Mitigating Risk with a Framework for Evaluating AI Solutions   

In the rapidly evolving landscape of HR tech, health and wellness, and employee benefits, harnessing the power of AI has become paramount for organizations aiming to stay competitive and offer superior experiences to their workforce and clients.  

We have worked with clients to improve their operational efficiency and enhance their patient experience through AI. With this experience we’ve been able to help our ecosystem make informed business decisions that help drive innovation.  

Through the insights gathered from our generative AI consulting engagements, we’ve developed an AI framework tailored for C-suite leaders aimed at evaluating AI platforms that can bring transformative benefits across these industries. 

Approaching AI Deployment from a Departmental Perspective

When considering the deployment of AI within the HR tech and employee benefits space, it is crucial to approach the evaluation process from the perspective of departments, business functions, or delivery areas rather than taking a larger enterprise-wide approach. This focused lens allows for a clear definition of the concrete tasks AI can effectively solve. 

HR tech and employee benefit leaders can identify the specific applications of AI in HR functions by understanding seven areas addressed through AI and breaking them down into three cognitive tasks. One such example is chatbots for employee support, which can revolutionize how organizations provide information and assistance to their workforce. Evaluating these areas and cognitive tasks will guide the evaluation of AI solutions and their potential impact on HR processes and employee benefits. 

Here are the seven areas that HR tech and employee benefits leaders can address with AI: 

  1. Customer Support: Utilize AI to provide information, solutions, or predictions based on patterns to field employee questions on policies, practices, and more. 
  1. Data Analysis: Use AI to visualize, manipulate, or transform data to infer meaningful insights in areas such as employee performance, engagement, and retention. 
  1. Demand Forecasting: Leverage historical data to forecast different areas of customer demand, such as predicting future hiring needs or employee benefits preferences. 
  1. Fraud Detection: Utilize AI to detect various forms of fraud within and external to the organization, such as identifying fraudulent benefit claims. 
  1. Image & Video Recognition: Use AI to analyze images and videos to recognize patterns and datasets that can be used for tasks like facial recognition for attendance tracking or analyzing employee sentiment from video interviews. 
  1. Predicting Customer Behavior: Apply AI to segment and analyze patterns to anticipate customers’ future behavior, such as identifying potential attrition risks or personalized benefits recommendations. 
  1. Productivity Improvement: Use AI to automate time-intensive tasks around data and repetition, increasing productivity in areas like payroll processing or benefits administration. 

These areas can be further broken down into three cognitive tasks that inform the types of AI solutions to evaluate: 

  1. Cognitive Automation: This task aims to automate administrative and financial functions in the back office. These AI tools can input and consume information across IT systems, streamlining processes and increasing efficiency in tasks like data entry, payroll processing, and benefits administration. 
  1. Cognitive Insight: The output relies on algorithms to detect data patterns and interpret their meaning. Leaders can identify AI tools to analyze and visualize data to infer meaningful insights by evaluating areas where mental insight can be applied. This helps gain valuable insights from large datasets, identify trends, and make data-driven decisions in areas such as employee performance analysis, engagement measurement, and talent management. 
  1. Cognitive Engagement: This task uses natural language processing to interact with employees or customers. Users can enhance customer support, improve employee experience, and personalize interactions by using AI tools to answer questions, predict outcomes, and provide support from a knowledge base in employee self-service, benefits inquiries, and onboarding processes. 

By breaking down the seven areas into cognitive tasks, organizations can identify the specific applications of AI in HR functions and evaluate AI solutions accordingly. For example, if an organization wants to address customer support through AI, it can assess chatbots that use natural language processing to provide support from a knowledge base (Cognitive Engagement).  

This approach ensures that the AI solutions selected align with the desired outcomes of replacing current activities, increasing efficiency, and increasing effectiveness. Additionally, it helps organizations identify potential challenges and develop strategies to overcome them, such as providing employee training or addressing ethical considerations. 

Evaluating AI Solutions Based on Outcomes

Organizations should assess whether the tool achieves desired outcomes when implementing AI solutions. When working with our clients to ensure seamless implementation and integration, the Archetype team provides a structured approach based on the outcomes achieved. Any AI solution being considered should achieve at least one, if not more, of the results listed below: 

  • Replacing Current Activity: An AI solution should be able to eliminate a task or responsibility that a human is currently performing. By automating repetitive or manual tasks, AI can reduce overhead costs and increase productivity. This outcome focuses on streamlining operations and freeing human resources for more strategic and value-added activities. 
  • Increasing Efficiency: AI should cut down on time and increase the capacity to accomplish a task. By leveraging algorithms and data analysis, AI can streamline processes, reduce errors, and improve efficiency. This outcome aims to optimize workflows, improve resource allocation, and enhance operational performance. 
  • Increasing Effectiveness: AI should elevate work conducted by the organization to make it more effective or have a more significant impact. This outcome involves leveraging AI to enhance decision-making, improve accuracy, and remove human error or bias. AI can provide valuable insights, predictions, and recommendations, enabling organizations to make more informed and effective choices. 

