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Home Business Bridging the AI Divide: How to prepare your employees for generative AI in the workplace

Bridging the AI Divide: How to prepare your employees for generative AI in the workplace

by Jessica Weisman-Pitts
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Bridging the AI Divide: How to prepare your employees for generative AI in the workplace

By Susan Charnaux, Chief People Officer, Appian

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 organisations 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 organisations. 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.

Organisations 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 utilising 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 organisations 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 realise 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, organisations 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 organisation owns or has access to. Training data in a private AI environment allows the organisation to gain more control over the data and the outcome. By going private, AI models remain with the organisation. 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 organisation 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 programme that touches every part of your organisation, 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.

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Jessica Weisman-Pitts

Jesse Pitts has been with the Global Banking & Finance Review since 2016, serving in various capacities, including Graphic Designer, Content Publisher, and Editorial Assistant. As the sole graphic designer for the company, Jesse plays a crucial role in shaping the visual identity of Global Banking & Finance Review. Additionally, Jesse manages the publishing of content across multiple platforms, including Global Banking & Finance Review, Asset Digest, Biz Dispatch, Blockchain Tribune, Business Express, Brands Journal, Companies Digest, Economy Standard, Entrepreneur Tribune, Finance Digest, Fintech Herald, Global Islamic Finance Magazine, International Releases, Online World News, Luxury Adviser, Palmbay Herald, Startup Observer, Technology Dispatch, Trading Herald, and Wealth Tribune.