The number of disabled people in employment is expected to triple by 2023 due to AI and emerging technologies reducing barriers to access; 69% of an average manager’s workload is expected to be automated by 2024
Enterprises limit their ability to realize the business value of artificial intelligence because most struggle to develop AI pilots into production, suggests a recent report from Garter.
In its annual Data and Analytics Predictions list, the analyst firm projected that more than half of of all analysis by deep neural networks will happen at the point of capture by 2023, an increase from less than 5% in 2019.
Cloud-based AI workloads are expected to increase five-fold from 2019, with AI becoming one of the top cloud services; by 2022, ‘cloud-native’ application containers (think Kubernetes) are estimated to become integral to 85% of enterprise AI pipelines.
However, while AI proofs of concept (POC) have become common, Gartner still sees major blocks to ope rationalizing their development.
A changing world
“IT leaders must strive to move beyond the POC to ensure that more projects get to production and that they do so at scale do deliver business value,” stated the authors of the report.
“IT leaders responsible for AI must nurture infrastructure strategies that enable the evolution of AI pilots into scalable production and, importantly, value realization.”
Through 2021, most (80%) line of business leaders are expected to override business decisions made by AI.
The demand for data scientists is expected to decrease, with the number of application development engineers building machine learning models using automated ML is expected to grow to 25% by 2022.
By this point, Gartner expects nearly half (40%) of machine learning development will be done in products that do not have machine learning as their primary goal.
‘Machine learning engineer’ is projected to be the fastest growing role in AI and ML, with open positions for ML engineers reaching half that of data scientists, an increase from fewer than 10% in 2019.
The majority (85%) of AI solutions from vendors are estimated to focus on concrete domains and industry verticals by 2023.
Artificial intelligence is also is seen as having impact throughout the enterprise. For example, the number of disabled people in employment is expected to triple by 2023 due to AI and emerging technologies reducing barriers to access.
Gartner predicts that all personnel hired for AI development and training will have to show expertise in responsible development practices by 2023.
By 2025, nearly half (47%) of budgets for learning and development are anticipated to be wasted, with AI eliminating 67% of on-the-job, task-based learning opportunities.
The role of the manager is expected to change completely, since 69% of an average manager’s workload today is expected to be automated by 2024.
More than 50% of new technologies evaluated are expected to include AI among key criteria for simplifying integration.
AI services are projected to become essential and largely invisible in daily work activities by 2024.