More than half of enterprises now allocate at least 5% of IT budgets to artificial intelligence, yet only 26% describe themselves as advanced in putting AI into operation, according to a Forrester Consulting study commissioned by FPT Corporation. The gap between spending and scaled deployment leaves many organizations stuck in pilot mode despite rising investment.
The research surveyed 397 business and technology decision-makers across North America, Europe, Asia Pacific, and Japan, with senior executive interviews included. Industries ranged from automotive and financial services to healthcare, manufacturing, energy, and sports. AI remains focused on automation, cost reduction, and operational tasks, while 34% of respondents said their organizations were pursuing an AI-first operating model.
Integration and data silos block progress
Integration complexity was named as a challenge by 41% of respondents, and 38% cited data silos. Another 39% reported meaningful progress in aligning AI strategy, governance, and operating models. For executives and managers, these findings reinforce the need for disciplined AI for Management approaches that tie technical capabilities to business processes.
Measurement remains a weak point. The study found that 35% of respondents do not collect quantified metrics for AI initiatives, and 10% do not measure AI outcomes at all. Without clear metrics, deciding which projects to expand or deprioritize becomes guesswork.
What enterprises want from external partners
When selecting external AI partners, 48% of respondents prioritized the ability to engineer, deploy, and operate AI systems across their full lifecycle. The same percentage pointed to governance and security capabilities. Integration with existing systems was a priority for 47%.
Regional differences emerged. Full-lifecycle AI capabilities were prioritized by 59% of North American respondents and 54% in Europe, the Middle East, and Africa. Organizations in Asia Pacific and Japan placed greater weight on strategic and execution support throughout the deployment process.
Linking strategy, integration, and operations
Pham Minh Tuan, executive vice president of FPT Corporation and CEO of FPT Software, said organizations need to treat AI strategy, integration, governance, and operations as a single challenge rather than separate workstreams. "Organizations can no longer move forward in silos-they need partners who can bridge strategy, integration, governance, and operations," he said.
FPT, which commissioned the study as part of its enterprise AI business, operates the FleziPT AI platform and AI facilities in Vietnam and Japan. The company claims its AI-supported development processes have reduced development time by up to 60%, cut rework by more than 50%, and increased developer productivity by 30%. FPT did not provide methodological details for those figures. It has also introduced FPT CASAN, a methodology that assesses organizations at five levels of AI adoption: Curious, Augmented, Standard, Automatic, and Native. The framework is designed to evaluate AI readiness, governance, and deployment across business functions, aiming to help companies move from isolated experiments to broad operational use.
Why this matters for executives and strategy
The study confirms that AI spending is growing, but the operational payoff remains elusive. The absence of quantified metrics in more than a third of organizations means that investment decisions often lack a clear ROI basis. Leaders who prioritize integration, governance, and full-lifecycle partner capabilities stand a better chance of breaking out of the pilot trap. Frameworks like FPT CASAN offer a practical benchmark for assessing readiness, and the broader discipline of AI for Executives & Strategy becomes essential for turning budget allocations into business results.
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