Constraints 360 Assessment covers eight assessment areas. Together, they provide holistic landscape view to current state of bottlenecks and roadblocks that prevent achieving AI at Scale.
Assessment is about identifying bottlenecks and roadblocks with good understanding of their nature: What they are and how they prevent achieving AI at Scale.
Before assessment, good questions to ask are as follows:
- “What prevents us from flourishing in the Age of AI?”
- “What prevents us from achieving AI at Scale?”
- “What is needed to do hundreds of concurrent AI use cases?”
Constraints 360 Assessment outcome – that is, constraints identified and understood – is the foundation for systematic digital capability build-up towards true AI Organization. Long-term goal is to have AI embedded in all aspects of value creation for higher customer value, better customer experience and enhanced operational efficiency.
Assessment areas for holistic landscape view are as follows:
Strategic Management – Strategic management appears as a constraint when organization lacks direction, focus or push to stay competitive in AI-defined business environment. This results in constantly weakeaning financial performance due to poor pricing power, high-cost operations and low margins. Assessment covers business strategy, digital strategy, execution plan and change management.
Digitalization – Digital characteristics of products, services, business processes and business systems create the foundation for AI integration in order to embed AI in all aspects of value creation. Significant shortcomings in digitalization become severe constraints for AI at Scale.
Cloud Migration – Cloud computing is about modularity, scalability and elasticity. In addition, cloud computing provides cutting edge tools for data management, AI engineering and software engineering. All of these are essential to do AI at Scale. Incomplete cloud migration is prone to create constraints.
Data Management – AI use cases are dependent on reliable high-quality data. Established data management ensures that AI models are trained on good data, produce reliable outcomes, and can be trusted by stakeholders. Constraints assessment covers data integration, DataOps and data governance.
AI Engineering – Maturity of AI engineering has decisive impact on AI utilization. AI practises, tools and skills appear as constraints when AI use cases with high perceived value cannot be implemented. Assessment covers AI technology utilization, AI model lifecycle management, MLOps, and business alignment.
Software Engineering – To embed AI in all aspects of value creation is to integrate AI use cases and models in products, services and processes. This is the job for software engineering with enterprise application becoming the ultimate AI use case integration point. Outdated software engineering practises form severe contraint to do AI at Scale. Constraints assessment covers maturity of DevOps practises and AI model integration.
Operating Model – While AI technology evolution creates the push, it is operating model that creates organizational pull to match that push. The way digital capabilities are organized and managed thru operating model design and deployment will ultimately determine resulting AI utilization scale. Assessment focuses on ownership of data assets and digital capabilities, operational bottlenecks, and sustained digital innovation.
Data Culture – Together with operating model, data culture creates organizational pull to match AI technology push. Strong data culture leads to proactivity in data and AI utilization: Business capability owners seek to leverage AI to improve performance on their own, without centralized control or push. Constraints assessment focuses on data literacy, data vision and data values as tangible ways to create strong data culture.
Digital Ecosystem consisting of platform, tool and service providers is utilized extensively to alleviate bottlenecks and to eliminate constraints. Digital ecosystem cuts across all assessment areas. It is not an assessment area of its own. Rather, ecosystem utilization is assessed in the context of each assessment area.
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