Scenario and roles
Who does what, and where a person checks the result.
Build AI into the team's work. Scenario, integration, pilot, training and quality control, so the pilot becomes everyday work.
Sound familiar?AI tools are used manually and in scattered ways, The scenario has no owner and no quality criterion, Pilots don't turn into everyday work
AI and Technology
Who does what, and where a person checks the result.
Which systems the tool is built into and how errors are handled.
Recording every case where a person had to step in.
Spot checks and a response plan when quality drops.
Implementing AI takes more than choosing a model. It also takes a process, data, an interface, controls and training. A pilot without a stop criterion named in advance almost always ends with "promising overall" and never goes into production.
AI built into a working process.
Named limits for automated decisions.
A total cost of ownership estimate, including control.
The cost of waiting
The pilot will stay an experiment.
Customers or the manager will be the ones to find the errors.
The team will lose trust in the tool.
time, cost, number of errors.
their share and trend.
whether people work with the tool every day.
Four to six weeks. Longer means the task was chosen too large.
A named person in the process throughout the pilot, and after that by sampling.
Before the start, decide which data can be passed to the tool and where it's processed.
Services: AI Consulting · AI in Workflows · Process Automation
When the model stops working
From the inside, it's hard to tell a temporary downturn from an exhausted model, and a mistake either way is expensive. This is a set of signs that help tell them apart.