A study revealed that AI and data management are essential pillars to enterprise success.

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Data management and AI adoption is critical in achieving enterprise success

  • Data management challenges were cited as a significant risk factor for survey respondents’ company’s potential AI success
  • AI application in business operations will be pervasive or essential by 2025

Data is the new gold in the digital age, because it truly is everything. Every firm should place a high focus on data management if they want to grow and succeed. When an enterprise has a robust data management system in place, it makes sure that the data is always easily available and in a secure state.

In conjunction with the adoption of artificial intelligence (AI), it makes it possible for data and analytics software to predict, automate, and optimize processes, reducing time to value. Realizing this could have an impact on its future if it is not fully utilized.

According to a recent survey report by MIT Technology Review Insights, which highlights AI and data management as crucial pillars to enterprise success, the majority of survey respondents identified data mismanagement as a significant issue that could affect their company’s future AI performance.

The report titled “CIO vision 2025: Bridging the gap between BI and AI” was carried out in May and June 2022 in collaboration with Databricks, the pioneer of the lakehouse architecture. The findings of the report are based on a survey of 600 global CIOs, CDOs, and CTOs from 14 industries and interviews with C-level executives from top companies to understand how leaders are thinking about challenges in data management and business value realization as they strive to unleash the power of AI in their organizations.

The following companies are among those included in this report: Procter & Gamble, Johnson & Johnson, Cummins, CNH Industrial, Walgreens Boots Alliance, S&P Global, Marks & Spencer, Tokio Marine, Virgin Australia, and Freshworks.

The state of enterprise data management and AI

AI development initiatives are likely to fail if a solid data management infrastructure and plan are not in place.

As such, the report stated that by 2025, a majority of executives anticipate that AI application in business operations will be pervasive or essential. The executives who were interviewed anticipate a significant increase in use cases for AI in all key tasks over the next three years, from its currently relatively limited use across the enterprise.

Also, according to 72% of C-level respondents, data management issues would imperil future AI successes. To increase AI adoption, the majority of surveyed businesses plan to invest in integrating their data platforms for analytics and AI in the coming three years. 78% of executives surveyed stated that the top objective for data strategy is scaling AI successfully. The data and AI strategies of the surveyed organizations are intertwined. Scaling AI and machine learning use cases to generate business value is, according to more than seven in ten (78%) of the executives interviewed, the top goal for their enterprise data strategy over the next three years.

Interestingly, financial services will see the most AI investment. The two industries with the highest concentrations of AI leaders were manufacturing and retail/consumer goods. Executives also consider open standards and multi-cloud to be crucial to the advancement of AI. The majority of survey participants (72%) value the flexibility that a multi-cloud strategy offers for AI development.

According to more than two-thirds of the technology leaders they surveyed, data challenges are more likely than not the cause if firms fail to reach their AI goals, according to Francesca Fanshawe, the report’s editor.

“Improving processing speeds, governance, and quality of data, as well as its sufficiency for models, are the main data imperatives to ensure AI can be scaled,” Fanshawe added.

Chris D’Agostino, Global Field CTO at Databricks, added that these observations from global CIOs are congruent with what the company learns from its field employees.

“AI-ready data is no longer a nice-to-have – it is critical to solve real-world problems and drive business outcomes,” said D’Agostino. “An open and unified platform like the Databricks Lakehouse enables organizations to put their data into action and we are committed to ongoing innovations that will empower business leaders to deploy and scale mission-critical AI projects successfully.”