How to prepare your employees for generative AI in the workplace
Exploring differences in work preferences between generations, how to recruit top talent and how to ensure organizations can embed a work culture across the workforce.
It has been a year since the launch of ChatGPT, a chatbot that became a global phenomenon overnight, ushering in an era of rapid technological innovation driven by generative AI. The series of AI advancements that followed unlocked a global competition for AI dominance and forced governments, businesses, and consumers to rethink what our world will look like in the era of generative AI.
This technology will have a profound impact on the future of work. While generative AI offers great potential to accelerate productivity and innovation, it poses new challenges to business leaders. For instance, how do organizations prepare their workforce for a future where humans and AI work together to make critical decisions and complete complex tasks? How can they adopt generative AI safely across the business? How do they make sure that no one is left behind?
Business leaders and front-line workers have different views of AI
One concern related to generative AI is that it will create new knowledge divides within organizations. Recent data from Boston Consulting Group (BCG) suggests that these divisions are most conspicuous at the hierarchical layers of the business. According to the research, 80% of leaders use generative AI regularly, versus just 20% of frontline employees. Business leaders also tend to be more optimistic about the potential of the technology, with 62% of senior decision-makers expressing this sentiment compared to 42% of frontline employees.
These disparities in attitudes towards AI could align with people’s understanding of the technology. The research indicates that 44% of leaders have received training on generative AI to sharpen their skills and stay relevant, while only 14% of frontline employees have received similar training. Familiarity with the technology, or lack thereof, seems to be causing further ruptures across the different generations within the workforce. Organizations must act quickly to bridge the generational divide.
Generational differences in AI use in the workplace are another area of concern, with research showing that over half of workers above 35 are not using AI in the workplace, while 71% of younger employees are utilizing these tools. This could create a rift between generations, leaving behind older workers who don’t have a good grasp of the technology. However, one of the most transformative attributes of generative AI is that it is very user-friendly, meaning new users can easily learn to work with the technology and use it to enhance their productivity and performance.
Earlier this year, researchers from Stanford University and the Massachusetts Institute of Technology (MIT) conducted the world’s first large-scale empirical study of the impact of generative AI on workers. The data showed that lower-skilled workers saw the biggest increase in productivity because of generative AI. This early data on the impact of the technology indicates that generative AI offers huge opportunities for organizations to improve productivity and level the playing field for all employees by freeing up more time for them to focus on more meaningful work. But to benefit from this, businesses must act quickly to bridge the AI divide and equip all employees with the right skills to make the most of generative AI.
Building a safe AI environment and fostering an AI-friendly culture
To realize the full benefits of generative AI, business leaders must empower everyone within their workforce to use the technology safely and effectively. This means building a culture of knowledge, understanding and responsibility towards AI. Before rolling out formal training, businesses should consider how they can protect their intellectual property and their employees from the risks associated with generative AI.
Allowing wide use of public AI applications such as ChatGPT comes with significant risks as all data fed into their algorithms is publicly accessible, which can expose sensitive customer data and business trade secrets to the prying eyes of malicious actors or your competitors. To mitigate those risks, organizations should consider a private AI model, which means all the data, AI algorithms, and IT infrastructure are fully controlled within the business.
In this scenario, AI models are trained exclusively on data the organization owns or has access to. Training data in a private AI environment allows the organization to gain more control over the data and the outcome. By going private, AI models remain with the organization. Therefore, unique algorithms and trade secrets remain protected for competitive advantage. This approach creates a safer environment where employees can use generative AI without exposing their organization to security risks. Most importantly, this protects data privacy of employees, customers, and business partners.
Once you have created a safe AI environment, it is essential to establish clear policies and guidelines for its use across the business and roll out a comprehensive training program that touches every part of your organization, tailored to different technical skills and levels of experience. This strategy will enable you to empower your workforce to make the most of AI and create an AI-friendly culture that nurtures a deeper understanding of the technology and an exponential increase of its benefits for the business.
We’ve featured the best online collaboration tool.
This article was produced as part of TechRadarPro’s Expert Insights channel where we feature the best and brightest minds in the technology industry today. The views expressed here are those of the author and are not necessarily those of TechRadarPro or Future plc. If you are interested in contributing find out more here: https://www.techradar.com/news/submit-your-story-to-techradar-pro