Businesses with high AI maturity – What sets them apart?
More tangible advantages, higher expenditures With measurable effects on measurable business benefits, organizations with high AI maturity demonstrate a more extensive approach to AI integration. High-maturity organizations commit significant resources to AI. Specifically, they make twice the investment in digital, twice the people allocation, and twice the number of AI solutions scaled. These investments pay off, as IDC reported that leading generative AI users see a 10x ROI, far higher than the 3.7x average for all users.
Combining talent, leadership, and AI in core operations
Importantly, success in AI requires more than increased expenditure. High-performing organizations understand that achieving real value from AI requires aligning technology with business goals, cultivating the right talent, and embedding AI into everyday operations. Senior management, who see AI as a crucial enabler of long-term competitive advantage, frequently achieve this broader vision. Indeed, Gartner’s 2025 survey revealed that 91% of high-maturity organizations have established dedicated AI leadership roles. These leaders don’t work in isolation – they actively integrate AI into core business areas such as operations, sales, and R&D, where 62% of AI’s value is realized. According to a separate study conducted by IDC, AI thrivers are three times more likely to have a change management program that focuses on employee engagement with new agentic workflows as part of a broader, communicated business strategy and drives transformation throughout the organization. a strong emphasis on AI and governance that are responsible Implementing AI alone is not enough.
For high-maturity AI organizations, they have also established clear responsibilities, governance frameworks, and ethical standards to guide their use. These organizations create systems that are efficient and in line with their values and societal expectations by incorporating accountability and transparency into the development and deployment of AI. AI thrivers are four times more likely, according to the IDC MaturityScape Benchmark AI Survey 2025, to have an AI Governance framework that is aligned with their AI strategy and includes standards and practices for managing AI models, data, and security across the enterprise. The unified AI governance model of more established businesses distributes governance to the business by incorporating controls into its operations.
They actively redesign business processes to fully utilize AI’s potential for long-term value creation rather than simply layering AI onto existing workflows. Businesses with a low level of AI maturity: AI is still in the experimental stage. Businesses with low AI maturity, in contrast to high-maturity organizations, are still in the early stages of adoption and primarily concentrate on experimenting rather than implementing AI at scale or producing substantial value. According to Accenture, 63% of organizations worldwide are “AI Experimenters” who are only beginning to explore AI and have yet to realize its full potential. Specifically, only 20% of low-maturity organizations maintain AI projects that last three years or more, far fewer than high-maturity organizations.
Organizations with low AI maturity, especially in sectors like banking and insurance, struggle to capture strategic values due to weak governance and lack of trust in AI. According to a McKinsey survey, common issues such as inaccuracies, cybersecurity breaches, and IP violations frequently stem from inadequate oversight. As agentic AI introduces more autonomy and complexity, the associated risks become even more significant. Yet, only 28% of CEOs report direct involvement in AI governance, which calls for stronger executive accountability and robust oversight frameworks before scaling AI across the enterprise.
Additionally, rather than focusing on fundamental business transformation, their AI initiatives frequently target short-term productivity enhancements.
This means, these companies tend to view AI as a tool for operational efficiency, with limited emphasis on innovation or strategic differentiation. According to IDC research, only three of the 23 generative AI proof-of-concepts (POCs) tested made it to production, demonstrating that low-maturity organizations also struggle to transition from experimentation to enterprise-level implementation. Common obstacles to implementing AI Despite the difference in AI maturity levels, both high- and low-maturity organizations share several common barriers to successful AI implementation. One of the most prominent concerns is data availability or quality, cited as a top-three barrier by 29% of high-maturity respondents and 34% of low-maturity respondents.
As a requirement for efficient AI deployment, this data obstacle highlights the universal significance of clean, accessible, and well-structured data. According to the same Gartner study, deploying and operationalizing AI appears to be a challenge for both high- and low-maturity organizations (22% for high maturity and 19% for low maturity), indicating that even advanced businesses have trouble transitioning from proof-of-concept AI systems to scalable, production-ready AI systems. These obstacles are expected to get worse as businesses expand, despite early efforts to regulate AI adoption and secure the necessary talent—two areas in which organizations are less mature. If organizations fail to expand their talent pool, they might risk losing opportunities, slower innovation, and lower market competitiveness. Legacy infrastructure is another obstacle to AI adoption, a problem that is especially prevalent in younger businesses. These outdated systems often lack the flexibility, processing power, and integration capabilities required to support modern AI technologies.
FPT – Your trusted partner to overcome AI challenges
Businesses need a reliable partner to accelerate progress and overcome critical obstacles, regardless of where they are on the AI maturity scale. FPT’s expansive global partner network, including industry giants such as NVIDIA, Mila Institute, and LandingAI, empowers businesses to accelerate their AI transformation journey with confidence and scale. FPT is committed to promoting open innovation, ethical governance, and collaborative development across all aspects of AI as a founding member of the AI Alliance, which was co-founded by IBM and Meta, and the Ethical AI Committee in Vietnam. With a robust pool of over 1,000 AI experts, FPT empowers businesses to bridge critical talent gaps by providing access to industry knowledge, deep domain expertise, and a scalable best-shore model (including onshore, nearshore, offshore) to execute complex AI projects.
To further cement its position in AI, FPT announced a strategic partnership with NVIDIA to deliver a comprehensive AI & Cloud ecosystem. This includes cutting-edge AI products, GPU infrastructure, domain-specific expertise, and a unified platform accessible across all regions where FPT operates. One of the fastest commercial supercomputers in the world was recently named FPT’s AI Factory. FPT’s AI Factories in Japan and Vietnam, which utilize NVIDIA H200 Tensor Core GPUs (SXM5) and were ranked 36th and 38th globally on the June 2025 TOP500 list, make FPT the leading commercial AI cloud provider in Japan. Established on the philosophy of “Build Your Own AI”, these factories democratize access to high-performance computing, bridging the gap between potential and application across industries and everyday life.
