Data & AI roadmap
Structuring a dedicated data & AI roadmap and mobilising the associated resources — human, organisational and technical — are key success factors if we are to exploit the full potential of these technologies.
How can we transform and create value through data and AI?
The abundance of enterprise data and the power of AI, particularly with the recent emergence of generative AI, are key levers for achieving strategic business objectives.
In order to make the most of this data asset, coupled with technological innovations, the IT Department needs to structure itself to offer a value production chain that serves the company’s use cases.
80% of companies believe that data is becoming a priority issue within their business, particularly with the rise of generative AI. 2024 Data Management Barometer — Capgemini Invent x Quantmetry — January 2024
In all sectors, companies are getting into gear to control and exploit their data.
Today, data and AI represent a key lever for improving operational efficiency, customer satisfaction and/or regulatory compliance.
Once the stage of exploration and localised experimentation is over, a data roadmap that is shared with all the stakeholders, that is genuinely implementable and creates value, will enable this data transformation to be supported and sustained over the long term.
This data roadmap will be all the more concrete and actionable if there is a global vision at organisational level:
- Provide a high-level vision to ensure strong sponsorship from senior management and align data priorities with the company’s strategic ambitions,
- Align the data roadmap with the IT roadmap to integrate the needs and constraints in terms of technological prerequisites for going live,
- Identify the organisational resources needed to support the data & AI trajectory,
- Adopt MLOps (practices and tools for the commercial use of AI) to professionalise and industrialise your AI capabilities,
- Measure and manage the impact of data projects,
- Encourage business, data and IT teams to work together to design use cases,
- Ensure that the tools and solutions are taken on board by the business lines.
How we can help
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Analysis of the existing situation and definition of objectives
Using a multi-dimensional approach, identify a concrete and achievable ROI through the Business, Data, Model and Application framework.
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Sourcing use cases: ideation, qualification and costing
A series of workshops bringing together various stakeholders and end-users to identify areas for discussion and even data and AI opportunities to be seized.
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ROI-driven prioritisation
Score the portfolio of use cases through the prism of ROI to identify your priorities and ensure concrete results.
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Draw up your data & AI roadmap and the prerequisites
Map and plan the priority projects, including the technical resources (Cloud, Data and AI technologies, etc.), human resources (architecture, governance, skills, change management, etc.) and key processes and practices (Make or Buy directives, MLOps, etc.) required to deploy the Data & AI trajectory.