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AI projects may fail without sufficient support in data infrastructure: Study
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Around 20% of AI projects might not succeed without sufficient support in data infrastructure, found a recent study conducted by intelligent data infrastructure provider NetApp. The IDC White Paper titled "Scaling AI Initiatives Responsibly: The Critical Role of an Intelligent Data Infrastructure" aimed to uncover the essential components required for successful AI projects, stressing the fundamental importance of data infrastructure.
The study suggests that organizations considered AI Masters prioritize their data infrastructure to support transformative AI initiatives. These organizations focus on facilitating easy access to corporate datasets with minimal preparation, establishing a unified, hybrid, multicloud environment capable of accommodating diverse data types and access methods.
Challenges persist across different levels of AI maturity. AI Masters face obstacles such as infrastructure-based access limitations, compliance issues, and data insufficiency, while AI Emergents encounter challenges like budget constraints, inadequate data for model training, and business restrictions on data access.
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The study indicates that AI Masters demonstrate superior data accessibility, with instant availability of structured and unstructured data. Moreover, these organizations seamlessly integrate private data with AI cloud services, indicating a high level of infrastructure flexibility.
Effective data governance and security processes emerge as crucial indicators of organizational maturity in AI initiatives. AI Masters prioritize standardized governance policies enforced by independent bodies, while AI Emergents often struggle due to the absence of such policies.
Efficient resource utilization is essential for AI model development. AI Masters exhibit clearly defined metrics for assessing resource efficiency, a factor lacking in many AI Emergent organizations.
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The study, conducted between December 2023 and January 2024, comprised interviews with global decision-makers involved in AI-related fields. Based on the findings, IDC developed an AI maturity model categorizing organizations into four levels: AI Emergents, AI Pioneers, AI Leaders, and AI Masters.
The IDC White Paper provides valuable insights for organizations embarking on AI initiatives, offering actionable insights to mitigate common pitfalls and ensure project success. By prioritizing the development of intelligent data infrastructure, companies can enhance their AI scalability, efficiency, and overall business outcomes.
Jonsi Stefansson, Senior Vice President and Chief Technology Officer at NetApp, emphasizes the significance of intelligent data infrastructure, asserting that it enables companies to access data securely and efficiently, driving innovation and long-term success in AI endeavours.
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