In this review, we’ll explore the practical benefits of combining AI and HRTech solutions, why this integration is necessary, and the advantages it offers. We’ll also address the challenges of developing quality solutions and how to overcome them.
What is AI and HRTech? Benefits of Using AI in HRTech
AI is now widely used in custom software development across various sectors, including healthcare, finance, education, HR management, etc. HRTech involves software and systems designed to optimise HR frameworks, combining technology and HR to improve company efficiency. HRTech encompasses tools like human resource management ecosystems, talent acquisition systems, L&D platforms, performance appraisal systems, and so on.
Importance of Quality HRTech Development and AI Integration
Challenges in HRTech and Talent Acquisition in 2024
- Global Talent Shortage: By 2030, there could be a shortage of over 85 million skilled workers, risking $8.5 trillion in annual revenue losses (source: Korn Ferry).
- Talent Search Issues: 75% of employers struggle to find the necessary talent (source: ManpowerGroup).
- Technology Integration: 58% of companies have difficulties finding compatible technologies (source: Techinformed).
- Time Spent Sourcing: Recruiters spend about 13 hours per week per vacancy (source: Novoresume).
- AI Adoption Hesitation: 60% of recruiters are hesitant to use AI in hiring due to implementation challenges (source: SIA).
- HRTech Implementation: 82% of users face difficulties with new technologies (source: Hiringthing).
- Candidate Dissatisfaction: 72% of workers believe employers rely too heavily on AI for hiring, complicating the process and increasing offer rejections (source: SIA).
Candidate dissatisfaction often results from poor-quality solutions or inadequate training. This doesn’t mean AI shouldn’t be used; it underscores the need for quality solutions and proper training.
A telling example of AI penetration in HRTech is shown in the diagram by Josh Bersin.
Four Key High-Level Benefits of Using AI in HRTech
All the mentioned challenges, advantages, and AI use cases should be considered during the product discovery phase, before initiation of the software development process. Implementing AI in HRTech can bring a variety of gains:
- Automation of Routine Processes: AI can automate up to 70% of typical tasks, such as CV analysis and initial candidate screening. This allows hiring teams to concentrate on more critical aspects of the hiring process, like candidate engagement and decision-making.
- Refined Precision: AI enhances accuracy in tasks like performance prediction, talent identification, and risk assessment. By analysing big data, AI can find perfect candidates more reliably than traditional methods.
- Increased Productivity: AI streamlines operations, enhances interaction, and enhances user experience. With AI use cases handling repetitive tasks, HR staff can dedicate extra time for strategic initiatives and candidate interaction.
- Cost Savings: AI facilitates expense reduction by automating processes, minimising errors, and improving resource efficiency. By arranging operations, AI enables companies to save on recruitment costs while maintaining high standards.
Integrating AI in HR Technology Solutions: From Recruitment to Career Development
Seven Detailed Niched Advantages of AI Integrations in HRTech
1/ Automating Regular Tasks and Recruitment Process Automation
- CV Initial Screening and Documents Processing: recognizing various types of documents using various types of deep learning models like computer vision and multimodal neural networks combined with Optical Character Recognition (OCR).
- AI Personal Assistants: AI assistants based on large language models (LLMs) allow HR staff to focus on strategic initiatives.
2/ Optimising Recruitment Frameworks and Processes
- Data Analytics:
- Examining extensive candidate datasets
- Mitigating biases
- expanding “the search horizons” (accessing candidates from diverse channels).
- Personalisation: AI can personalise the recruitment workflow for individual candidates, enhancing enjoyment and processes efficiency.
- Video Interviews Processing: AI-driven video interview sessions can autonomously assess candidates’ communication abilities and body language through computer vision and multimodal neural networks. Finally, it can make a quick and structured summary using speech-to-text and other deep learning models.
3/ Customised Education and Growth L&D Programs
- Adaptive Learning Systems and Programs: AI can monitor staff progress and provide tailored L&D recommendations.
- Career Growth Recommendations: AI-powered talent development platforms can assist in pinpointing and fostering upcoming leaders, lessening the reliance on costly external recruitment and training initiatives.
4/ Predictive Analytics
- Turnover Forecasts: AI can forecast staff turnover risks, helping to retain valuable professionals.
- Staffing Optimisation: pretrained HR deep learning models can enhance strategic workforce management and anticipate forthcoming staffing needs.
5/ Productivity Assessment and Decisional Optimisation
- Data Analysis for Strategic Planning: Strategic Planning through Data Analysis: AI offers unbiased performance assessments and tailored feedback, boosting employee efficiency.
- Internal Mobility: AI recognizes possibilities for internal promotions and mobility, offering detailed data and reporting.
6/ Cultivating Greater Workforce Dedication
- Chatbots for FAQ and Feedback: LLM-based chatbots can quickly address staff inquiries and offer clear and constructive feedback.
- Sentiment Monitoring: AI can analyse employee sentiment to find and solve issues, using deep learning models, e.g. NLP / LLM.
7/ Compensation and Benefits Management
- Salary and Benefits Analytics and Insights: AI can process all the data in your compensation system to suggest competitive reward packages.
- Payroll Management Tuning: AI can handle repetitive payroll processes and personalise reward programs.
