A Prominent Insurance Provider's Path to

AI Readiness











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Project:

Through a collaborative partnership we helped our client navigate the complexities of AI readiness. Leveraging an AI readiness assessment co-developed with Gartner, we devised a structured

methodology to evaluate their strengths and weaknesses across seven critical categories necessary for AI integration.


Challenges


Through the collaborative efforts of our client's internal teams and our own independent assessment, supported by a profound understanding of their business model, we identified key areas of concern during our AI readiness evaluation. The AI readiness assessment that we co-developed with Gartner, evaluates strategic alignment, data landscape, technical infrastructure, talent, governance, ethical considerations, and stakeholder engagement


AI Readiness Discrepancies


Strategy and Goals: Disparity existed in the alignment of AI goals with business outcomes.


Data Management: Data governance structures were underdeveloped, and data readiness was overestimated.


Talent and Expertise: A gap was found between necessary AI skills and existing capabilities within the workforce.


Ethical AI: Ethical guidelines and AI governance frameworks were nascent or ill-defined.



Solution


Led by our specialised consultants, targeted remediation plans were drawn up to elevate their AI maturity to a market-ready 'MVP' status.


Strategic Alignment: Workshops were conducted with key stakeholders to define clear, measurable AI objectives linked to business outcomes.


Data Governance Enhancement: Design and implementation of robust data governance frameworks. Data literacy programs introduced to democratise data understanding across the organisation.


Technical Infrastructure Upgrade: Assessment of existing technology stacks to ensure compatibility with AI deployments. Recommendations made for scalable cloud solutions and advanced data storage systems.


Talent Development: Custom training modules designed for upskilling employees in AI and machine learning. Plans to hire AI specialists to augment the skill gap and lead internal teams.


Ethical AI Framework: Development of ethical AI guidelines and policies. Institution of a cross-functional governance team to oversight AI deployments

Key Outcomes


  • A strategic plan for AI that resonated across leadership and operational teams.


  • A data governance model ensuring data integrity, security, and availability for AI applications.


  • Augmented workforce capabilities to spearhead AI initiatives.


  • An ethical framework serving as a bedrock for responsible AI deployment.

"With Intelligen’s expertise, our client has effectively transitioned from AI aspirants to a benchmark AI-ready organisation, poised to disrupt the insurance provider’s market through intelligent automation, dynamic risk assessment, and enhanced customer experience. This case stands as a testament to Intelligen's methodical approach and commitment to turning AI ambitions into tangible, strategic assets for its clients."


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