Data and analytics leaders should embrace three imperatives when leveraging the top data and analytics trends for 2022 in their enterprise, according to Gartner.
The three key areas are: activate dynamism and diversity, augment people and decisions, and Institutionalise trust.
“This year’s top data and analytics trends represent business, market and technology dynamics that will help organisations anticipate change and transform uncertainty into opportunity, both of which have come under the purview of the data and analytics leader,” said Rita Sallam, distinguished research vice president at Gartner.
In 2022, Gartner identified 12 top trends in data and analytics 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.
For example, the trend “always share data” reinforces data sharing as a business-facing key performance indicator that an organisation 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 an urgency to share data 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 sharing data.
Augment people and decisions
To make insights relevant to decision-makers, data and analytics leaders must deliver enriched, context-driven analytics created from modular components by the business. This includes prioritising data literacy and putting in place strategies to address the scarcity of data and analytics talent.
By 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’s research shows that organisations that deal with the human element of data and analytics are more successful than organisations 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 data and analytics, decision-centric data and analytics, and skills and literacy shortfall.
Institutionalise trust
Achieving value from data and analytics 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 organisations cannot interpret or explain what their models are doing, resulting in a lack of trust and transparency. Organisations 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 mis-performing 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 organisations that develop trustworthy, purpose-driven AI will see over 75 per cent of AI innovations succeed, compared to 40 per cent 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.
