𝟱 𝗖𝗿𝗶𝘁𝗶𝗰𝗮𝗹 𝗠𝗶𝘀𝘁𝗮𝗸𝗲𝘀 𝗪𝗶𝘁𝗵 𝗔𝗱𝗮𝗽𝘁𝗶𝘃𝗲 𝗔𝗜 𝗜𝗻 𝗙𝗶𝗻𝗮𝗻𝗰𝗲

𝟱 𝗖𝗿𝗶𝘁𝗶𝗰𝗮𝗹 𝗠𝗶𝘀𝘁𝗮𝗸𝗲𝘀 𝗪𝗶𝘁𝗵 𝗔𝗱𝗮𝗽𝘁𝗶𝘃𝗲 𝗔𝗜 𝗜𝗻 𝗙𝗶𝗻𝗮𝗻𝗰𝗲

Finance teams set big goals for AI. They want to automate everything. Many fail. They get bad models. They lose money. Avoid these errors.

Mistake 1: Too Much Scope Do not fix everything at once. Big projects take too long. You see no results. Pick one small process. Example: One vendor group. Aim for high accuracy in 90 days. Then grow.

Mistake 2: No Maintenance AI is not a set and forget tool. Business changes. Suppliers change formats. Models drift. Accuracy drops. Track metrics weekly. Check exception rates. Review models every quarter.

Mistake 3: Bad Data Do not use a few months of data. Do not use dirty data. AI learns from what you give it. You need 12 to 18 months of history. Clean your vendor records. Fix your GL codes first.

Mistake 4: Ignoring People Do not ignore your staff. Your AP and AR teams use the tool. If they hate it, they will avoid it. Involve them on day one. Let them flag errors. Use their feedback to train the AI.

Mistake 5: No Audit Trail Do not use a black box. Audit teams need answers. "The AI did it" is not an answer. Log every decision. Keep version control. Set human review limits.

Adaptive AI works with a plan. Start small. Involve your team. Clean your data. Monitor results. Stay compliant.

Source: https://dev.to/edith_heroux_aca4c9046ef5/5-critical-mistakes-when-implementing-adaptive-ai-architecture-in-finance-1l7n Optional learning community: https://t.me/GyaanSetuAi