Configit Tech Chat Puts Manufacturing AI Adoption on Data Access and Configuration Control

Manufacturing AUTOMATION’s July 17 feature previews Damantha Boteju’s discussion of introducing AI across operations and Configit’s configuration lifecycle management positioning.

Manufacturing AUTOMATION has published a Tech Chat feature centered on Configit Chief Product and Technology Officer Damantha Boteju’s views on AI implementation and configuration work on and off the factory floor.

The discussion frames reliable, accessible organizational data as a prerequisite for manufacturers that want to use AI in operational processes. Boteju is also set to address how companies can introduce AI across the business and how Configit differentiates its configuration lifecycle management approach.

For plant and operations leaders, the immediate takeaway is that AI deployment depends less on selecting a model than on whether product, engineering, commercial, service, and manufacturing data can be accessed and governed consistently. Configuration data can determine which parts, options, rules, and constraints apply to a specific product or customer order. If those records are incomplete or disconnected between systems, AI tools can produce recommendations that conflict with engineering rules, available manufacturing options, or approved commercial configurations.

That makes integration the practical issue behind the discussion. A manufacturer considering AI-supported configuration work would need to determine how product lifecycle management, enterprise resource planning, customer relationship management, manufacturing execution, and service records exchange configuration data. The company would also need ownership for rules, version control, approvals, and changes made after products enter production or the field.

Configit’s emphasis on configuration lifecycle management positions the company in a market where manufacturers are trying to manage complexity across configurable product portfolios. The relevant operational question is whether configuration controls reduce manual review, engineering rework, order errors, or delays in releasing accurate production information. Those outcomes can affect cycle times from quotation through engineering release and production scheduling, but Manufacturing AUTOMATION’s feature does not provide throughput figures, deployment scale, pricing, customer results, or payback periods.

Uncertainty remains substantial. The feature is a trade-publication Tech Chat preview and does not provide independent evidence that Configit’s approach improves configuration accuracy, AI performance, factory throughput, or return on investment. It also does not specify the format of the conversation beyond identifying it as a Tech Chat. Manufacturers evaluating similar tools should treat the discussion as a view into Configit’s market positioning rather than a demonstrated operating result.