented Generation (RAG), which constrains the AI to answer only from verified sources. Crafter.ai's knowledge base functionality implements this by default.
What are the GDPR implications of deploying a customer-facing AI chatbot? The AI system qualifies as a data processor under GDPR. Companies must ensure they have a valid legal basis for processing, maintain processing records, and have a Data Processing Agreement with their AI provider.
Is there a legal requirement to disclose that a chatbot is an AI? Yes — under the EU AI Act and general transparency principles, users must be informed they are interacting with an AI system. Crafter.ai includes configurable disclosure messages by default.