The rapid advancements in generative AI are changing strategic agendas and impacting the responsibilities of data and analytics (D&A) leaders and their functions in diverse ways. Access this report to learn how D&A leaders are shaping GenAI initiatives and the key challenges they face.
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Head of Data Science and AI
Get actionable, objective insight to help you and your team drive artificial intelligence projects forward and unlock new value for the business.
How data and analytics leaders are shaping generative AI initiatives
AI value creation accelerates with adoption
The AI adoption phases are intended to provide D&A leaders with a framework for their AI strategy. Organizations will find that their required timeline for AI adoption will vary with different categories of AI application. The AI adoption curve is not linear.
Top challenges for heads of data science and AI
Become an AI-First Organization: 5 Critical AI Adoption Phases
Optimize your AI strategy and implementations to deliver value, make tangible business impact and mitigate risk, while managing cost.
Support Advanced Analytics and AI Initiatives With the Right Roles and Skills
Define core AI and ML roles, skills and responsibilities to help align them for advanced analytics initiatives.
Get Your Enterprise AI Ready
Focus on four key initiatives to map your AI ambitions as you explore and commit to different AI opportunities.
Close the Data Science Talent Gap by Hiring and Upskilling Internally
Read this case study to learn how Eastman drove value and overcame data science talent challenges in a competitive market.
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