While 51% of enterprises worldwide are allocating at least 5% of IT budgets to AI, only 26% consider themselves advanced in operationalizing it, according to FPT.
This is from a report based on a survey of 397 business and technology decision-makers globally, supported by in-depth interviews with senior executives across North America, Europe, Asia-Pacific and Japan.
The study was conducted by Forrester Consulting and covered industries including automotive, financial services, healthcare, manufacturing, energy and sports.
Findings show that AI is largely deployed to drive operational gains – with automation and cost reduction among primary drivers, but relatively few are yet redesigning their business models around AI, with only 34% pursuing an AI-first operating model.
As organizations push toward more ambitious use cases, constraints become more structural. The research points to integration complexity (41%) and data silos (38%) as the most significant barriers to operationalizing AI, particularly in data- and operations-intensive environments
Beyond technology, only 39% of enterprises report meaningful progress in aligning strategy, governance, and operating models – highlighting a broader imbalance between AI ambition and organizational readiness, limiting the ability to scale AI in a consistent and controlled way.
At the same time, organizations are still struggling to measure AI impact in a way that supports scaling decisions. Notably, 35% of them do not collect quantified metrics at all, and 10% do not measure AI outcomes in any form, making it difficult to identify which initiatives should be scaled and which should be deprioritized.
As a result, even high-potential use cases risk stalling in pilot phases without clear pathways to enterprise-wide adoption.
In response, enterprises are rethinking how they scale AI – not as isolated deployments, but as coordinated systems across the full lifecycle. When selecting partners for enterprise AI, they increasingly prioritize the ability to engineer, deploy, and operate AI systems at scale across the full lifecycle (48%), supported by strong governance and security capabilities (48%) and the ability to integrate seamlessly with existing systems (47%).
Regional preferences reflect this shift, with demand for full lifecycle capabilities particularly strong in North America (59%) and Europe, the Middle East and Africa (54%), while APAC and Japan’s organizations place greater emphasis on end-to-end strategic and execution support.
This signals a broader transition toward partnership models that enable co-innovation and repeatable execution – a critical step for enterprises seeking to move beyond pilots and unlock sustained, enterprise-wide value from AI.
“As AI ecosystems become more complex, organizations can no longer move forward in silos—they need partners who can bridge strategy, integration, governance, and operations to turn innovation into repeatable, enterprise-wide execution,” said Pham Minh Tuan, EVP of FPT and CEO of FPT Software.
FPT’s AI-first approach is supported by its AI platform, FleziPT, as well as a global team of more than 30,000 AI-augmented engineers, AI Factories in Vietnam and Japan, and collaborations with global AI leaders to accelerate innovation and delivery at scale.
This enables FPT to scale AI deployment through tailored solutions that enhance speed, scalability, and traceability, resulting in up to 60% optimized development time, over 50% less rework, and a 30% uplift in developer productivity.
