Founder & Director of Workmetrics, a leader in workforce software. Completed a Doctorate of Information Technology at Murdoch University.
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As the latest hot topic in the tech world, generative AI is increasingly becoming perceived as the next cornerstone of products and services that will change the nature of work.
There’s a good reason for this optimism: The technology’s selling point is the creation of new data or information like text, audio, video or photos based on provided input. With such a broad skill set, the applications of this branch of artificial intelligence are expanding in various directions, and workforce management is no exception.
Generative AI can be used to revamp the entire workplace, from evaluating and predicting employee performance to generating operational and personalized training programs. In a perpetually complex business world, this technology can be the linchpin that ties everything together in a seamless and more productive manner.
There is no shortage of ways generative AI will change the way HR departments operate, beginning with their approach to employee performance and productivity.
With tools such as ChatGPT and Bard having access to a year’s worth of an employee’s work, meetings and other output, HR can quickly create customized templates that prompt employees to provide specific details about their accomplishments, areas for improvement and future goals. The results can be used to identify areas where employees are excelling and where they need additional support. In turn, managers can have productive conversations during performance reviews and, ultimately, empower employees to develop in their roles.
The same principle can be applied to recruitment efforts. It’s no secret that HR often struggles to attract the right candidates. A major reason why lies in the job postings that miss the mark. By analyzing employee biographies, work histories, workplace tools and various related materials, generative AI can circumvent this challenge by creating more engaging and compelling job postings—ones that accurately reflect the position’s requirements and the company’s mission, values and vision.
As a bonus, the technology can also provide guidance on how to attract top talent by forming a profile of the ideal candidate and outlining key responsibilities, thus helping HR departments refine their approach to make the right hiring decisions.
Then, there is an entire segment of policies and procedures that can be upgraded with a language model that writes a human-like response.
For some employees, these documents are incoherent and difficult to comprehend. ChatGPT and the like can simplify things through clear and concise instructions on how to follow company policies and procedures, as well as advice on how best to handle common situations that may arise within the confines of the workplace. This would make these documents more accessible and user-friendly, helping employees understand what is expected of them and how to remain compliant with company policies and regulations.
The fusion of generative AI and management framework can be a powerful tool for a department such as Safety and its practice of contractor management. Activities such as evaluation responses, audits and the preparation of safety documentation materials like safety manuals and hazard analyses are an excellent fit for AI.
Based on a large dataset of previous contractor responses, it can pinpoint key phrases, patterns and other elements that indicate the contractor's level of safety preparedness. This can help quickly filter out those who meet set safety standards and flag those who don’t.
When it comes to conducting audits of contractor safety practices, there is a database of previous safety incidents, near misses and other relevant data to assess and extract actionable insights from (a.k.a. AI’s bread and butter). The resulting analysis can provide a map of areas most likely to be problematic, leading safety departments to focus their audits and improve their overall effectiveness.
In the same way, generative AI tools can identify key elements and best practices from existing safety documentation, then come up with new materials that are tailored to the specific needs of the organization. In doing so, safety departments save time and resources while also making certain the ensuing materials are more authentic and effectual.
Naturally, if there’s one thing we can rely on AI to do, it’s automation. The entire reporting process of work orders, equipment histories, maintenance schedules, energy expenditures, and others can be scheduled or triggered based on certain parameters, which will save time and improve accuracy in the long run.
By analyzing data on how an employee learns and performs, multimodal generative AI like GPT-4 can create training content that is more engaging, improving information retention in the process.
Employees can have personalized learning programs made for them by AI algorithms that take into account their hobbies, career aspirations, and present abilities. Moreover, the technology monitors workers' improvement, providing HR managers with crucial information about their strengths and places for further development to reach their maximum potential.
For that cause, this information can be utilized to produce a development program, together with tests, training courses and interactive content that are up-to-date and more efficient.
In a way, AI would assume the role of a coach who focuses on improving productivity and developing an individual—much like what Salesforce's Einstein GPT is doing by creating personalized content for the company’s staff.
While there are considerable challenges to factor in, such as the cost of implementation and lack of trust in the technology (one has to imagine there will also be a few employees who will resist the change), it’s hard to dismiss the massive game-changing potential.
Generative AI is the most transformative thing in the business landscape right now, perhaps even since the proliferation of the internet. Without a decent understanding of its abilities, leaders and organizations risk being left behind by the competition, which will, in all likelihood, thrive rather than flounder with the help of this technology.
For the moment, there are a few kinks to work out. At the same time, we’re bound to see more “out of the box” applications as adoption rates grow. For some businesses, it may be too late then to join the party.
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