Gartner's top data and analytics predictions for 2019
January 18, 2019, 5:12 a.m. EST
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).