A recent survey released by Gartner has illuminated the significant impact that artificial intelligence (AI) is having on how companies manage and govern data. The survey, which encompassed 479 leaders in data and analytics (D&A) from various global organizations, showed that a staggering 61% are reconsidering their D&A strategies due to the disruptive nature of AI technologies.
These leaders, including chief data and analytics officers, chief data officers, and chief analytics officers, are quickly realizing that traditional operating models may no longer suffice. In fact, 38% of respondents are planning a comprehensive overhaul of their D&A architectures in the next 12 to 18 months. Additionally, 29% intend to revamp their data asset management along with the adoption and application of governance policies and standards.
Alan D. Duncan, Vice President Analyst at Gartner, underscored the urgency with which chief data analytics officers (CDAOs) are acting to adapt their operating models to align with the rapid advancements in D&A and AI technologies. Duncan highlighted the expanding scope of responsibilities shouldered by CDAOs, pointing out the increasing challenges posed by budget and resource constraints.
Further, the Gartner survey revealed that AI has become an integral part of the responsibilities for a majority of CDAOs, with 58% acknowledging AI within their purview—an increase from 34% in 2023. Gartner Senior Director Analyst Donna Medeiros emphasized how organizations, particularly in the private sector, are recalibrating their entire business models around AI to capitalize on automation, operational excellence, and new business opportunities.
The significance of high-quality data for the successful deployment of AI technologies was also a key theme. A Forrester report titled “AI Is Ready For The Spotlight, But Data And Analytics Determine If It Shines” highlighted that the effectiveness of AI outputs heavily depends on the quality of input data. The report likened AI as the star actor in a musical, with data and analytics leaders playing the crucial role of stage managers setting the stage for success.
Data quality improvements were showcased as pivotal for enhancing the accuracy of machine learning models and, consequently, the predictability of outcomes. Forrester’s analysis underscored the necessity for data and analytics teams to adopt robust data platforms and quality practices, and to invest in data skills training to ensure the fluency of their teams in new AI technologies.
However, the Gartner survey also exposed a significant gap in the establishment of metrics by CDAOs to measure the business outcomes of D&A initiatives. Only 49% of surveyed CDAOs had implemented business outcome-driven metrics, while a third had not established any business outcome metrics for D&A at all. This gap underscores a critical area for improvement in demonstrating the value of D&A investments to stakeholders.
The survey also touched on the challenges and the increased demands placed on CDAOs, including budget constraints and the need for better engagement and support from C-suite executives to secure funding for D&A initiatives. Gartner predicts that CDAOs who fail to extend their influence across the organization and make a measurable impact will likely be integrated into other technology functions by 2026. This highlights the pressing need for CDAOs to assert their role and demonstrate the strategic value of D&A within their organizations.
Source
