Generative AI’s Role in Job Satisfaction

Generative AI (GenAI) is a pivotal technology that enhances work in a myriad of ways. From automating complex analysis to simulating scenarios that assist in decision-making, GenAI use cases are making a big impact across a broad swath of industries, including financial services, consultancies, information technology, legal, telecommunication and more.

Certainly, organizations recognize GenAI’s potential with the increasing adoption of AI within organizations. According to a PWC survey, 73% of U.S. companies have adopted AI in some areas of their business. Yet, discussion persists about GenAI’s role within the workplace, given fears over job displacement, bias, decision-making transparency and more. Despite this, GenAI has made AI technology much more accessible to employees within organizations, regardless of their specific roles.

In fact, a LexisNexis Future of Work survey showed that 72% of professionals anticipate a positive impact from GenAI, and only 4% see it as a threat to job security. GenAI can automate mundane tasks, allowing users to focus on more specialized, impactful and strategic tasks. This, in turn, can increase employee productivity and job satisfaction while ensuring human ambition and innovation walk hand in hand.

AI’s Productivity Boost

GenAI’s rapid rise marks a crucial shift in how organizations must operate and strategize to augment every role. GenAI applications are as diverse as they are impactful. It’s not just hype; GenAI is already poised to increase labor productivity by 0.1 to 0.6% annually through 2040.

GenAI has also created value across multiple sectors and industries. Significant business functions, including Sales, Marketing, Customer Operations and Technology have leveraged GenAI to increase productivity. In technology, for example, GenAI-based coding assistants are a massive help to software developers in suggesting code snippets, refactoring code, fixing bugs, understanding complex code, writing unit tests, documentation and creating complete end-to-end applications.

As employees experiment and explore with GenAI tools, their comfort level with the technology increases. Eighty-six percent of professionals ‘agree’ or ‘strongly agree’ with a willingness to embrace GenAI for both creative and professional work. Sixty-eight percent of employees plan to use GenAI tools for work purposes, while 69% are already using these tools to assist with daily tasks. The data makes it clear that organizations that adopt GenAI can boost productivity, and employees are willing to use it to accelerate efficiency.

Productivity Gains Are a Given, But Also AI Helps with Job Satisfaction

One of the most significant opportunities around GenAI lies in its power to help with job satisfaction. While professionals have fairly balanced expectations on how far adoption will go, 82% expect generative AI to take over a range of repetitive administrative tasks by automating routine tasks and data analysis, freeing them to focus on more strategic aspects of their work.

When asked how they perceive GenAI’s role in the work environment, more than two-thirds of professionals see it as a ‘helpful tool’ or ‘supportive co-worker.’ As a result, they recognize AI’s potential to enhance, not hinder, job performance and are embracing it with a positive mindset toward eliminating repetitive tasks and freeing up time for more rewarding, higher-value work.

Most professionals do not see generative AI as a detriment to job satisfaction, either. Over half (51%) say job satisfaction has improved significantly or moderately thanks to GenAI, while only 10% felt that it decreases job satisfaction. A fundamental rethink is necessary where and how organizations implement GenAI tools within the workplace.

Recommendations to Improve Engagement and Job Satisfaction

Organizations need to consider employee engagement throughout the adoption process of GenAI tools. Here are some recommendations to improve engagement and thereby increase job satisfaction:

• Engage your employees to identify the use cases that are most impactful for a particular role or group. Pick tasks that are most time-consuming and tedious, such that solving them would free up time to focus on more critical items.
• Identify the GenAI tools and large language models (LLMs) that are most effective for solving the identified use case. Take the time to experiment, test and validate the output. Ensure that you account for a diverse set of inputs for the use case and measure the output quality, including the hallucination rate, to help build trust within your employee base using the solution.
• Provide training to your team. Take advantage of the vast information available on the web, with videos, code samples, tool vendor resources and tutorials on using the specific tool, LLM, associated prompts and guardrails. Create mentors and experts within the team to help coach the rest. Showcase examples of lessons learned and success stories to inspire team members who may not see the value.
• Identify and measure KPIs. These could include adoption, productivity gains, costs saved or repurposed, employee satisfaction, quality improvement and other KPIs that may be specific to the team or business.

Gen AI isn’t just for technologists anymore; it’s making potent tools accessible to everyone. Most business professionals who once viewed these technologies with skepticism now accept and even welcome them. And it’s no secret why, given GenAI’s power to present organizations and employees alike with unprecedented opportunities toward the future of work.