One survey offers a small snapshot into the ways that large corporations are tooling up to make the most of AI

Based on a survey about data architecture in the AI era across around 600 IT decision makers* from the U.S., Europe and the Asia Pacific region (APAC) in organizations with annual revenues of more than US$500m or more than 1,000 employees globally, some trends were reported from the data.

First, 90% of respondents believed that unifying the data lifecycle on a single platform is critical for analytics and AI, based on perceptions that the proliferation of generative AI (GenAI) requires trustworthy data, and because AI insights are only as powerful as the data feeding them.

Second, respondents face obstacles in their AI journeys due to the quality and availability of data (36% vs 35% in APAC), scalability and deployment challenges (36% vs 38% in APAC), integration with existing systems (35% vs 33% in APAC), change management (34% vs 36% in APAC), and model transparency (34% vs 31% in APAC).

Other key findings 

Three other key findings were also gleaned from the respondents’ feedback for achieve effective AI:

    3. Most popular perceived benefits of modern data architecture: When it came to the benefits of modern data architectures, the most popular responses were:
    • simplifying data/analytics processes (40% vs 43% in APAC)
    • gaining flexibility in handling all types of data (38% vs 42% in APAC)
    4. Hurdles to AI model development: When it came to factors that were holding back end-to-end data management needed for AI model development:
    • 62% of respondents indicated it was the volume and complexity of data (vs 59% for APAC)
    • 56% indicated data security (vs 59% for APAC)
    • 52% indicated governance and compliance (vs 55% for APAC)
    5. Choice of versatile and secure data platforms: 93% of respondents agreed to prompts that “multi-cloud/hybrid capabilities for data and analytics are key for an organization to adapt to change” (93% for APAC).

According to Abhas Ricky, Chief Strategy Officer, Cloudera, the firm that commissioned the survey: “In order for (respondents) to effectively leverage AI capabilities, (large organizations) need to design and embed standardized, use case-centric data architectures and platforms that will allow disparate teams to tap into all of their data — no matter where it resides.”

Large organizations that are looking to get the most out of their data “need to rapidly build and deploy modern platforms and AI architectures that support that mission,” Ricky noted.

* with job designations of Director or above, and including being responsible for the selection of data-related products and services, including, but not limited to, infrastructure