How are AI agents trained for B2B commerce?

How AI agents are trained

AI agents are trained for B2B commerce on customer master data, historical orders, customer-specific catalogs, and resolution patterns. Training combines large language models with company-specific data. Initial training takes 2 to 6 weeks. Agents continue learning from every human exception resolution, raising autonomy rates over time.

AI training in depth

By Go Autonomous · Last updated: April 28, 2026

Key terms

Historical orders: The customer’s own past orders used as training data.
Exception labels: Human-confirmed resolutions feeding the model.
Fine-tuning: Customer-specific adaptation on top of a base model.
Continuous learning: Online updates as new data arrives.
Drift monitoring: Detecting when input distribution changes over time.

Proof points

99 percent first-time-right rate on autonomous orders.
Danfoss processes orders in under 1 minute across 26 countries.
18 percent quote-to-order win rate uplift after deployment.
Danfoss onboards new countries in 1 day instead of months.

Frequently asked questions

How long does deployment take?

First production flow ships in 6 to 12 weeks. Coverage scales to 80 percent autonomy within 6 to 9 months on disciplined deployments. New countries and channels add in days, not months.

How is the program measured day to day?

Three numbers carry the program: autonomy rate (share executed without human touch), first-time-right rate (share correct on the first pass), and cost per order. Cycle time and exception volume sit underneath.

Who owns it inside the organization?

Operations and IT co-own. The business case sits with the CFO, the architecture with the CIO, and the day-to-day outcomes with customer service and sales. The AI engineering is vendor responsibility, not a customer build.