FPT seals $30M AI partnership to build smart factories across Southeast Asia starting 2025

FPT signs $30M AI deal to modernize manufacturing across Southeast Asia starting 2025. A phased roadmap boosts efficiency, data-led decisions, and self-optimizing ops.

Published on: Sep 21, 2025
FPT seals $30M AI partnership to build smart factories across Southeast Asia starting 2025

FPT signs $30M AI deal to modernize manufacturing across Southeast Asia

FPT Corporation has signed a multi-year, $30 million strategic agreement with one of Southeast Asia's largest industrial conglomerates. The program starts in 2025 and will roll out AI across the client's regional manufacturing operations. The focus: measurable efficiency, smarter decisions, and a future-ready factory model.

This collaboration signals a step-change for industrial modernization in the region. It connects plant-floor data, business operations, and back-office processes under one AI-driven model.

Three-phase AI roadmap

  • Phase 1 (2025): Build the AI foundation
    Deploy OCR for document processing, digitize manufacturing workflows, integrate machine and sensor data, and apply computer vision for safety and attendance.
  • Phase 2 (2026): Drive operational intelligence
    Use AI for forecasting, optimization, and scenario planning across procurement, production, and workforce management to support faster, data-led decisions.
  • Phase 3 (2027+): Move to self-optimizing operations
    Adopt digital twins, AI assistants, autonomous agents, and conversational AI to streamline operations and improve customer service.

Why it matters for leaders, IT, and developers

  • Data readiness: Map data sources (ERP, MES, QMS, SCADA). Standardize schemas and unify identity across systems. Prioritize high-signal data tied to core KPIs.
  • MLOps at scale: Establish pipelines for ingestion, feature stores, model training, CI/CD, and monitoring. Bake in drift detection and feedback loops.
  • Computer vision safety: Start with clear policies, labeled datasets, and defined alert thresholds. Validate against real incident data before scaling.
  • Digital twins: Ensure accurate asset models, live telemetry, and version control. Align use cases to maintenance, throughput tuning, and energy optimization. See: NIST on Digital Twins.
  • Governance and risk: Set data retention, access controls, and audit trails. Use an AI risk framework to track model intent, safety, and impact. Reference: NIST AI RMF.
  • Change management: Define new roles (AI product owner, data steward). Train operators and analysts to work with AI insights and agents.

Expected outcomes to track

  • OEE uplift and reduced unplanned downtime via predictive maintenance and scheduling.
  • Shorter cycle times and scrap reduction through process optimization.
  • Higher forecasting accuracy and improved service levels.
  • Procurement cost and lead-time reductions from smarter planning.
  • Fewer safety incidents with proactive CV monitoring.
  • Back-office automation gains in invoice processing, reporting, and support.

What FPT will deliver

With over two decades in manufacturing, FPT will implement AI across the full value chain-operations, plant performance, and back-office functions. The plan blends workflow digitization, machine data integration, and decision automation to create an intelligent, efficient production model.

Levi Nguyen, CEO of FPT Thailand, said the partnership reflects a shared vision to build factories of the future, adding that FPT is committed to leading industrial AI adoption across Southeast Asia.

FPT's regional footprint

FPT serves seven ASEAN countries with several thousand professionals. The company supports enterprises across manufacturing and other sectors including banking and finance, retail, automotive, healthcare, energy, consumer goods, and aviation.

Past regional partnerships include AIA, Central Group, Honda, IHH Healthcare Singapore, Mitsubishi, Panasonic, RS Group, SCB, and Unilever-showing a track record across complex, high-scale environments.

Next steps for your team

  • Prioritize two to three high-ROI use cases tied to clear KPIs and data availability.
  • Stand up a secure data platform with role-based access and lineage from day one.
  • Pilot, measure, then scale-avoid proof-of-concept sprawl without production paths.
  • Invest in skills: data engineering, MLOps, prompt design, and CV/IoT integration. Explore role-based programs at Complete AI Training.