HR Best Practices for the Age of AI

Next-generation technology is changing the rules of Human Resources. Here are the essential HR best practices for a new era. 

16 June 2025 | By Alex Schulte

AI is moulding Human Resources (HR) into a more strategic role.

HR functions, once unfairly perceived as extending to paperwork, dispute management and policy development, are now the bedrock of talent management and attrition mitigation. These are among the most essential components for business survival in an increasingly competitive and alienating world. 

The so-called era of AI runs in tandem with ‘quiet quitting’. Professions like AI researchers and engineers are in short supply, and the war for talent is fierce. Employees want more than just money; they want flexibility and the ability to work with the latest technology. 

The toll of mental illnesses, currently at epidemic proportions, requires HR to entice candidates with meaningful work and emotional support. Combined with increasingly tight budgets, HR professionals must get creative. All of which requires the swift scaling that AI allows. 

This is why high-quality HR roles are growing fast. HR management roles are expected to grow 6% by 2032, according to the US Bureau of National Labor Statistics (BNLS), far above the national average. 

To stay ahead of the curve, HR professionals must outsource the more traditional tasks associated with their profession – writing contracts, managing benefits, creating employee handbooks, collecting timecards – to machine learning algorithims, artificial intelligence (AI), and automation – so the HR department can focus on value-adding tasks that actually give a business a competitive advantage. 

This guide to HR best practices in the age of AI will show you how to implement a new kind of HR: AI-driven, strategic deployment of human capital.

But first:

Why Automate HR Processes?

AI in HR saves time, enables smarter decisions, cuts costs, and gives HR a seat at the strategic table. 

The results speak for themselves. HR leaders are already seeing:

• 63% productivity boost from AI tools
• 55% automation of manual tasks
• 52% improvement in overall efficiency
• 93% of HR leaders say AI helps cut costs

And these savings are massive. By 2025, AI-driven workforce transformation is expected to save $1.2 trillion globally.

• AI copilots for HR queries → 95% faster employee search times
• Career assistants powered by AI → 25% boost in career satisfaction
• Project/role matching tools → 30% better skill alignment + 25% less bias
• Performance-based skills inference → 25% rise in employee performance.

To put it simply, AI is a weapon – so use it. 

AI Revolutionises HR Strategy

By using AI, HR can perform high-value strategic decision-making. Not simply managing human capital, Human Resources becomes the linchpin of a broader business strategy. It can forecast talent needs, flag flight risks, and pivot hiring strategies in real-time. These new tools enable it to do more than before. 

For example, instead of scrambling to fill roles or fix engagement problems, HR can now:

• Spot issues before they arise
• Deploy resources more strategically
• Align talent with business goals
• Make faster, fairer decisions.

But how does it work in practice? 

Let’s look at:

How HR Teams Actually Use AI

There are five key ways that AI drastically changes HR: 

• Recruitment and talent acquisition
• Employee engagement and retention
• Learning and development
• Performance management
• Compliance. 

Let’s start with:

Recruitment & Talent Management

AI has made the hiring process faster, fairer, and smarter. 

Thank heavens for that. Traditional recruitment is:

• Expensive: Some businesses spend up to $5,000 per new employee.
• Time-consuming: Lengthy recruitment processes lead to one quarter of employers being ‘ghosted’ by prospective candidates. 

AI-driven recruitment changes all of that. It’s the difference between a rocket ship and a horse-drawn cart.

For example: 

• Applicant Tracking Systems (ATS) utilise natural language processing and predictive algorithms to screen CVs and match candidates to roles automatically.
• Chatbots can handle FAQs, schedule interviews, and keep candidates in the loop.
• Predictive analytics forecasts which candidates are likely to thrive based on past hiring data.

The results of AI-driven recruitment: 

• 90% drop in review time of video interviews and game-based assessments (according to Unilever)
• 16% increase in diversity
• 68% of businesses report cutting costs and time-to-hire (according to LinkedIn’s Global Talent Survey). 

AI recruitment is here to stay. Some even estimate that 70% of companies will use AI for end-to-end hiring. So buy your ticket to the New World or you will be left behind. 

Employee Engagement & Retention

AI makes workforce planning a little easier. It helps HR professionals understand how employees are feeling –  I should add, before they hand in their notice. In short, it goes a long way to nurturing a team of engaged employees.

• Sentiment analysis tools scan internal comms and surveys to flag early signs of disengagement. This software can then personalise career development based on each employee’s skills, interests, and performance.
• Internal mobility tools powered by AI highlight who’s ready for a new challenge.
• Generative AI can even craft tailored recognition messages or update the staff handbook.

The results of AI-driven talent management: 

• Retention rates could rise 25% by 2025 thanks to AI-driven engagement tools
• Burnout may drop 30% with AI-led wellness programmes.

In short, AI gives HR time back to focus on strategy, growth, and meaningful employee experiences.

