Smart factories face AI vendor proliferation where every product company adds modules that increase subscriptions without clear value. Organizations standardize on enterprise platforms as controlled playgrounds rather than chasing vendor AI capabilities, while others struggle with poor input data quality that undermines tool effectiveness. Lead exposure drives battery manufacturers toward automated lines with digital twins and control rooms, but legacy equipment running serial connections cannot support cloud-connected architectures.

Governance requires practical boundaries that democratize AI usage while protecting sensitive data and managing bias risks.

In this session, the panel of experts will share insights on:

• Platform standardization strategies that avoid subscription sprawl by selecting trusted enterprise tools over vendor-specific modules;
• Data quality challenges where poor input undermines AI tool effectiveness regardless of capability;
• Multi-pillar security models that wrap protection around automated lines, control rooms and cloud-transmitted factory data.