𝟱 𝗣𝗶𝘁𝗳𝗮𝗹𝗹𝘀 𝗢𝗳 𝗚𝗲𝗻𝗔𝗜 𝗜𝗻 𝗜𝗻𝘁𝗲𝗿𝗻𝗮𝗹 𝗔𝘂𝗱𝗶𝘁
Many AI projects fail. They fail because teams rush the setup. They ignore the actual workflow.
Avoid these five mistakes to save time.
- No clear goals. Do not use AI because it is a trend. Define the problem first.
- Reduce detection time from 30 days to 24 hours.
- Increase scanning coverage to 95%.
- The black box. Do not trust a model you do not understand.
- Ask for training data documentation.
- Require evidence for every alert.
- Keep the ability to tune the model.
- Poor integration. AI should not be a separate report. It must fit your daily work.
- Add AI checks to GitHub or GitLab.
- Put findings in your sprint backlog.
- Block risky deployments automatically.
- Dirty data. Bad data produces bad results. Audit your data first.
- Standardize your log formats.
- Link code commits to incidents.
- Ensure you have six months of quality data.
- Too much trust. Do not let AI make final decisions alone.
- First 3 months: AI suggests, humans decide.
- Next 3 months: AI handles low risk, humans handle high risk.
- After 6 months: AI handles routine tasks.
AI does not replace human judgment. It helps you find patterns faster. Combine AI with your expertise for the best results.
Optional learning community: https://t.me/GyaanSetuAi