Learning & Development

AI and automation help businesses offer tailor-made learning and development opportunities. This is critical, given that employee development opportunities and learning new skills (particularly in AI) are major demands from the modern workforce.

• Smart platforms spot skill gaps, personalise learning paths, and deliver real-time feedback.
• Reinforcement learning matches trainees with the right coaches.
• Generative AI can build immersive learning. Think role-play simulations for leadership training. 
• Real-time coaching (take platforms like Gong.io) offers feedback on how employees perform in the flow of work.

Employees know they need AI skills to survive. 

Take the financial professionals most recently surveyed, 90% of whom said learning tech skills is the only way to stop their pay from decreasing. 

The glory of AI? It can teach people how to use it and personalise each lesson based on their progress. 

Employee Performance Management & Workforce Analytics

HR professionals can use AI and machine learning to monitor employee satisfaction and performance. This helps them proactively prevent attrition before it happens, rather than firefighting reactively. 

For example:

• Performance: AI aggregates key performance indicators from systems like Jira, GitHub, or Salesforce (as Lattice does), providing managers with real-time insights. This helps spot issues early and offer targeted support.
• Satisfaction: AI predicts satisfaction levels by analysing pay, workload, leave, and survey responses. It identifies disengaged teams and high-flight-risk employees. It can even optimise staffing based on availability and demand.
• Risk: Unsupervised learning helps group employees by risk or behaviour, allowing tailored interventions. 

The results of an AI-driven performance management process

• 70% of companies use at least one AI for real-time performance tracking. 
• Predictive HR analytics now forecast workforce trends with up to 90% accuracy.
• Some companies, like JP Morgan, use machine learning to root out bad apples in the workforce. 

HR Automation & Compliance

AI is ideal for repetitive tasks, such as onboarding checklists, payroll calculations, and benefits admin. 

• Travel compliance assistants can evaluate travel risk level with real-time monitoring of overseas compliance obligations
• Monitor changing labour laws and update internal policies to stay compliant. 
• Document automation tools scan, categorise, and summarise HR files instantly.

That means less admin, fewer mistakes, and more time for HR to focus on strategy and the employee experience.

Risks You Can’t Ignore (and How to Handle Them)

No AI application is perfect, and they all come with baggage that HR teams must remain vigilant about. The most noteworthy risks are: 

• Bias
• Privacy breaches
• Alienation

However, there are ways out. Let’s look at each risk factor in turn – and the best HR practices for managing them.  

First thing to tackle is:

Bias

AI is not omniscient. It is only as good as the data it learns from, and that data can be full of bias. 

If you don’t have a diverse workforce already (and if, like JP Morgan, you rely on a referral system) you may entrench pre-existing biases at scale. 

Bias is also present in AI development, with programmers inputting their own biases. 

To protect the integrity of your outputs, you need to go straight to the source and consider any prejudices inherent in the training data.  

✅ HR best practices:

• Train AI on diverse, inclusive datasets
• Use fairness-aware algorithms and debiasing techniques
• Run regular audits with human oversight
• Make AI decision-making transparent
• Involve the HR and ethics teams in development.

Stale data

As mentioned, AI is only as good as the data it’s fed on. If the data is stale, the processes its built on will suffer. Recruitment is a case in point. 

AI scans CVs and online profiles for short, acontextual words that prove the candidate is qualified. But stale data – aka, out-of-date information – means it can automatically sift real talent onto the scrap heap.  

• 45% of Americans don’t update their profiles, according to ResumeLab
• AI recruitment software misses their CVs and impressive experience
• This leads to negative experiences among candidates, according to a study by the Future of Higher Education and Talent Strategy. 

✅ HR best practices:

• Experienced professionals must oversee AI implementation 
• Run regular audits to iterate 
• Be transparent: inform job applicants that you use AI, and that they must keep their information up to date 
• Rely more on fostering human connections via positive referrals. 

Chatbots Versus Chatbots

Recruiters are integrating AI more into the hiring process. Zal AI, for instance, uses chatbots to interview candidates, testing their knowledge on coding questions and applying real-life work scenarios. 

Some candidates use chatbots like Cluely to answer questions. This is why recruiters need a “human in the loop”, as Tim Whitley puts it. The alternative is just chatbots talking to chatbots. Recruiters learn nothing about applicants, and potential hires never find out about the human dimensions of their prospective workplaces. 

In short, the more integrated AI becomes, the more essential human oversight becomes. 

Privacy and Security

AI in HR handles incredibly sensitive data like salaries, medical histories, and performance reviews. 

That makes it a major target for cyberattacks, hence why 70% of CHROs say data privacy is a top concern (and why hiring in fields like compliance and cybersecurity is skyrocketing). 

