Gartner's top data and analytics predictions for 2019

By Andrew White January 18, 2019, 5:12 a.m. EST 3 Min Read

Predicts 2019: Data and Analytics Strategy

By 2022, 90 percent% of corporate strategies will explicitly mention information as a critical enterprise asset and analytics as an essential competency.
By 2023, data literacy will become an explicit and necessary driver of business value, demonstrated by its formal inclusion in over 80 percent of data and analytics strategies and change management programs.
By 2022, 30 percent of CDOs will partner with their CFO to formally value the organization’s information assets for improved information management and benefits.
By 2023, 60 percent of organizations with more than 20 data scientists will require a professional code of conduct incorporating ethical use of data and AI.
By 2022, more than half of major new business systems will incorporate continuous intelligence that uses real-time context data to improve decisions.

Through 2020, 80 percent of AI projects will remain alchemy, run by wizards whose talents will not scale in the organization.
Through 2022, only 20 percent of analytic insights will deliver business outcomes.
By 2021, proof-of-concept analytic projects using quantum computing infrastructure will have outperformed traditional analytic approaches in multiple domains by at least a factor of 10

By 2021, legislation will require that 100 percent of conversational assistant applications, which use speech or text, identify themselves as being nonhuman entities.
By 2022, 30 percent of consumers in mature markets will rely on artificial intelligence (AI) to decide what they eat, what they wear or where they live.
By 2022, 30 percent of organizations will use explainable AI models to build trust with business stakeholders, up from almost no usage today.
By 2023, a Fortune 1000 antitrust case will hinge on whether tacit cooperation among autonomous AI agents in competitive markets constitutes collusion.
By 2023, over 75 percent of large organizations will hire AI behavior forensic, privacy and customer trust specialists to reduce brand and reputation risk.

By 2022, 50 percent of cloud buying decisions will be based on the data assets provided by cloud service providers rather than on the product capabilities.
By 2023, AI-enabled automation in data management will reduce the need for IT specialists by 20 percent.
By 2023, 75percent of all databases will be on a cloud platform, reducing the DBMS vendor landscape and increasing complexity for data governance and integration.
By 2022, organizations utilizing active metadata to dynamically connect, optimize and automate data integration processes will reduce time to data delivery by 30 percent.
By 2021, enterprises using a cohesive strategy incorporating data hubs, lakes and warehouses will support 30 percent more use cases than competitors.

Through 2023, computational resources used in AI will increase 5x from 2018, making AI the top category of workloads driving infrastructure decisions.
Through 2022, only 15 percent of use cases leveraging AI techniques (such as ML and DNNs) and involving edge and IoT environments will be successful.
Through 2022, over 75 percent of organizations will use DNNs for use cases that could be addressed using classical ML techniques.
By 2023, 70 percent of AI workloads will use application containers or be built using a serverless programming model necessitating a DevOps culture.
By 2023, 40 percent of I&O teams will use AI-augmented automation in large enterprises, resulting in higher IT productivity with greater agility and scalability.

(This post originally published on Andrew White's Gartner blog, which can be viewed here).

Research vice president, Gartner Inc.