In addition, organizations should consider five factors to ensure the suitability of the AI solution for implementation. These factors ensure the tools align with the company’s goals, resources, and capabilities. 

  • Ground Truth: Refers to the accuracy of the training data in highlighting positive and negative data. The training data should be correct, and representative of the real-world scenarios the AI tool will encounter. 
  • Risk: Consider whether the tool poses any legal risks, potential harm to individuals or society, or reputational risks to the organization. Low-risk solutions have minimal legal and ethical implications. 
  • Cost: Evaluate whether the solution requires a low-cost subscription model or a significant investment. Consider the financial feasibility and return on investment of the AI solution. 
  • Ease of Adoption: Consider the level of technological literacy required and whether the tool is user-friendly. A highly adaptable solution is easy to understand, implement, and integrate into existing workflows. 
  • Complexity: Low-complexity solutions are off-the-shelf tools that require minimal customization or implementation effort. High-complexity solutions may require significant investment, customization, and ongoing maintenance. Consider the level of training, execution, and support needed for the AI solution. 

Evaluating AI solutions based on these factors helps ensure that the chosen solution aligns with the desired outcomes of replacing current activities, increasing efficiency, and increasing effectiveness. 

Use Cases for AI in HR Tech and Employee Benefits

There are numerous examples of successful AI implementation in various organizations, showcasing its potential benefits to the HR tech and employee benefits space. For instance: 

  • Chatbots for Employee Support: AI-powered chatbots can provide instant support to employees, answering common questions about policies, benefits, and HR processes. These chatbots use natural language processing to understand and respond to employee inquiries, improving response times and reducing the workload on HR teams. 
  • Predictive Analytics for Employee Retention: AI algorithms can analyze employee data and identify patterns that indicate the likelihood of attrition. By leveraging predictive analytics, organizations can proactively take steps to retain valuable employees, such as offering personalized incentives or development opportunities. 
  • AI-Powered Recruitment Tools: AI can streamline recruitment by automating resume screening, identifying top candidates, and conducting initial interviews. These tools use machine learning algorithms to match job requirements with candidate profiles, saving time and improving the efficiency of the hiring process. 
  • Personalized Benefits Recommendations: AI can analyze employee data, preferences, and behavior to provide customized benefits recommendations. Organizations can offer tailored benefits packages that improve employee satisfaction and engagement by understanding individual needs and preferences. 

Challenges of Implementing AI in HR Tech and Employee Benefits

Implementing AI in the HR tech and employee benefits space presents several challenges that organizations must address. These challenges include the need for high-quality data, the potential for bias, and the requirement for employee training. Overcoming these challenges is crucial to ensure the successful implementation of AI solutions. 

To address the challenge of high-quality data, organizations should focus on collecting and cleaning data from various sources. It is important to ensure the data used to train and validate AI models is accurate and representative of real-world scenarios. Data augmentation techniques can also be employed to increase the quantity and diversity of data. 

AI solutions often require significant changes to existing processes and workflows, and as such, employee training is essential to enable the effective utilization and quality control of AI solutions. Training helps employees embrace AI technology and leverage its capabilities to enhance their work. Organizations should involve employees in the process to simplify any transitions, communicate the benefits of AI solutions, and provide support. 

Ethical considerations are also important when implementing AI. Government regulations are beginning to be issued on a state-by-state basis. Organizations should develop ethical guidelines for AI use, ensuring compliance with regulations and conducting regular audits to identify and address ethical concerns. This ensures that AI solutions are deployed responsibly and ethically, protecting privacy and security and avoiding potential harm to individuals or society. 

Explore What’s Possible with AI

In today’s rapidly evolving business landscape, harnessing the power of artificial intelligence (AI) has become a critical factor in driving success and staying competitive. Embracing AI in the HR tech and employee benefits space can revolutionize business strategies, enhance operational efficiency, and deliver personalized experiences to employees.  

As new AI solutions are launched every day, soon the industry will face point-solution fatigue, resulting in confusion, overwhelm, and silos. At Archetype, we build growth strategies and provide developmental support to healthcare, wellness, and HR Solution industries. Our experience helps organizations fully utilize generative AI to enhance employee and client experiences, mitigate risks, and achieve operational efficiency. Get value from AI faster – contact us to learn more.