Reputational risks aside, lax security measures have financial repercussions. Under GDPR, a breach could cost you up to €20 million or 4% of your global turnover, and pose future challenges for compliance.

Thus, AI in HR demands a trade-off between privacy concerns and effectiveness. For instance, you must give AI access to Zoom meetings, Slack channels, and email accounts for it to be truly effective. 

This has undeniable security implications. 

✅ HR best practices:

• Follow GDPR/CCPA rules to the letter
• Encrypt all sensitive data
• Limit who can access what (and log it)
• Use AI tools for redacting personal data
• Design privacy into your systems from day one
• Be transparent with employees about how data is used.

Losing the Human Touch

Automated HR can feel cold. If employees only interact with dashboards and bots, they may start to feel like binary numbers, not complex individuals that “contain multitudes” (to quote Whitman). Far from helping to boost employee engagement, it dents employee morale and increases employee turnover.

• AI can spot performance dips (but can’t always understand context or emotion). 
• Over-monitoring, like tracking keystrokes or screen time, worsens the disconnect.

✅ HR best practices:

• Use AI to support humans, not replace them
• Keep performance conversations human-led, AI-informed
• Don’t automate empathy; host real check-ins and feedback sessions
• Be open about AI tracking, and let employees opt out
• Focus AI on employee wellbeing and development, not micromanagement.

Resistance to Change

AI adoption is a people issue. 

Fifty-one percent of employees in marketing and advertising worry AI will take their jobs. Naturally, they’re reluctant to sharpen the knives that might cull them. 

They’re not always receptive to the key message – that it’s only through learning how to use AI that they can thrive in an AI-driven economy. That requires some teaching.

✅ HR best practices:

• Be transparent: explain what AI will and won’t change
• Address job-loss fears directly. Emphasise upskilling, not replacement
• Start with small pilot projects that show real value
• Provide tailored training that mixes tech and soft skills
• Build culture around AI readiness: awareness, desire, ability, reinforcement.

The Future of AI-driven HR

Even more change is coming at rates we simply can’t predict. Your HR strategy must prepare your current and future workforce.

Between 2026 and 2029, we’ll see a shift from basic automation to intelligent systems that collaborate, reason, and even empathise. 

This means AI and mood monitoring. It means digital personas. A hybrid workforce where people and machines work side by side.

Let’s start with:

Agentic AI

These are autonomous agents that manage tasks end-to-end, and they’re already showing up in enterprise tools. These AI “co-workers” will: 

• Schedule meetings
• Prioritise tasks
• Prompt wellbeing breaks
• Keep workflows humming behind the scenes. 

HR teams will have more time for strategy and leadership, while AI handles the day-to-day. 

Smarter LLMs and Multi-Modal AI

Large Language Models are:

• Approaching the reasoning skills of advanced-degree holders. 
• Tackling complex analysis, multi-step problem solving, and nuanced interpretation.

Add in multi-modal AI, which reads text, video, and audio with emotional sensitivity, and things start to feel human.

Expect interactions with HR systems to feel more like conversations than just filling out forms.

Flatter Org Structures

AI is trimming corporate fat, flattening organisational structures. 

• Gartner predicts that by 2026, 20% of companies will use AI to cut over half of middle management roles. 
• Routine tasks such as scheduling, reporting, and performance tracking will be fully automated, freeing managers to focus on innovation, strategy, and team growth.

HR will need to redefine what leadership looks like, help teams adjust to leaner structures, and prepare employees for more creative and collaborative roles. 

Digital Personas

By 2027, 70% of new employee contracts will include licensing terms for the use of AI-generated digital personas. 

These virtual replicas could appear in training videos, customer support, or internal knowledge bases.

It’s a bold new frontier for HR, but one that raises tough ethical questions about identity and ownership. These are questions that HR leaders will need to step up to answer. 

Start by building clear policies around digital representation, usage rights, and fair treatment.

Mood Monitoring

By 2028, 40% of large companies are expected to use AI tools to track and influence employee mood and behaviour. These systems will scan internal comms to assess morale, engagement, and overall cultural trends.

The potential for real-time insights is huge, but so are the risks. HR will need to lead on transparency, ethics, and data governance: explaining what’s being monitored, why, and how employee privacy is protected.

AI Unleashes Strategic Human Resource Management

As automation takes over admin-heavy tasks such as payroll, leave tracking, and onboarding paperwork, HR leaders are stepping into more strategic, consultative, and data-driven roles. 

Now, HR needs more than just soft skills. The AI-powered HR leader needs to think like a strategist, act like a consultant, and operate like an analyst.

Centuro Global’s AI-driven Travel Compliance Assistant empowers HR professionals to send employees overseas without stumbling into legal and compliance issues. This first-of-its-kind technology gives Global Mobility managers and HR leads the confidence to make data-driven decisions and focus on the complex, sensitive people management that machines cannot handle. 

Book a demo now to see it in action.