Looming is addressing deficiencies in data management and corporate infrastructure, as well as internal structural and process rigidity and talent deficits. About 72% of tech executives surveyed in this study say that if their companies fail to achieve their AI goals, data issues are likely to be the cause. Survey respondents say that improving processing speeds, governance, and data quality, as well as adequacy of models, are key data imperatives to ensure that AI can scale.
This report highlights these and other data limitations that organizations must address to unleash potential AI for their businesses. It also outlines the investments and other measures companies plan to take to closely align their data capabilities with their AI ambitions. The study findings are based on a global survey of 600 CIOs, CTOs and other top technology leaders. We also drew insights from in-depth discussions with 10 of these CEOs.
Here are the main findings of the study:
- Companies view the widespread adoption of AI as an important milestone for their future. From the mostly limited use of AI across the organization today, the executives surveyed plan to significantly expand use cases across all core functions in the next three years. More than half expect AI use to be widespread or critical in information technology, finance, product development, marketing, sales, and other functions by 2025. While most will pursue a variety of use cases, many also aim to enhance The impact of artificial intelligence on the first line, increasing returns from revenue-generating uses.
- Successful scaling of AI is the number one priority of the data strategy. The data of the surveyed companies and AI strategies are closely related. More than three-quarters (78%) of CEOs we survey – and nearly all (96%) of the lead group – say scaling AI and machine learning use cases to create business value is their top priority for enterprise data strategy over the next three years .
- Significant growth in spending is planned to strengthen the data foundations of AI. The CIOs surveyed—particularly those in the leadership group—are planning a significant increase in investment between now and 2025 to strengthen various parts of their data and the foundations of AI. Leading companies will spend 101% on data security over the next three years, on data management by 85%, on new data and AI platforms by 69%, and on existing platforms by 63%. (The similar figures among the sample as a whole are 59%, 52%, 40% and 42%, respectively).
- Investment growth intentions are strongest in the financial services industry. Among the 14 industries surveyed, AI leaders were the most numerous among retail/consumer goods and auto/manufacturing companies. The expected investment growth in these sectors in the above areas of data management and infrastructure is higher than others with one exception: the planned increases by financial service providers will significantly exceed those in all other sectors.
- Multi-cloud and open standards are an integral part of the advancement of AI. Most survey respondents (72%)—and nearly all leaders (92%)—appreciate the flexibility that a multi-cloud approach to AI development provides. The CIOs interviewed for the study also stress the role of open architecture standards in supporting multi-cloud, and the importance of both in advancing AI development.
This content was produced by Insights, the dedicated content arm of the MIT Technology Review. It was not written by the editorial team at the MIT Technology Review.