With AI and Machine Learning advancing, what new roles do you see emerging in the data and analytics space?

Innovation & Emerging Trends Team & Organizational Design

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Senior Data and Analytics Leader in Government2 years ago

As AI and machine learning continue to advance, new roles are emerging in the data and analytics space to leverage these technologies effectively and drive value for organizations. Some of these emerging roles include:

1. Ethics Officer
2. AI Model Validator
3. Data Privacy specialist
4. AI Solution Architect
5. ML engineer
6. AI Product Manager
7. AI Governance specialist
8. AI Trainer

Director, Information Technology in Services (non-Government)3 years ago

Some existing roles will increase in importance such as Chief Data Officer, Data Privacy Officer, and Data Scientist, but new roles such as AI Strategist, AI Solution Architect, AI Trainer and others be created and evolve.

Director of Data in Consumer Goods3 years ago

1. AI/ML Engineer
2. AI Ethicist
3. AI Product Manager
4. AI/ML Educator
5. Data Labeling Specialist
6. Data Privacy Officer
7. Prompt Engineer

CTO in Software3 years ago

AI Translator
Data Curator
MLOps Engineer
Explainable AI Specialist
Data Privacy Specialist
AI Ethics Officer

Senior Director of Engineering in Software3 years ago

I don't see a lot of new roles emerging. I see more demand for the already existing AI / ML roles.

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With AI and Machine Learning advancing, what new roles do you see emerging in the data and analytics space?

Sort by:

Content you might like

Are you planning a project to transition existing manual app testing to automated testing?

Should public companies be required to have at least one board member with cyber experience?

What "tells" have you noticed for AI-generated text (i.e., typical words/phrases, or other patterns indicative of GenAI)?

What team compositions and skill sets do you think are essential for AI-enabled IT organizations? What roles or functions are critical to have as you build AI capabilities?

Is your organization pursuing large-scale AI enablement, such as enterprise-wide access to tools like Microsoft Copilot, or are you focusing on high-value use cases within specific functions? Why have you chosen that approach?

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