In 2022, Gartner identified 12 top trends in D&A that span the following three core categories.
Activate diversity and dynamism
The rise of adaptive artificial intelligence (AI) systems, such as AI engineering, drives growth and innovation while coping with fluctuations in global markets. 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.
As one example, the trend “always share data” reinforces data sharing as a business-facing key performance indicator that an organization is achieving effective stakeholder engagement and increasing access to the right data to generate public value. The coronavirus pandemic and other recent large-scale global events created urgency to share data in order to accelerate independent and interrelated public and commercial digital business value.
Gartner expects that by 2026, applying automated trust metrics across internal and external data ecosystems will replace most outside intermediaries, reducing data sharing risk by half.
The 2022 trends in this category include: adaptive AI systems, data-centric AI, metadata driven data fabric, and always share data.
Augment people and decisions
To make insights relevant to decision-makers, D&A leaders must deliver enriched, context-driven analytics created from modular components by the business. This includes prioritizing data literacy and putting in place strategies to address the scarcity of 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. Gartner research shows that organizations that deal with the human elements of D&A are more successful than organizations that only consider technology. A human focus fosters broader digital learning, rather than simply delivering core platforms, datasets and tools.
The 2022 trends in this category include: context-enriched analysis, business-composed D&A, decision-centric D&A, and skills and literacy shortfall.
Achieving value from D&A at scale is only possible by managing AI risks and enacting connected governance across distributed systems, edge environments and emerging ecosystems.
AI is becoming more pervasive, yet most organizations cannot interpret or explain what their models are doing, resulting in a lack of trust and transparency. Organizations are not prepared to manage the risks of fast-moving AI innovation and are inclined to cut corners around model governance including security, escalating the negative consequences of misperforming AI models, such as incorrect business decisions or worse, those impacting life or death.
As AI regulations proliferate globally, they are mandating certain auditable practices that ensure trust, transparency and consumer protection. By 2026, Gartner anticipates organizations that develop trustworthy purpose-driven AI will see over 75 percent of AI innovations succeed, compared to 40 percent among those that don’t.
The 2022 trends in this category include: connected governance, AI risk management, vendor and region ecosystems, and expansion to the edge.