McKinsey says artificial intelligence (AI) adoption (globally) increased dramatically in 2024 after years of little meaningful change. Marketsandmarkets forecasts the AI market to reach US$407 billion by 2027, experiencing substantial growth from its estimated US$86.9 billion revenue in 2022. A Forbes Advisory survey reveals that 64% of businesses believe that AI will help increase their overall productivity.
Now it’s all well and good to try out a technology and get it to work in a department or business unit. But scaling it so that a large percentage of your workforce can use the technology effectively and efficiently is another story.
Scaling AI in the workforce involves integrating artificial intelligence technologies to enhance productivity, streamline processes, and create new job roles while addressing potential challenges related to human experience, trust, and job displacement.
Ricky Kapur, head of APAC for Zoom, observes that in Asia, business leaders and CIOs are leveraging AI to strengthen productivity, collaboration and inclusion in the workplace. He cites a survey by Morning Consult and Zoom that reveals that 73% of APAC leaders hold a favourable attitude towards AI, seeing its potential time savings as a top benefit.
He asserts that AI-powered collaboration tools can help optimise meetings, assist with scheduling, and generate summaries. In so doing, employees can win back their workday and focus on strategic tasks.
Ensuring empathy and trust in the workplace
Asked what strategies organisations can use to ensure AI integration does not undermine trust and empathy in the workplace, Kapur suggests organisations should prioritise transparency, communication, and training when implementing AI.
He stresses the importance of outlining the reasons for investing in AI, including the objectives to be achieved and the opportunities it can bring for employees. He goes on to suggest that organisations should establish parameters around AI usage. He advocates implementing training and education initiatives that show employees exactly how AI can help automate certain parts of their job.
“In addition, concerns around data privacy, bias and security should be addressed to build trust. Ultimately, we believe the goal should be to harness the power of AI in a way that complements the human experience,” he went on.
Fostering a culture of learning
The Morning Consult survey also found that nearly 70% of APAC leaders say a key barrier to AI adoption is not knowing how to use it. Kapur says with multiple generations in the workforce, AI adoption should take into consideration diverse digital skills and communication preferences.
“Organisations might find interactive, video-based training for younger employees more effective, while their senior counterparts may prefer formal presentations,” he adds. “Another strategy could involve demonstrating real-life AI use cases via platforms for internal communication, designed for employees to communicate and collaborate with features that make sharing knowledge and learning easy.”
Ensure data privacy
With the accelerated adoption of digital technologies, mobile solutions and artificial intelligence tools, concerns are now rising that practices around data privacy are not catching up with the technologies.
Kapur says organisations need to articulate clearly in their communication to employees how they are ensuring data privacy. One way of doing so is to select vendors committed to secure data practices and who do not use company data to train their models.
He also stresses the importance of partnering with vendors that clearly articulate their data privacy measures and offer employees control over their information. Prioritising these practices helps maintain trust and protects sensitive data in AI-driven systems.
Balancing the benefits of AI
As advances in artificial intelligence and its use continue to deepen, fears have risen about the potential of the technology to displace humans altogether. However, some suggest that this future state of AI is still years away from being possible. In its current state, AI remains subservient to humans, and AI should be treated as a supporting technology to its human users.
“Balancing AI’s benefits while maintaining human connections involves leveraging AI to enhance, not replace, personal interaction,” says Kapur. “AI can automate routine tasks, like meeting summaries, freeing up time for more meaningful human engagement.”
“By using AI to handle administrative tasks and facilitate cross-cultural interactions, organisations can ensure that employees remain connected and focused on strategic and relational aspects of their roles. This approach strengthens team cohesion and reinforces the overall company culture, driving long-term success.”
Ricky Kapur
Best practices and pitfalls
Kapur believes that to effectively scale AI in an organisation, CIOs should ensure AI tools are accessible to the entire workforce, avoiding exclusions based on roles or cost constraints. “For example, providing AI tools at no additional cost per user can facilitate broad adoption,” he posits.
He also suggests avoiding reliance on a single AI model; instead, uses a federated approach with multiple models to stay adaptable as technology evolves.
“Common pitfalls include limiting AI access to a small group and over-dependence on one model, which may become outdated as new advancements emerge,” he concludes.
Click on the PodChats player to hear in detail Kapur’s thoughts on how to scale AI in the Workforce.
- In Asia, how do you see enterprises, led by the CIO, are arming their workforce with AI-assisted tools to improve productivity and well-being?
- What strategies can organizations use to ensure AI integration does not undermine trust and empathy in the workplace?
- What are some effective methods for fostering a culture of learning when introducing AI tools?
- How can companies ensure data privacy while using AI-driven feedback loops for workforce insights?
- How can companies balance the benefits of AI with the need to maintain human connections?
- Our topic is scaling AI in the workplace. Can you cite a couple of best practices for ensuring the proper scaling of their AI initiatives? Any pitfalls to avoid?