Enterprises that conduct regular audits of their artificial intelligence (AI) systems derive more than three times the business value from generative AI (GenAI) than those that do not, according to a recent global survey from Gartner. The research, which took place from May to June 2025, involved 360 business and technology leaders from organizations with at least 250 employees across North America, Europe, and Asia-Pacific. The study emphasizes the significance of consistent governance practices in transforming AI experimentation into tangible business benefits.
Kjell Carlsson, a VP Analyst at Gartner, stated, “AI governance really is a case of doing well by doing good.” The actual value gained hinges on the effectiveness of governance practices. While some practices focus on managing risks or ensuring compliance, others significantly enhance the business impact of GenAI initiatives.
The Gartner analysis revealed that businesses implementing structured AI governance frameworks—such as regular system evaluations, policy enforcement, and targeted employee training—were much more likely to see tangible returns from GenAI.
Companies that perform ongoing audits of their AI systems demonstrate the highest correlation with GenAI success. These regular assessments help in early detection of biases and ethical concerns, allowing leaders to adjust systems before risks escalate. Gartner advocates for utilizing dedicated AI governance platforms to automate assessments and facilitate auditing processes.
Additionally, providing role-based AI training significantly boosts outcomes—firms offering such training are twice as likely to achieve favorable GenAI results. Those with ethics-focused training programs improve their chances by 1.7 times. Embedding AI literacy across various departments can further strengthen the integration of technology with organizational strategies.
Investing in AI-specific usage policies and governance features continues to enhance performance. Enterprises that allocate budgets to third-party governance tools are almost twice as likely to realize increased value from their GenAI systems. More notably, companies that broaden their GenAI applications beyond small, low-risk environments are 3.3 times more likely to reap substantial business benefits.
Gartner’s findings convey that effective scaling in AI, supported by strong governance, fosters safe innovation while maximizing the potential of AI technologies. For organizations keen on unlocking sustainable impacts from AI, it’s clear: governance transcends compliance; it is crucial for achieving measurable business value.
FAQ: Building and Managing GenAI Infrastructure
What is GenAI infrastructure?
GenAI infrastructure encompasses the hardware, software, and data systems necessary for developing, training, and deploying generative AI models, including high-performance servers, GPUs, and governance frameworks.
Why does GenAI require specialized infrastructure?
Generative AI workloads necessitate extensive computational power and data throughput, which standard IT setups often lack. Specialized infrastructure is crucial for performance, reliability, and cost efficiency.
How can organizations ensure GenAI infrastructure remains secure?
Security measures should include data encryption, role-based access, continuous monitoring, and compliance audits. Employing AI governance frameworks can help mitigate ethical and regulatory risks.
What role do GPUs and accelerators play in GenAI performance?
GPUs and similar accelerators enable parallel processing for training and inference, significantly enhancing speed and efficiency compared to traditional CPUs.
How should businesses plan for future GenAI infrastructure needs?
Enterprises should utilize scalable, modular architectures capable of integrating advanced hardware and software. Collaborating with vendors that offer flexible compute solutions helps ensure preparedness for future demands in GenAI.
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