The Call For Action
The higher education sector, especially in professional healthcare training, is undergoing significant change. Rising student diversity, increased competition, and the need for measurable outcomes are driving institutions to rethink how they deliver education.
Key Problems Identified:
Personalize learning to match individual student needs and progress.
Use predictive analytics to forecast academic risks and enable early interventions.
Optimize faculty engagement with targeted feedback loops.
Enhance student motivation through greater visibility into their own academic journey.
Driving Change
Tangram's Solution:
Tangram delivered a 1-day bespoke AI awareness training for a leading logistics and warehousing provider in Malaysia. Designed to be highly interactive, the session combined foundational learning with hands-on engagement to build awareness and inspire practical AI integration across leadership, operations, and strategy.
Participants were introduced to core concepts of Artificial Intelligence, Machine Learning, and emerging technologies, with step-by-step breakdowns of AI systems, terminology, and ethical considerations. Live demonstrations showcased AI tools in action, including financial analysis using ChatGPT and image generation with Midjourney, offering real-time insights into automation, analytics, and content generation. The training featured industry-specific examples, fireside discussions with subject matter experts, and a case-study-driven approach that helped participants apply AI thinking across business growth stages.
Tangram’s solution also explored governance frameworks, data readiness strategies, and change management models critical to successful AI adoption. Open dialogues encouraged participants to raise real operational challenges, including document automation across various freight formats, market rate tracking, competitor intelligence, predictive analytics, and data sourcing strategies. The session empowered leadership teams with conceptual clarity and practical strategies to drive AI-driven transformation across their organization.
Impactful Outcomes
The training resulted in several impactful outcomes for the leadership team. Participants gained a clear roadmap for early-stage AI adoption, one that was closely aligned with the organisation’s strategic business objectives. They also developed a deeper understanding of how to structure and prepare internal data assets—an essential step for accelerating AI implementation and maximizing its value. In addition, the session provided a practical framework for evaluating AI tools, potential vendors, governance models, and identifying internal capability gaps. This empowered the organisation to make informed decisions around AI investments and readiness.
Following the training, several actionable next steps were identified. These included the development of a centralised data hub, the design of proof-of-concept (POC) initiatives, and the proposal to establish a Chief AI Officer role to lead AI governance and execution. Overall, the session marked a significant shift from AI exploration to strategic readiness, laying a strong foundation for future digital transformation.
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