Artificial intelligence (AI) is rapidly transforming the workplace across Asia, and generative AI, a subfield of AI concerned with creating new content, is no exception. However, a concerning disconnect exists between leadership's perception of generative AI training and the reality experienced by managers and employees.
This article explores this gap and suggests solutions for organisations in Asia to bridge the divide and effectively train their Asian workforce for the future in generative AI.
The Disconnect Between Perception and Reality
A recent Upwork survey revealed a significant discrepancy between C-suite executives' perceptions of generative AI training and the actual experience of employees. While nearly three-quarters (73%) of executives believe their companies offer comprehensive training, only 37% of employees report receiving such training. This disconnect highlights a crucial gap that organisations need to address.
Why a Broad-Brush Approach Won't Work
Simply providing generic AI training is insufficient. Leaders often adopt a "check-the-box" mentality, assuming a one-size-fits-all approach fulfills training needs. However, effective AI training requires a more nuanced and personalised strategy. For example, some companies are exploring how AI can clone your voice, your face and even your insights, requiring specialized training.
Individual Responsibility and Continuous Learning
The onus for addressing this gap lies not solely with employers but also with individual employees. The current learning landscape empowers individuals to take charge of their upskilling and reskilling journeys. While employees may feel burnt out from constant change, the call to action for continuous learning remains crucial. This is especially true in regions like Southeast Asia, where AI's Trust Deficit can hinder adoption.
How Leaders Can Bridge Gap Using with Generative AI training in Asia
Organisations can bridge the training gap by adopting a multi-pronged approach:
Developing a formal generative AI skills program: This program should provide employees with the necessary skills and knowledge to leverage generative AI effectively.,Creating a well-defined generative AI strategy: A clear strategy ensures alignment between leadership and workforce regarding AI implementation and training goals.,Prioritizing learning and experimentation: Organizations must prioritize learning and experimentation alongside efficiency to foster a culture of continuous improvement and adaptation. This proactive stance is echoed in discussions about what every worker needs to answer: What Is Your Non-Machine Premium?.
Fostering a Generative AI Community
Upskilling and reskilling programs are essential, but fostering a vibrant, generative AI community within the organization is equally important. This can be achieved through:
Creating online forums: These forums allow employees to share best practices, troubleshoot challenges, and learn from each other's experiences.,Organising "prompt-athons": Similar to hackathons, these events encourage employees to experiment with generative AI prompts in a collaborative and competitive setting.,Developing leaderboards: Recognizing and rewarding employees who excel in using generative AI prompts can incentivize participation and foster a sense of healthy competition.
The Future of Work and Generative AI
A majority of learning and development professionals acknowledge the importance of proactively equipping employees with the skills needed to navigate the evolving workplace. Generative AI has the potential to usher in a new era of productivity, but only if organizations embrace continuous learning and redesign jobs around these new capabilities. This aligns with broader trends in APAC AI in 2026: 4 Trends You Need To Know.
Conclusion
Bridging the generative AI training gap is critical for organisations in Asia to prepare their workforce for the future. By adopting a comprehensive approach that combines strategic training, community building, and a culture of continuous learning, organisations can empower their employees to leverage the transformative power of generative AI and thrive in the ever-evolving workplace. Read more about generative AI training in Asia at the WEF.
Is your organisation fostering a future of innovation or clinging to the productivity paradox of the past? Let us know in the comments below!
Latest Comments (4)
This "unusual behaviour" from Copilot is definitely concerning, especially when we're talking about integrating AI into diverse Asian workforces. It makes you wonder how these models are truly being trained – is it solely on western datasets, perhaps? That could explain some of the disprepancies, noh? We need more transparency about their development to ensure safety and cultural relevance.
This "Generative AI Training Discrepancy" article really caught my eye. The mention of Copilot's "unusual behaviour" particularly makes me wonder. It’s not just about safety, is it? More, perhaps, about the inherent biases in the datasets themselves. We’ve seen these issues across various applications, but with generative AI, the potential for these disparities to be amplified is quite concerning. Are they looking at a more diverse, culturally nuanced data collection approach, or is it still a somewhat Western-centric modelling strategy? That’s the real crux of the biscuit, if you ask me. It’s a bigger puzzle than just fixing a glitch.
Hmm, interesting points raised. While the Copilot behaviour is certainly concerning, I wonder if the "discrepancy" isn't just a learning curve for us here in Asia. Perhaps we're expecting too much too soon from these generative AI models. It's early days, after all.
Quite the head scratcher, this Copilot kerfuffle! Here in Singapore, with our push for Smart Nation initiatives and generative AI, these "unusual behaviours" are definitely something we're keeping an eye on. It underscores the need for robust testing, especially before widespread deployment in our local enterprises. Can't be having unexpected hiccups, you know?
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