by Andrew White | January 3, 2019 | Comments Off on Our Top Data and Analytics Predicts for 2019
- By 2022, 90% 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% of data and analytics strategies and change management programs.
- By 2022, 30% of CDOs will partner with their CFO to formally value the organization’s information assets for improved information management and benefits.
- By 2023, 60% 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% of AI projects will remain alchemy, run by wizards whose talents will not scale in the organization.
Through 2022, only 20% 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% of conversational assistant applications, which use speech or text, identify themselves as being nonhuman entities.
By 2022, 30% 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% 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% of large organizations will hire AI behavior forensic, privacy and customer trust specialists to reduce brand and reputation risk.
- By 2022, 50% 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%.
- By 2023, 75% 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%.
- By 2021, enterprises using a cohesive strategy incorporating data hubs, lakes and warehouses will support 30% 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% of use cases leveraging AI techniques (such as ML and DNNs) and involving edge and IoT environments will be successful.
- Through 2022, over 75% of organizations will use DNNs for use cases that could be addressed using classical ML techniques.
- By 2023, 70% of AI workloads will use application containers or be built using a serverless programming model necessitating a DevOps culture.
- By 2023, 40% of I&O teams will use AI-augmented automation in large enterprises, resulting in higher IT productivity with greater agility and scalability.
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