Accelerating accounting workflow automation with AI — lessons from real projects

When we started applying AI to accelerate accounting workflow automation, the first thing we realized was: input data matters more than the algorithm. A good AI pipeline running on bad data still produces bad results.

The data preparation phase — cleaning, normalization, classification — typically accounts for 60 to 70 percent of total project time. It is unglamorous work but determines the quality of everything that follows.

Once past that stage, results usually arrive faster than expected. The businesses we have supported with accounting workflow automation typically see measurable outcomes within 8 to 10 weeks of the system going live.

Share