Hello everyone, and welcome back to the Cognixia podcast. We are back with another interesting episode today. Every week, we meet to discuss a new topic from emerging digital technologies – from new developments to hands-on guides, from things you should know to what you can do to embrace new tools and best practices, and so much more.
In today’s episode, we continue our conversation about Generative AI, this time with a focus on different job roles and how managers can use Generative AI to design better job roles for the organization as well as employees. Organizations do their best to improve employee engagement and keep employee turnover as minimal as possible. But, there is one key metric, or rather a very important attribute that often gets ignored or hasn’t been checked much so far employee burnout. Surveys conducted by Gallup in the United States in 2022 showed that 40% of the employees surveyed reported that the job hurt their mental health and around 30% have shared that they regularly face burnout. About 32% have said that they feel engaged at work while 17% have said that they were actively disengaged. On a global level, the employees’ lack of engagement has been estimated to cost employers roughly $7.8 trillion, which is equivalent to a whopping 11% of the global gross domestic product, according to a report in the MIT Sloan Management Review.
Experts opine that a lot of disengagement and work stress employees go through is rooted in how organizations design job roles for the employees. Decades of extensive research by experts have discovered that poor work design leads to negative employee outcomes – mental strain, high turnover, job dissatisfaction, decreased productivity, impaired learning, etc.
The MIT Sloan research goes on to highlight that quite often, the managers in organizations lack the understanding and insight to design high-quality jobs. With the recent advances in technology, this is a very critical area in which artificial intelligence can help organizations. It can help bridge the knowledge gap among managers and enable organizations to design high-quality work which would be a win-win situation for both the organization as well as the employees, current and potential. But before the managers are empowered to do this, they need to be well-versed in the pros and cons of using Generative AI for work design.
To understand where the job role design quality flounders, we first take a look at understanding what determines whether a job role is high-quality or not. The SMART design model designed by Sharon Parker defines high-quality work as
- Is Stimulating, i.e., jobs have considerable task variety and provide opportunities to learn new skills
- Incorporates Mastery, i.e., has a clarity of what the role entails and gives the individual ample feedback to improve
- Is Agentic, i.e., provides for job autonomy and change participation
- Is Relational, i.e., one that provides the individual with social support and positive teamwork opportunities
- Is Tolerable, i.e., has manageable work hours and reasonable levels of time pressure
Now this framework helps an organization understand how to design good and high-quality job roles, and yet, poorly designed jobs are way more prevalent in the world. According to the Gallup survey, only 40% of employed Americans are engaged in job roles that follow the SMART principles.
In line with this, a new report by the World Economic Forum called Job of Tomorrow highlights the potential impact of large language models on job tasks. Generative AI is changing the way we work while it is also reshaping the nature of the work itself. The need of the hour then would be to harmonize the potential of Generative AI’s potential with the disruptions it causes. Organizations would need to put new talent management strategies in place so the employees can transition into new roles and new roles can be designed with the SMART principles in mind.
Generative AI has the potential to revolutionize the way organizations and managers design job roles. It has the power and capability to understand and process humongous amounts of data, generate creative text formats, and can derive & deliver valuable insights into human behavior.
So, what can Generative AI do for managers that can help them design better job roles for team members and employees?
Generative AI can help analyze job descriptions, industry trends, employee data, etc. which would help managers identify specific skills, knowledge, and competencies that would be required for each role. Using this, managers can define accurate and current job descriptions, based on which candidates can also understand the job role better. A well-written, accurate job description can go a long way in attracting the right candidates who would be the perfect fit for the position.
Generative AI can help managers analyze the existing workflows & task assignments, thereby helping identify opportunities and scope for improvement. Generative AI can help managers further by suggesting alternative task arrangements or automating repetitive tasks. As a result, workflows can be optimized, and employee productivity will improve too.
Using Generative AI, managers can focus and excel at designing job roles that offer greater autonomy and decision-making authority. This, as we mentioned before, is one of the principles of the SMART framework. This is possible because managers can use Generative AI to get better and deeper insights into employee preferences & expectations around the principles of autonomy and decision-making.
Additionally, Generative AI can be used by managers to understand individual needs and preferences better. Generative AI tools can analyze large amounts of employee feedback and employee performance data captured over time. This would help identify individual strengths, weaknesses, as well as preferences for individual job roles. This information can be immensely helpful in designing job roles for employees by giving the managers an all-around outlook of the job roles and their different aspects, the skills, and knowledge required for the role, etc. Eventually, this would also help improve employee satisfaction and retention.
One word of caution here is that while Generative AI can prove to be very helpful for managers in designing and developing high-quality job roles, it cannot be a replacement for human expertise. Generative AI can make useful suggestions, but managers would still need to use their judgment, discretion, knowledge, and learnings from their experience, the company culture in their organization, the organizational goals, the situation that is driving the need for this job role, team dynamics, as well as their first-hand understanding of the situation before making any decisions or finalizing any job roles.
To make all of this happen, the most important starting point is to ask Generative AI the right questions, giving it the right prompts, which would then enable Generative AI to deliver the right outputs. Learning prompt engineering could be a critical skill for managers and just about everyone in this rapidly evolving world we live in where we are yet to even scratch the surface properly when it comes to exploring the potential of Generative AI. To learn more about Generative AI, check out Cognixia’s live online instructor-led training and certification programs in Generative AI. These programs are designed to help learners get a deeper understanding of what is Generative AI, how it functions, and how it can be leveraged to be a very useful ally at work. You can visit our website – www.cognixia.com for more details. You can connect with us directly over the chat function there, and we will help answer all your questions there.
With that, we come to the end of this week’s Cognixia podcast episode. We hope you enjoyed listening to us today and were able to learn something new & interesting from the episode. We will be back again next week with another insightful new episode of the Cognixia podcast. Until then, happy learning.