Over the past year, the insurance industry has the challenges around attracting and retaining skilled professionals. In this fiercely competitive market, conventional approaches have proven to be not enough, with phenomena such as the "Great Resignation" and the emergence of "quiet quitting" further complicating matters.
Fortunately, a promising wave of AI tools tailored for talent management has emerged, offering potential solutions to these challenges. These innovative tools have the capacity to revolutionise the way organisations within the insurance industry identify and recruit high calibre candidates, enhance employee development initiatives, and foster long-term retention through improved engagement strategies.
However, the integration of AI in talent management brings its own unique set of challenges, necessitating careful consideration. Before insurance industry leaders embrace these cutting-edge tools, it is crucial for them to grasp the potential advantages that AI can offer their company. Equally important is the ability to anticipate and effectively address the fundamental obstacles associated with implementing AI for talent management.
Areas where AI can help revolutionise talent management
In the insurance industry, the process of finding and hiring suitable employees can be arduous, inefficient, and susceptible to biases. Traditional recruitment methods, involving job postings, resume screening, and interviews, can be time-consuming and result in delays that lead to missed opportunities with qualified candidates. Biased language in job postings can further deter applications from underrepresented groups, exacerbating the lack of diversity. Additionally, inconsistencies in matching candidates to appropriate job openings can result in missed potential for both individuals and organisations.
Fortunately, AI offers a solution by enabling the creation of accurate job postings, targeted advertisements, and efficient applicant screening processes that aim to mitigate human biases. For instance, platforms like Traitify leverage AI in candidate assessment tools, measuring actual skill demonstrations and reducing bias in the screening phase. These platforms also redirect suitable candidates who may have narrowly missed a position to other relevant job opportunities, saving recruiters time and engaging promising applicants automatically. By embracing AI-driven solutions, the insurance industry can streamline its hiring processes, enhance diversity, and maximise talent acquisition efficiency.
Talent management includes the crucial aspect of providing continuous learning and development opportunities to employees. A significant challenge in employee development lies in motivating individuals and ensuring they have access to suitable learning opportunities. Frequently, there is a lack of information about available opportunities, and organisations struggle to create high-quality content that meets the learning and growth needs of their employees.
AI presents a valuable solution to address these challenges in real-time. For instance, both Enskill and EdApp, are AI-powered learning management systems, offering personalised learning recommendations to employees based on their performance and engagement analytics. These tools allow HR leaders to swiftly create micro-learning content and track learner progress, while also enabling content revisions based on analytical insights.
Employee engagement plays a vital role in retaining top talent as it reflects the level of connection and dedication employees have towards their organisation. However, improving employee engagement proves challenging for employers due to the difficulty in accurately measuring it and addressing issues like burnout and well-being.
Thankfully, AI tools offer effective solutions by providing real-time and precise metrics to measure employee engagement, as well as developing employee-centric approaches to enhance well-being. An illustrative example is the zavvy.io platform, which combines sentiment analysis with collaboration data to assess employee engagement and well-being. By leveraging such AI-powered tools, the insurance industry can gain valuable insights and implement strategies that foster employee engagement.
Employee wellbeing is heavily influenced by workplace culture and working conditions. To effectively enhance wellbeing, insurance companies should prioritise building a strong culture and support network. While this concept is familiar to HR professionals, recent advancements have disrupted established “best practices.”
Leading companies are now adopting AI-powered technologies, such as wellbeing.ai, that enable HR teams to collect valuable feedback from employees and translate it into impactful actions that positively influence wellbeing and retention. This innovative approach allows for more meaningful insights and interventions to support employee wellbeing within the insurance industry.
Areas of concern around AI and talent management
The potential of AI Bias
Although AI has the potential to mitigate bias in decision-making, it is important to acknowledge that AI systems are not entirely free from biases. These biases can stem from the use of existing datasets, which may inadvertently perpetuate historical biases. Instances of bias in AI range from the infamous case of an Amazon AI tool that disadvantaged women applicants to sourcing algorithms that disproportionately target specific demographic groups for certain job positions.
Considering the susceptibility of AI to bias, implementing AI in talent management within the insurance industry carries the risk of producing outcomes that contradict ethical codes and organisational values, leading to negative impacts on employee engagement, morale, and productivity.
Algorithm aversion is a prevalent issue around AI technology, as people often mistrust and perceive AI-driven decisions as impersonal and less fair than human decisions, despite the potential for algorithms to eliminate biases.
This lack of trust stems from a limited understanding of AI, a loss of decision control, and a perception of impersonal and reductionistic outcomes associated with algorithmic decisions. Employees tend to perceive algorithm-based decisions as less fair when compared to decisions made by humans, as evidenced by research findings.
AI technologies have been implemented by organisations in the insurance industry for real-time employee tracking, but their poor implementation can significantly impact employee privacy, resulting in heightened stress, accelerated burnout, compromised mental well-being, and reduced autonomy.
The Covid-19 pandemic has contributed to a substantial increase in the adoption of these tracking technologies by employers, with over 50% of large organisations currently utilising AI tools for tracking purposes. It is important for employers to be aware of their potential liability, as even unintentional employment discrimination caused by AI-driven systems can hold them accountable, while the laws governing AI-related rights and responsibilities of employers and employees continue to evolve at local, national, and international levels.