Gartner: 3 Ways to Understand the Top Data and Analytics Trends for 2022

The need to anticipate change and transform uncertainty into opportunity is a driving force underlying the top trends in data and analytics this year, according to research firm Gartner. The company recently identified 12 key areas defining data and analytics (D&A) in 2022: adaptive AI systems; data-centric AI; metadata-driven data fabric; a philosophy to always share data; context-enriched analysis; business-composed D&A; decision-centric D&A, skills and literacy shortfall; connected governance; AI risk management; vendor and region ecosystems; and expansion to the edge.

To put those trends into context, Gartner offered three "imperatives" — overarching categories that define D&A's real-world impact and how organizations can best leverage D&A trends in the coming year.

1) Activate diversity and dynamism. Adaptivity and data-sharing is key, Gartner asserted: "Innovations in data management for AI, automated, active metadata-driven approaches and data-sharing competencies, all founded on data fabrics, unleash the full value of data and analytics." The COVID-19 pandemic, for example, made it vital to share and increase access to the right data for decision-making across stakeholders. And that has been made possible by new technologies and approaches that mitigate data-sharing risk, the research firm pointed out. "By 2026, applying automated trust metrics across internal and external data ecosystems will replace most outside intermediaries, reducing data-sharing risk by half," Gartner predicted. Trends to watch in this category: adaptive AI systems; data-centric AI; metadata-driven data fabric; and the "always share data" philosophy.

2) Augment people and decisions. Here, Gartner pointed to the importance of data literacy and developing data and analytics talent. "Through 2025, the majority of CDOs will have failed to foster the necessary data literacy within the workforce to achieve their stated strategic data-driven business goals," the firm said. Focusing on the human elements of D&A "fosters broader digital learning, rather than simply delivering core platforms, datasets and tools." Trends to watch include context-enriched analysis; business-composed D&A; decision-centric D&A; and skills and literacy shortfall.

3) Institutionalize trust. Achieving value from D&A at scale is only possible with trust and transparency. And that means "managing AI risks and enacting connected governance across distributed systems, edge environments and emerging ecosystems," Gartner said. AI innovation has outpaced model governance, and "most organizations cannot interpret or explain what their models are doing," the research firm cautioned. By 2026, "organizations that develop trustworthy purpose-driven AI will see over 75% of AI innovations succeed, compared to 40% among those that don't." Trends to watch here: connected governance; AI risk management; vendor and region ecosystems; and expansion to the edge.

The full report, "Top Trends in Data and Analytics, 2022," is available to Gartner clients here.

About the Author

Rhea Kelly is editor in chief for Campus Technology, THE Journal, and Spaces4Learning. She can be reached at [email protected].

Featured

  • futuristic representation of interconnected individuals within a digital network

    OpenAI Launches Safety Fellowship to Fund External AI Research

    OpenAI is expanding safety efforts beyond its walls with a new Safety Fellowship that will fund external researchers to study AI risks.

  • Abstract energetic glowing lines with particles

    Meta Steps Up Enterprise AI Ambitions with Muse Spark Launch

    Meta has announced the launch of Muse Spark 1.1, a multimodal reasoning model designed for agentic AI, alongside a new Meta Model API that gives developers access to the model for the first time.

  • Abstract neural network 3D illustration

    IntelĀ® AI EmpowerED: The AI-Ready Campus, Delivered

    Artificial intelligence is transforming higher education, prompting institutions to rethink how they manage infrastructure, security, governance, and workforce readiness. Successful adoption requires a strategic, institution-wide approach that aligns AI initiatives with educational goals, faculty enablement, and scalable operational frameworks.

  • clock and neon light trails

    Don't Wait for the Clock to Run Out on Digital Accessibility

    Public universities with over 50,000 students face the looming April 24, 2026, deadline to comply with new Americans with Disabilities Act (ADA) Title II standards. The urgency many feel is warranted: Implementation timelines are tight and the scope of compliance is extensive.