Emerging Technologies

AI: 3 important considerations for leaders as large language models transform business

LLMs have an increased potential to automate jobs that involve repetitive and routine use of language.

LLMs have an increased potential to automate jobs that involve repetitive and routine use of language. Image: Unsplash/Clem Onojeghuo

David Elliott
Senior Writer, Forum Agenda
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Artificial Intelligence

  • Large language models such as OpenAI’s ChatGPT are revolutionizing business.
  • Up to 40% of jobs could be transformed by such generative AI technology.
  • The World Economic Forum white paper, Jobs of Tomorrow: Large Language Models and Jobs – A Business Toolkit, presents a guide to help leaders navigate the changes.

In November 2022, generative AI hit the public consciousness with the launch of OpenAI’s ChatGPT.

Much of the conversation since has focused on how such large language models (LLMs) will affect the world of work – and some workers are understandably nervous. Towards the end of 2023, for example, global searches for “Is my job safe?” doubled.

Recent World Economic Forum research found that LLMs will impact job tasks rather than jobs as a whole, and could augment many roles, offering the potential for job growth. Even so, over 40% of working hours could ultimately be transformed – so businesses will need to move quickly to navigate these changes in the way that is best for both their organizations and their employees.

Here are three areas leaders need to consider as they do so, outlined in Jobs of Tomorrow: Large Language Models and Jobs – A Business Toolkit, a white paper written by the World Economic Forum in collaboration with Accenture.

Table showcasing the summary of business strategies in each of the primary three concerns.
A business strategy matrix for effectively leading the workforce transition through the large-scale deployment of LLMs. Image: Jobs of Tomorrow: Large Language Models and Jobs – A Business Toolkit

1. Job change and job displacement risk

Job tasks with the highest potential for automation by LLMs are those that use language in a routine and repetitive manner – and roles emphasizing these types of tasks could see a decline. At the same time, LLMs could augment many jobs, assisting with those that rely on abstract reasoning and problem-solving skills.

Organizations should respond by supporting workers through any disruption, the report says. Using predictive analytics to forecast the jobs most likely to be affected by LLMs will empower employees with the knowledge to make better decisions as they look to reskill or move to a new role. This will increase trust and wellbeing, as well as performance and business accountability.

Alongside, creating an internal job marketplace that helps employees understand available opportunities and transition into new roles will provide workers with growth opportunities and firms with a tool to address talent shortages.

All of this should be underpinned by a culture that values and rewards flexibility in job roles. Encouraging employees to embrace diverse work experiences and develop skills useful across different roles will increase workforce agility – and could reduce anxiety around job displacement.

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2. Job quality

Some of the concern around LLMs in the workplace has focused on whether the technology will make jobs less fulfilling, inclusive and fair. The Forum report highlights that emerging data shows LLMs in fact have potential to improve job quality by making room for more creativity, problem solving and independent decision-making.

Ensuring this happens will rely on organizations including workers in the governance of LLMs, involving diverse teams in their development, and promoting awareness around the benefits of new tools.

For example, LLMs have the greatest impact when developed and used by teams with a diverse mix of skills and perspectives, helping to reduce bias and implement required operational changes – 92% of companies that scale AI effectively use cross-platform, multidisciplinary teams.

Transparent and inclusive governance is also key to effective deployments and building trust. This can be achieved through the creation of frameworks that explain how LLM design and use should be guided by participative decisions, employee feedback and ongoing assessment and refinement.

3. Skilling and learning

Business leaders estimate that 44% of workers’ skills will be disrupted in the next five years, according to the World Economic Forum Future of Jobs Report 2023. As such, training will need to focus on the skills predicted to grow the most – including analytical skills, creative thinking, technology literacy and lifelong learning.

Businesses can address this by increasing LLM fluency among their workforces with courses that explain the technology’s opportunities and limitations. This will help employees understand how their jobs will evolve, how they can use AI, and its benefits to the organization.

Work-based learning opportunities, such as apprenticeships and temporary assignments, are an effective way of keeping employees’ skills current and creating a culture of lifelong learning, the report says.

Alongside these literacy and skilling programmes, which will help build confidence in LLMs and encourage their use, businesses should develop a skills-first approach to upskilling and hiring. This involves ensuring a person has the right competencies – rather than the right degree or previous job title – for a particular role. And it can have a big impact – some studies have shown that companies hiring based on skills are 36% less likely to face talent and skills shortages.

The potential of LLMs in the workplace is huge, and considerations such as those outlined in the Forum’s toolkit will help guide business leaders to take advantage of the technology in a way that benefits the organization, employees and society.

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The views expressed in this article are those of the author alone and not the World Economic Forum.

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Emerging TechnologiesJobs and the Future of Work
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