AI fundamentals: How to identify AI needs in HR

Published: 18 September 2024 | Tessa Hilson-Greener

In today’s digital HR landscape, creative use of AI can significantly boost efficiency and increase productivity. But when you’re trying to find the right AI solutions, it’s vital to focus on specific needs rather than targeting all areas at once. Here, Tessa Hilson-Greener sets out a step-by-step guide to help you define your AI needs.

Effectively managing AI cultural change is essential for success. Starting with one critical need allows for smoother implementation and provides valuable insights for broader AI strategies and investments. Prioritising key functions — such as automating résumé screening, sentiment analysis for employee engagement and personalised training recommendations — helps HR departments achieve manageable integration, better collaboration and measurable outcomes.

Step 1: Set up an AI committee

• Form an AI committee including key stakeholders from HR, IT, senior management and sponsors at the C-suite level.
• Ensure the committee has the authority, budget structure and resources to drive the AI initiative forward, including creating a digital AI culture with a change plan.
• Align the AI project with organisational goals to secure support from senior management, executives and other departments.
• Engage all relevant stakeholders to gather diverse perspectives and foster a sense of ownership.

Internal analysis

• Stakeholder interviews: Engage with HR leaders, managers, team members, SMEs and other stakeholders to gather insights on current challenges and potential areas for improvement.
• Data collection: Collect relevant data on current HR performance metrics (e.g., time to hire, employee satisfaction scores).

External research

• Industry reports: Read industry reports, white papers and online articles from reputable sources (e.g., Gartner, McKinsey, Deloitte, LinkedIn) to understand AI trends, best practices and case studies (use cases) in HR.
• Academic research: Review academic journals and publications for research on AI applications in HR (e.g., MIT, Consensus, Perlego).
• AI providers: Research AI providers (e.g., Amazon AWS Gen AI, Microsoft Co-Pilot AI).

Step 2: Conduct an HR operational review (process and functional)

• Conduct a comprehensive review of current HR processes to understand their flow and list pain points. This will be helpful to identify AI needs.
• Use tools like Process Plan Gap Analysis (PPGA) to systematically name inefficiencies, duplications and time-consuming areas.
• Identify specific HR functions that could receive help from AI, such as recruitment, training, talent management and employee engagement.
• Clearly define the problems you aim to solve or the opportunities you want to seize with AI integration called a “functional requirement”.
• Identify one need that you can address with AI and start with that one — you can then scale up with other AI tools once this project is successful. You can always try a bigger solution, e.g., AWS or Co-Pilot, once you have a valuable experience of AI and an idea of how it fits with your organisation’s technical environment.

Here are examples of how HR processes can be mapped to AI functional requirements, providing a starting point for organising your specific needs.

How to review current HR processes

Start by analysing your current HR processes to pinpoint inefficiencies, particularly in repetitive tasks. Here are two process area examples (one for recruitment and one for the engagement process), mapping both with functional areas for AI.

Step 3: Bridge the two workflows (HR processes and AI functional applications)

To effectively decide where AI could benefit, integrate the insights from both workflows by reviewing current processes and defining specific problems AI can resolve:

• Map out inefficiencies: Use the documented inefficiencies from the first review to create a detailed map of problem areas within your HR processes.
• Align problems with AI capabilities: Match the identified problems and inefficiencies with AI capabilities. For instance, if résumé screening is a bottleneck, consider AI solutions for automating this process.
• Prioritise areas for AI implementation: Rank the identified opportunities based on factors such as ease of implementation, expected return on investment and alignment with strategic goals.

Step 4: Research AI vendors

Market research

• Vendor websites: Visit websites of AI vendors to explore their HR solutions. Pay attention to features, case studies, HR expertise and customer testimonials.
• Software reviews: Use software review platforms (e.g.,  G2, Capterra) to compare different AI solutions based on user reviews and ratings.
• Industry events and webinars: Attend HR and AI industry conferences, webinars and workshops to learn about the latest solutions and network with experts.
• AI industry experts: Gain advice from impartial AI independents (e.g., my own AI-Capability).

Research AI technologies and vendors

• Research available AI technologies and vendors to find solutions that meet your defined requirements.
• Evaluate each solution based on scalability, ease of use, support services and cost.

Specify functional requirements

• Decide the specific functional requirements for AI in your HR processes, such as résumé screening, performance analytics or predictive modelling for employee turnover.
• Focus on tasks that will have the most significant impact on efficiency and effectiveness.

Include technical requirements

• Consider technical aspects such as integration with existing HR systems, data security and compliance with data protection Regulations.
• Prioritise requirements based on their feasibility and potential impact on your HR operations.

Prioritise requirements

• Rank the identified requirements to focus on the most critical needs first.
• Use criteria such as ease of implementation, expected return on investment (ROI) and alignment with strategic goals.

Conduct a cost-benefit analysis

Financial analysis

• Initial costs: Calculate the initial investment needed for AI implementation, including software licences, hardware and integration costs.
• Operational costs: Estimate ongoing costs such as maintenance, training and support.
• ROI calculation: Project the return on investment by estimating the potential savings and productivity gains from AI implementation.

Feasibility study

• Technical feasibility: Assess whether the AI solutions can be integrated with your existing HR systems and infrastructure.
• Scalability: Consider whether the AI solution can scale to meet future needs and expansion.

Step 5: Conduct an AI pilot 

Select a test group

• Choose a small, representative group to pilot the AI solution.
• Ensure the group includes diverse users to gather comprehensive feedback.

Track and report progress

• Monitor the performance of the AI solution during the pilot phase.

Key metrics and considerations during the pilot phase

By focusing on these areas, you can ensure a comprehensive evaluation of the AI solution’s performance during the pilot phase, identify improvement areas and make informed decisions about full-scale implementation. Collect and analyse feedback to find any issues or areas for improvement.

Step 6: AI implementation

Develop an implementation timeline

• Create a detailed timeline outlining each phase of the AI implementation process.
• Allocate necessary resources, including budget and personnel, to ensure smooth execution.

Train users and stakeholders

• Provide comprehensive training to all users and key stakeholders.
• Implement a change management plan to address any resistance and ensure user buy-in.
• Define a communication approach and implement it.
• Implement the digital cultural change plan.

Step 7: Compliance

Regularly review AI performance

• Continuously watch the performance of the AI system to ensure it meets your needs.
• Gather feedback from users and make necessary adjustments to policies and procedures.

Seek opportunities for enhancements

• Stay updated with regulatory changes and ensure ongoing compliance.
• Look for opportunities to further enhance the AI system and improve HR operations.
• Ensure all GDPR areas are covered and add ethical standards to the reporting policies.
• Ensure that the AI system is meeting all the defined HR functional application requirements on time, without bias, free of legal issues and without any restrictions.

Implement AI SLAs and strengthen partnerships

• Set up Service Level Agreements (SLAs) with AI vendors to ensure reliable support, quality of service and technical performance.
• Build strong partnerships with vendors to ease continuous improvement and innovation.

Conclusion

By following these steps, HR professionals can effectively identify their AI needs and implement solutions that drive efficiency, accuracy and strategic value in their HR processes. Conducting thorough research and starting with one critical need allows for a focused and manageable introduction of AI technology, setting the stage for scalable future projects.

This structured approach ensures that AI solutions are targeted and effective in enhancing HR processes, ultimately supporting organisational goals and growth, keeping pace with the digital cultural change taking place throughout organisations worldwide.