Terex Names Namita Jindal Chief AI & Data Officer
The role spans enterprise data management and AI deployment
Terex Corporation recently appointed Namita Jindal as Senior Vice President and Chief AI & Data Officer, effective January 19, 2026. Jindal will report to Simon Meester, President and CEO, and serve on Terex’s executive leadership team.
The announcement from Terex mentions that Jindal’s scope includes leadership over AI and data systems across the company. She joins Terex from CentralSquare Technologies, where she served as Chief Information Officer since 2021. Prior to that, she spent more than a decade in digital leadership roles including as CIO for the Honeywell Intelligratedautomation division, where she was responsible for systems critical to warehouse and material-handling operations.
The role consolidates oversight for data infrastructure, analytics, and AI development.
Industrial AI Use Cases and System Integration
One of the most widespread applications in industrial sectorsis predictive maintenance, where machine learning algorithms analyze sensor data to identify signs of wear, degradation, or impending failure. Systems ingest vibration, temperature, acoustic, and other signals to produce maintenance insights that help schedule interventions before unplanned breakdowns occur.
Manufacturers and automation providers also deploy AI for quality inspection and defect detection on production lines, where vision models can catch anomalies in real time. In logistics and materials handling, AI-driven forecasting and scheduling tools assist in optimizing inventories, routing, and warehouse flows. Academic literature underscores diverse AI applications in manufacturing, including shop-floor monitoring, interfirm coordination, and process control, though it also highlights integration challenges such as data quality, system interoperability, and workforce readiness.
Industrial environments differ from purely software domains because AI systems must connect with operational technology and physical machines. This necessitates robust engineering, system safety protocols, and governance to ensure reliability and compliance with industrial standards. Industrial AI solutions must meet stringent requirements for uptime, safety, and performance even as they process high volumes of real-time data across manufacturing plant floors.
Executive Responsibility in Industrial AI
Industrial AI initiatives often span traditional organizational boundaries. Data management, analytics, cybersecurity, engineering, and operations must coordinate to scale AI models from pilots to production systems. Centralizing responsibility for AI and data under an executive role like Chief AI & Data Officer gives that leader authority to define data standards, oversee architecture decisions, and coordinate across historically siloed functions.
Companies such as Siemens AG have similarly elevated AI leadership roles. Siemens recruited a senior AI expert from Amazon in 2025 to lead data and AI across its industrial software and automation businesses, reflecting a strategic focus on linking AI capabilities directly to engineering and production systems.
Similarly, other industrial firms are expanding executive oversight of AI as they integrate advanced analytics into product development, manufacturing, and logistics. For example, Volkswagen Group has announced multibillion-euro investments in AI across its vehicle engineering and factory operations, with hundreds of existing internal AI applications, though not all directly comparable to Terex’s industrial equipment context.
Terex’s AI and Data Leadership
Jindal’s professional experience aligns with environments where software, controls, and analytics support continuous operations. At Honeywell Intelligrated, her work involved integrating complex software systems with hardware and control logic in warehouses and fulfillment centers. At CentralSquare, she led enterprise technology for public-sector clients. These backgrounds suggest acclimation to technical and operational complexity rather than a narrow focus on generative AI application development.
Terex has not disclosed specific deliverables, timelines, or performance targets associated with the new role. The broader practice of adding executive titles tied to AI and data is a recognition that these capabilities intersect with multiple facets of industrial system operations and corporate data strategy.