A report by Databricks sheds light on the future of artificial intelligence in business. Organizations worldwide plan to increase investments in data security, data governance and artificial intelligence platforms over the next three years. CIOs are recruiting ‘citizen data scientists’ to overcome a lack of trained professionals.

Databricks develops data analytics software. The organization is considered to be the inventor of the ‘lakehouse’, a combination of data warehouses and data lakes. Recently, the company initiated a survey on the challenges and future of artificial intelligence in business. The researchers discussed the topic with 600 CTOs, CIOs and data analytics executives worldwide.

More than half expect artificial intelligence (AI) to play a leading role in their company’s IT, development, marketing and sales operations by 2025. Most want to implement AI for multiple use cases. A significant amount focuses on use cases with direct returns, such as sales.

Growth

AI and data are inextricably linked. The accuracy and speed of an AI model depend on training, and training is impossible without data. It should come as no surprise that AI is a top priority in the data strategies of those surveyed. More than three-quarters (78 percent) indicated that scaling AI and machine learning is the most important part of their companies’ data strategy for the next three years.

Scaling comes with investing. The average executive expects his or her organization to invest 59 percent more in data security over the next three years; 52 percent more in data governance and 40 percent more in new data and AI platforms. The trend applies to every sector, but according to Databricks, financial service providers beat the average. The average financial services company expects higher investments than companies in other sectors.

72 percent of those surveyed prefer multi-cloud environments for AI development. Several chief intelligence officers (CIOs) emphasized the importance of open standards for multi-cloud architectures. According to them, multi-cloud environments and open standards are essential for the future development of AI.

Citizen data scientists

In addition to expectations, the researchers questioned respondents on the progress of AI. Companies with rapid and effective deployments share a number of characteristics. “The greater the number of employees in an organization who can configure and improve AI algorithms, the more AI-based innovations are likely to materialize”, the researchers described. The problem is that employees with AI skills are scarce. Available data scientists are hard to find.

According to the researchers, CIOs are trying to solve the problem with ‘citizen data scientists’ — employees that are skilled with data, but have not completed official data science training. Organizations with accessible infrastructure tools can employ more citizen data scientists. Therefore, the researchers advise organizations to focus on accessibility when scaling up.

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