What Most Companies Get Wrong About AI

Many enterprises rush into AI without the right strategy. Arm’s new insights reveal that compute power, talent, and trust are the real keys to sustainable AI success.

Artificial intelligence has become a business imperative, but many companies are discovering that enthusiasm alone doesn’t guarantee success. According to Arm’s AI Readiness Index, while 82% of global leaders report using AI, only 39% have a comprehensive strategy — leaving a vast majority struggling to turn experimentation into measurable ROI.

Arm, which partners with organizations across industries from hyperscalers to automotive and IoT innovators, argues that successful AI depends on three essentials: scalable compute, trusted data, and skilled people. Without these foundations, AI becomes an expensive experiment that drains resources and delays returns.

The Real Cost of Misguided AI Adoption

Companies chasing quick AI wins often face duplicated tools, inefficient infrastructure, and security roadblocks. Nearly half of surveyed executives cite poor data quality and lack of skilled talent as top challenges. As AI models grow more complex and data more sensitive, infrastructure decisions now carry business-critical weight.

Rethinking Compute: Efficiency Over Excess

With Moore’s Law slowing and AI’s computational demands accelerating, power efficiency has become the new frontier. Arm highlights the industry’s shift toward custom silicon and compute subsystems—tailored hardware designed specifically for AI workloads. From cloud training to edge inference, purpose-built architectures are enabling scalable AI performance without ballooning energy costs.

The Human Factor: Skills and Culture Matter

AI transformation isn’t just about technology—it’s about people. Arm’s research shows that nearly half of organizations say their employees lack basic AI understanding, and only 37% have a formal change management plan. The most successful companies are investing in training, leadership alignment, and AI fluency to embed innovation into everyday operations.

Data Trust and Responsible AI

As global regulations like the EU AI Act emerge, responsible data governance has become non-negotiable. Organizations must ensure transparency, privacy protection, and fairness in their AI systems. Arm stresses that ethical AI isn’t just a compliance checkbox—it’s a cornerstone of long-term trust and market credibility.

Building AI for Real ROI

Enterprises that align compute, data, and talent strategies are already seeing results. Arm’s study found that 65% of companies with clear AI roadmaps are meeting or exceeding ROI expectations. The takeaway: AI success is built, not bought.

The Bottom Line

AI is no longer a side project—it’s a company-wide transformation. To succeed, businesses must ground their ambitions in compute efficiency, data integrity, and human expertise. Those that do will move beyond hype and build AI capabilities that truly scale.