Unpacked: Totara Thursdays

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otara’s approach to AI is not about chasing features or automating for the sake of it. In this Rapid Fire edition, we explore how practical, permission-based AI capabilities can strengthen learning, performance, and accountability, while exposing the maturity of the systems already in place. The real opportunity is not simply adopting AI, but using it with structure, control, and clear organisational intent.
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Totara’s AI features promise a lot, but where do they actually create value? This article takes a practical look at how these capabilities support real learning and performance outcomes. Moving beyond feature lists, it explores where AI reduces friction, where it falls short, and how organisations can apply it meaningfully within their learning ecosystem.
Retail organisations are investing heavily in training, yet performance gaps on the shop floor persist. With frontline turnover often exceeding 50–70% globally, the challenge is not content, but how quickly and consistently employees can perform. This article explores why traditional approaches fall short, and how learning can be repositioned with Totara as a system that directly supports operational performance and commercial outcomes.

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