FPT Corporation has released a global study titled “From Pilots to Reusable Platforms: A Blueprint for Scaling Enterprise AI,” highlighting the growing gap between AI experimentation and enterprise-wide deployment. The research, conducted by Forrester Consulting, underscores that while 51% of organizations allocate at least 5% of IT budgets to AI, only 26% consider themselves advanced in operationalizing it. This shift signals a critical need for structured frameworks to bridge AI ambition with execution.
Key Findings: AI Adoption Outpaces Operational Readiness
The study surveyed 397 business and technology decision-makers across North America, Europe, Asia Pacific, and Japan, covering industries such as automotive, financial services, healthcare, manufacturing, energy, and sports. Despite increased AI investment, operationalization remains uneven. Automation and cost reduction drive most deployments, yet only 34% of enterprises pursue an AI-first operating model. Structural barriers include integration complexity (41%) and data silos (38%), particularly in data-intensive sectors like energy. Additionally, 35% of organizations lack quantified metrics to evaluate AI impact, stalling high-potential use cases in pilot phases.
FPT’s AI Strategy: Full Lifecycle Support and Governance
FPT’s approach centers on its AI platform, FleziPT, and a global team of 30,000+ AI-augmented engineers. The company’s AI Factories in Vietnam and Japan, alongside partnerships with global AI leaders, enable scalable deployment with up to 60% optimized development time and 30% higher developer productivity. FPT CASAN, a five-level AI-native framework (Curious, Augmented, Standard, Automatic, Native), provides a roadmap for transitioning from fragmented experimentation to enterprise-wide AI integration. This methodology emphasizes governance, traceability, and measurable business outcomes, aligning with the study’s call for coordinated systems over isolated deployments.
Regional Priorities and Partnership Demands
Enterprises increasingly prioritize partners capable of full lifecycle AI support (48%), governance and security (48%), and seamless system integration (47%). North American and EMEA organizations emphasize lifecycle capabilities, while APAC and Japan focus on strategic and execution support. This divergence reflects a broader shift toward co-innovation models, where partnerships play a pivotal role in translating AI pilots into scalable, repeatable solutions.
Key Takeaways
- 51% of organizations allocate at least 5% of IT budgets to AI, but only 26% are advanced in operationalizing it.
- Integration complexity (41%) and data silos (38%) are the top barriers to scaling AI in enterprise environments.
- FPT’s FleziPT platform and CASAN methodology aim to reduce development time by 60% and rework by 50%.
EnergyInsyte's Take
This study underscores a pivotal moment for energy executives and infrastructure stakeholders: AI’s potential hinges on operational discipline, not just innovation. While energy firms may lead in data-intensive applications, the sector’s complex regulatory and operational landscape amplifies risks of fragmented AI adoption. FPT’s emphasis on governance and lifecycle support aligns with the industry’s need for resilient, scalable systems. In our view, energy organizations must prioritize partnerships that bridge technical integration with strategic execution to avoid pilot purgatory and achieve measurable ROI. The path forward demands a balance of ambition and pragmatism—scaling AI as a core operational capability, not a standalone experiment.
Source: Businesswire
