2025 Data & AI Radar: 10 challenges to master your Data & AI transformation in 2025
Published January 17, 2025
- Data & AI
2024 has been an arduous year for Chief Data Officers and their teams. With the advent of AI, particularly generative AI, COMEX interest in and ownership of Data & AI topics, and regulations, CDOs/AI leaders have had to be on all fronts to get to grips with new topics while remaining good at their historic core activities: ensuring that the company derives maximum value from its data assets to improve its performance, decision-making, and competitiveness.
To prepare your strategies and roadmaps for 2025 (and beyond), Wavestone has analyzed the major trends that are currently occupying the daily lives of CDOs/AI leaders and will be at the heart of their challenges over the coming years.
2025 Data & AI Radar
We listed a 100+ topics sorted out in 5 categories. Each topic is sorted out from emerging to mature.
The 5 Data & AI categories for 2025 are:
- Strategy & organization
- Data governance & management
- Artificial intelligence
- Data viz and advanced analytics
- Technology & infrastructure
The main 2025 trends structuring this paper are:
- AI Industrialization
- Data Mesh
- Data Literacy
- Federated Governance
- Data Quality Management
- MLOps
- Data Products
- AI Governance
- Generative AI
- AI Act
- Responsible AI
- Data Storytelling
- Data Ops
- Data Marketplace
- Data Observability
Scaling up AI and industrializing governance
- Moving beyond the experimental stage
- AI Factory: towards a new organizational model
- MLOps: industrializing AI models
- Beyond PoCs: towards controlled industrialization
- Modular GenAI platforms
- Agents at the heart of the GenAI strategy
- AI Act: preparing for compliance
- A growing need for trusted AI
- AI cybersecurity: new threats, new protection
Data everywhere, accessible and manipulable by everyone
- A federated Data Office organization
- Unified roles and practices
- Data assets organized into Data products
- Promoting self-service via a Data Marketplace
- Citizen Data Scientist: democratizing Data Science
- Data Storytelling: the art of making Data talk
- Data Observability: real-time supervision
- Governance of unstructured Data
- AI for Data quality
Seeking return on investment
- Select the right use cases
- Systematically measure value
- Monitor adoption and performance
… and what’s next? Preparing for the future by putting people at the heart of your transformations
- Demystifying AI to reassure
- Adapting training courses to personas
- Raise awareness that without good Data, there can be no AI
- Exacerbated competition
- Rethinking your retention strategy
- Reskilling and upskilling
- Different impacts of AI on jobs
- Workforce planning strategy
- Driving change by involving social organizations
Thanks to Stéphan Mir, Guillaume Le Floch, and Ibrahim Sail for contributing to this study.