Challenges in AI and HRTech Integration
Data Privacy and Security
Integrating AI into HR systems involves handling sensitive personal data of candidates and staff. Enforce fortified security protocols, integrating sophisticated encryption, multifactor authentication, regular security / vulnerability checks and end-to-end audits, secure infrastructure deployment, cloud migration, DevOps as a Service and DevSecOps principles.
Validate alignment with data security regulations like GDPR and CCPA, while cultivating transparency about data usage.
Seamless Compatibility and Integration with Current Architectures and Systems
- System Compatibility: Platform Interoperability: Fusing AI capabilities into established HR infrastructures can be intricate due to differing data formats, communication protocols, and architectures, leading to compatibility issues and increased error risks.
- API Development: In custom software development, developing proper Application Programming Interfaces (APIs) is important for enabling seamless data transfer between your AI products and established ecosystems, thereby preventing data loss and errors.
- Quality Standards: To ensure seamless and transparent integration, AI-driven HR systems must meet high-quality standards in compatibility, data standardisation and management, and require cooperation from solution providers.
Additional Challenges
- Continuous Updates: Regularly update HR solutions, tools and deep learning models to keep them relevant.
- Resource Intensity: Manage the computational demands of large data processing, leveraging cloud technologies with security considerations.
- Transparency and avoidance of “Black Box”: Ensure decisional frameworks rely on clear and free from bias AI models.
- Algorithm Bias: Frequently assess and enhance algorithmic processes and models to avoid discrimination and distortions.
- Data Quality and Relevance: Mitigate limitations in data availability and representativeness.
- Ethical Considerations: Discuss ethical concerns like surveillance and job displacement, developing ethical AI use frameworks.
- Staff Qualifications: Employ skilled personnel in AI, machine learning, and data analytics, invest in the internal educational programs for stuff.
- Regulatory Compliance: Ensure AI solutions comply with relevant laws and standards, understanding the impact of regulatory decisions on AI adoption.
Practical AI Use Cases in HRTech: Sourcing and Initial Candidate Assessment
Sourcing and Selecting Relevant Candidates
Below is a list of the main functions and key operations that, when boosted by AI, will bring significantly more value.
- Algorithmic Talent Sourcing: AI-powered systems scour social media, professional platforms, CVs, cover letters, and databases to identify potential candidates.
- Intelligent CV Evaluation: AI can automatically assess resumes to pinpoint pertinent skills and experience.
- Initial Screening: AI conducts initial applicant evaluations leveraging CVs and supplementary information to surface the most suitable candidates for the role.
- Chatbots and Virtual Candidates’ Assistants: these solutions communicate with applicants, provide key information and FAQ, conduct quick basic preliminary interviews.
- Recommendation Models: Algorithmic models propose job openings to individuals based on an assessment of their abilities and inclinations.
- Predictive Analytics:
- Open Talent Intelligence: AI analyses socials to highlight candidates’ professional skills, achievements and some personal qualities.
- Projecting Candidate Outcomes: AI-powered models analyse information to foresee which applicants will thrive..
- Behavioural Insights: AI processes and forecasts candidate behaviour,, including the likelihood of when they may be considering a career transition.
Wandify: Enhancing Recruitment Efficiency
To best illustrate the maximisation of the utility of algorithmic talent prospecting and assessment tools, it is worth reviewing how the Wandify platform operates. The Allmatics team was directly involved in its development, setup, and subsequent evolution and enhancement.
Wandify is a sourcing platform designed to improve the efficiency of recruiters, sourcing specialists, and HR managers.
Here are some key Wandify’s features:
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- Candidate Search and Sourcing: Access a vast, updated resume database with direct contact information. It uses an optimised search engine with synonym and variant search functions.
- Expanding Search Horizons:
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- Advanced global contact search;
- Company discovery search feature.
- Smart Data Organization and Candidate Management: Tools for managing candidates, including folders, lists, filters, tags, and comments.
- Team Collaboration: Supports team collaboration with comments and tags for shared candidate information.
- Integration: API for integration with HR systems (ATS, CRM).
- Flexibility: Simplified resume import and CSV export, along with a Chrome extension for direct contact data extraction from online profiles.
Optimising Candidate Data Handling: Wandify Docs and API
- Wandify Docs: Converts resumes from PDF to .docx, saving HR professionals up to 20 minutes per CV. The process involves uploading a PDF resume, which the AI then processes, resulting in a .docx file ready for use.
- Wandify API: Automatically updates candidate data in databases (ATS, CRM, ERP). It checks and updates candidate information, enriching data with current contact details. This solution requires no software changes or programming skills, ensures data confidentiality, and provides updates with only the most current data.
Conclusion
Integrating AI with HR technology can transform talent recruitment and workforce management, boosting productivity and performance. Yet, prudent AI implementation is vital to prevent over-dependence and maintain a balanced strategy with a human touch.
For businesses aiming to refine their HR processes, integrating AI with HRTech is a strategic step towards achieving superior results. If you want to ensure your software development projects leverage the best and most effective approaches, consider partnering with experts who can deliver optimal results. All the key points, pros, cons, and best practices of AI implementation in HRTech will be discussed and evaluated during the product discovery stage.
Enhance your HR processes with cutting-edge AI and HRTech solutions. Partner with us to achieve superior performance and results. Contact us today to learn how we can help.