AI isn't perfect. Knowing the risks helps you implement safely. Here's what can go wrong and how to prevent it.
Key AI Risks
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Get Free Analysis → No signup required • Results in 30 seconds| Risk | What Happens | Mitigation |
|---|---|---|
| Errors/ Hallucinations | AI gives wrong answers confidently | Human oversight, fact-checking |
| Over-automation | Removing humans from decisions they should make | Keep humans in critical loops |
| Data security | Sensitive data exposed to AI platforms | Enterprise tools, access controls |
| Staff resistance | Team doesn't adopt or actively resists | Change management, communication |
| Dependency | Can't operate if AI fails | Backup procedures, alternatives |
| Bias | AI reflects biases in training data | Diverse testing, monitoring |
Risk: AI Errors
AI generates plausible but incorrect outputs:
- Cause: Ambiguous prompts, training data gaps, model limitations
- Prevention: Test thoroughly, human review for important outputs
- Recovery: Easy correction workflow, feedback loops
Risk: Over-Automation
Automating things that need human judgment:
- Cause: Over-enthusiasm, cost-cutting pressure
- Prevention: Define what AI shouldn't touch
- Principle: AI executes, humans decide
Risk Mitigation Framework
- ☐ Define high-risk vs. low-risk processes
- ☐ Human oversight for all high-risk areas
- ☐ Test thoroughly before deployment
- ☐ Monitor outputs continuously
- ☐ Have rollback plans ready
- ☐ Train team on escalation procedures
- ☐ Choose secure, enterprise platforms
How Greene Solutions Manages Risk
353+
Implementations with zero critical failures
100%
Human oversight on high-stakes processes
Always
Rollback plans in place
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