40% of organizations' struggles surrounding their current data and AI platform strategies stem from workforce upskilling and training, according to the latest survey by MIT Technology Review Insights and Databricks. The second edition of the report, "Bringing breakthrough data intelligence to industries," reveals the nuanced challenges and priorities of organizations in their path to democratizing data and AI.
Surveying 600 senior technology executives, the report highlights pressing topics, like unified data and AI governance models, real-time data analytics, and cross platform data sharing.
Sector-Specific Insights and Trends:
- Retail and CPG: In the Retail and Consumer Packaged Goods sector, companies are prioritizing efficiency and insight. Walmart US is leveraging AI to analyze vast amounts of customer and item data to refine the shopping experience. Sam’s Club is democratizing data access for a broad range of enterprise users, promoting a data-driven culture.
- Health Care and Life Sciences (HLS): The HLS industry is focusing on harnessing data and AI to enhance patient outcomes. Institutions like the Regeneron Genetics Center are employing AI to delve into genetic data.
- Manufacturing: General Motors is turning to AI to optimize their supply chains and improve quality control.
- Financial Services Institutions (FSIs): FSIs are driving data-led innovation and compliance. Companies such as AXA UK & Ireland are implementing AI to streamline processes like claims handling, which not only reduces costs but also enhances customer satisfaction.
- Telecommunications: With 77% adopting lakehouse architecture, companies like AT&T are centralizing data and AI to manage data traffic and enhance operations. Another priority is ensuring that cross-department employees can harness insights to improve customer service.
- Media and Entertainment (M&E): Condé Nast is investing in AI for content management. However, surrounding generation, "[We] will refrain from using LLMs to write magazine content," citing the inauthentic quality of LLM-written content.
- Public Sector: US Postal Service is using AI for fraud analytics. A significant majority are moving towards unified governance and real-time data sharing through lakehouse architecture.
A unified data foundation, i.e. lakehouse architecture — offered by Databricks — is a clear pillar for advancing the democratization of data and AI. It's expected to enhance the reach and benefits of AI across industries, shaping its anticipated, immense economic impact. However, the path is still laden with challenges, like constructing industry-specific data ecosystems.
Overcoming these challenges should enable full-fledged adoption of AI. Strategic collaboration seems to be a common requirement among industry leaders, technologists, and policymakers.
