Drive more effective collaboration with the right target operating model for AI
Data and AI capabilities are typically spread across multiple departments and functions. This often leads to operational inefficiencies: work is duplicated, while topics of cross-functional importance are neglected. To avoid this friction, organisations need a clear AI Target Operating Model (AI TOM). It defines organisational structures, roles and responsibilities – enabling efficient collaboration and targeted use of resources.
We support you in designing and implementing a fit-for-purpose AI target operating model that consolidates existing capabilities and provides a robust foundation for enterprise-wide collaboration on data and AI initiatives.
“Particularly in medium-sized and large organisations, an AI TOM is indispensable. It prevents waste of time and resources and accelerates initiatives in the dynamic field of data & AI innovation.”
What sets PwC’s AI Target Operating Model services apart
Successfully operationalising AI systems and data-driven solutions
In a very short time, artificial intelligence has evolved from a technological testbed into a key driver of competitive advantage. Yet the value creation potential of AI often fails at the organisational level. Data and AI capabilities and resources are frequently distributed across different departments. Teams work in isolation on similar problems, while collaboration between IT, business, analytics and compliance is patchy. Synergies are lost.
A clearly defined AI Target Operating Model establishes guardrails for enterprise-wide collaboration on data and AI. It provides an essential operational backbone that places AI initiatives on a common footing, standardises processes and enables sustainable collaboration. It also counteracts fragmented governance and reduces risks relating to data protection, data quality and regulatory compliance.
Benefits of an effective AI target operating model
By implementing such an operating model, organisational barriers can be systematically overcome. The AI TOM establishes consistent ways of working with data and AI across the organisation. It creates clear allocation of responsibilities and aligns leadership around shared objectives. This leads to significantly better collaboration and interaction between organisational units. Instead of working in silos, the cogs of the organisation mesh seamlessly.
“A tailored AI TOM increases the efficiency, innovative strength and speed with which companies can deploy AI solutions to the market or for internal use.”
Bring clarity to your AI organisation
Rely on a tailored operating model for data and AI
How we support you with your AI Target Operating Model
- Status quo analysis
- Design of the AI TOM
- Processes and steering
- Governance design
- Implementation plan
Status quo analysis
How mature are your current capabilities for using data and AI? Which structures and processes are already in place? Through a robust assessment of the current state, we identify gaps and redundancies and create the basis for targeted improvements to the operating model.
Design of the AI TOM
Based on your specific situation, we develop tailored frameworks for AI that define roles, responsibilities, decision rights and interaction patterns. The operating model also sets out which metrics will be measured and which targets should be achieved.
Processes and steering
Binding standards are key to establishing consistent ways of working across the organisation and avoiding data and process silos. We define and implement standardised processes and clear responsibilities to ensure the efficient use of AI.
Governance design
For data-processing systems and AI solutions, robust governance is critical. Inconsistent policies and controls create risks in terms of data protection, data quality and regulatory compliance. We establish scalable governance models that connect different oversight bodies, balance control with agility, and ensure consistent enforcement of standards.
Implementation plan
We help you prioritise AI initiatives according to their business impact and available resources, and develop clear roadmaps for phased implementation.
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