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Premium Research Jun 2026
... Agile data science emphasizes incremental delivery of value when exploring data, creating actionable insights, and building advanced analytics and AI-enabled/AI-powered/AI-native products. Data scientists must apply agile practices to increase business agility and deliver better outcomes. Overview Analysis ...

Analyst(s):   Peter Hyde
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Premium Research Aug 2026
... AI coding assistants and autonomous agents are transforming data science and machine learning workflows by automating repetitive tasks and enhancing productivity. For data scientists, interactive tools will be used for human-centric tasks while automation tasks will be delegated to agents. Overview ...

Analyst(s):   Cuneyd Kaya
Research Jul 2026
... Gartner client? Leaders responsible for AI need to reduce the risk of unpredictable cost overruns by leveraging data science agents within the data science and machine learning life cycle. Data science agents can drive value by delivering more rapid insights and ensuring robust governance across your organization ...

Analyst(s):   Yogesh Bhatt   |   Deepak Seth
Premium Research Aug 2026
... Transitioning to autonomous data science agents risks platform sprawl, hidden logic, and unpredictable costs. Leaders responsible for AI must use this checklist to assess the five core capability categories needed to build, govern, and securely scale data science agent workflows without sacrificing enterprise ...

Analyst(s):   Yogesh Bhatt   |   Sudarshana Bhattacharya   |   Deepak Seth
Research May 2026
... client? AI techniques such as forecasting and classification, not GenAI or agents, currently deliver most AI value. D&A leaders responsible for data science and machine learning can use this Hype Cycle to harness key technologies to build and govern generative, agentic, predictive and prescriptive models ...

Analyst(s):   Afraz Jaffri   |   JC Martel, PhD
eBook January 28 2026
... study: Close the Data Science Talent Gap by Hiring and Upskilling Internally How Eastman drove value and overcame data science talent challenges in a competitive market. Data science talent is infamously difficult for data and analytics (D&A) leaders to find. Organizations know their data is a latent asset ...
Research Jun 2026
... GenAI Model Engineering Monitoring and Observability Model Management Governance, Risk, and Project Mgmt. RAG Scalability Data Science Agents Agent Building Integrated Development Environment Insights Generation MLOps Composite AI AI Engineering AI Automation Inclusion and Exclusion Criteria Gartner Recommended ...

Analyst(s):   Diarmuid Curran   |   Afraz Jaffri   |   Yogesh Bhatt
Premium Research Oct 2026
... platforms that enforce robust operations practices, implement strict guardrails and provide AI governance for risk management. This note guides chief data and analytics officers to learn from the implementation experience of their peers shared on Gartner Peer Insights. Overview Peer Lessons Learned Gartner ...

Analyst(s):   Peer Community Contributor
Research Jun 2026
... Access Insights Already a Gartner client? AI platforms for data science and machine learning provide software that supports end-to-end AI models and agent development and life cycle management using diverse data science and AI techniques. Leaders responsible for AI need to select platforms with awareness ...

Analyst(s):   Diarmuid Curran   |   Afraz Jaffri   |   Yogesh Bhatt
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