Technology in HR: From Payroll Mainframes to Hiring Bots

The short answer

HR technology began by automating calculation (payroll), then moved to storing and sharing records, then to letting employees and managers do things themselves, and now to analyzing data and automating judgment-like tasks. Each step reduced some work and created new questions about accuracy, privacy and fairness.

The practical lesson is the same in every era. Tools help when they solve a clear problem and a person stays accountable for the decisions that affect people’s jobs and pay.

Eras of HR technology

A 2016 paper in the Communications of the Association for Information Systems, The Evolution of the Field of Human Resource Information Systems by Richard Johnson, Kimberly Lukaszewski and Dianna Stone, traces how HR technology and HR practice developed together. It groups the history into four technology eras: mainframe, client-server, ERP and Web-based systems, and cloud-based systems. We have read only its abstract, which says that HR needs drove adoption of each system type and that each system type in turn changed what HR could do. The approximate dates below are our general summary and the boundaries overlap.

The last row is our addition and is not part of the paper’s four-era scheme. Whether AI-assisted tools count as a separate era or a new layer on cloud platforms is a matter of opinion.

What changed in the work

• From clerical to analytical. Early systems removed hand calculation. Later systems freed time for analysis, planning and advising managers.
• From HR doing it to employees doing it. Self-service portals moved address changes, leave requests and benefit choices to employees.
• From local to global. Shared databases let large employers see their workforce across sites and countries.
• From records to data. Turnover, pay and engagement could be tracked over time and compared across groups.
• From tool owner to tool buyer. Cloud services shifted work from running servers to choosing vendors and managing contracts. Our guide to contract lifecycle management shows why that matters.

Where AI and automation fit today

Adoption levels vary widely by organization size and country. Some industry surveys report rapid growth in the use of AI in HR, but we could not verify current figures from a source we could read in full, so we do not quote any here.

Rules and risks

• Bias. A tool trained on past decisions can repeat past patterns.
• Privacy. HR holds sensitive data. Every new system is another place it can leak or be misused.
• Transparency. People may not know when software shapes a decision about them.
• Accountability. If a vendor’s tool makes a poor decision, the employer is usually still responsible.
• Regulation. Some places regulate automated hiring tools. New York City’s Local Law 144 is one example. According to the city’s Department of Consumer and Worker Protection page, employers and employment agencies may not use an automated employment decision tool unless it has had a bias audit within a year before use, information about the audit must be publicly available, and candidates and employees must receive certain notices. The page says enforcement began on July 5, 2023. Rules differ elsewhere and change, so check the law where you hire.

For the hiring side, see our guide to transparency in talent acquisition, and for the wider picture, human resource management challenges.

A made-up time-saving estimate

All numbers are invented. A company has 500 employees. Each makes about 4 routine HR requests a year (address changes, leave, benefit questions), so 500 × 4 = 2,000 requests. Handled by HR staff, each takes about 15 minutes, so 2,000 × 15 ÷ 60 = 500 hours.

After a self-service portal and a chatbot, suppose 60% of requests no longer need HR staff time. That frees 500 × 0.6 = 300 hours. At an assumed $40 an hour, the value is 300 × $40 = $12,000 a year.

Treat that as a soft saving: it is time freed, not cash removed from the budget, unless staffing changes. Compare it with the real costs of licenses, setup, training and upkeep. For a small company, the tool may cost more than $12,000 a year, in which case the case for it must rest on something else, such as accuracy or employee experience.

A made-up fairness check

Automated screening tools are often checked by comparing how many people from different groups they advance. Suppose a tool screens 500 applicants in group A and 700 in group B. It advances 150 from A and 140 from B.

The ratio of the lower rate to the higher rate is 20% ÷ 30% = 0.67. A commonly used rule of thumb, sometimes called the four-fifths rule, treats a ratio below 0.80 as a signal to investigate. It is not proof of discrimination, and a ratio above 0.80 does not prove fairness. Small numbers can also swing the result by chance. But it shows why audits compare rates between groups, and why an employer should ask a vendor how a tool is tested. Legal standards vary by place, so take advice for real decisions.

How to adopt tools well

1. Start with the problem. Write down what is slow, wrong or unfair now, and how you will measure it.
2. Check the rules. Privacy law, employment law and any rules on automated decisions.
3. Ask vendors hard questions. How is the tool tested for bias, what data does it use, what are the exit terms?
4. Pilot first. Try it with one group and compare results. Our guide to the agile HR mindset describes this approach.
5. Keep a human accountable. A named person owns every decision that affects pay, hiring or dismissal.
6. Tell people. Say when automated tools are used and how to ask for a human review.
7. Review regularly. Re-test results, costs and complaints at least yearly.

Careers in HR technology

HR systems have created specialist jobs: HRIS analysts who configure and maintain the system, people analytics specialists, talent acquisition technologists, and HR operations managers. Useful skills include process mapping, spreadsheets and databases, data privacy awareness and clear communication with both HR and IT. For the wider skill set, see our guide to essential skills for human resources, and for a structured route, the certificate in HR management.

Common mistakes

• Buying before defining the problem. Features are not outcomes.
• Automating a bad process. Fix the steps first, then automate.
• Trusting vendor claims. Ask for evidence and references.
• Counting soft savings as cash. See section 6.
• Forgetting the people. Training and change support decide whether a system is used well.
• Letting the tool decide. Software supports decisions; people are accountable for them.
• Ignoring data hygiene. A new system with old, messy data gives messy answers.

Learn more

If you want structured study of HR practice, online providers such as Coursera and Udemy list HR management courses. We may earn a commission if you sign up, at no cost to you. We are not affiliated with any university. Check the syllabus for coverage of HR systems and analytics. You can also browse our human resources guides.

Frequently asked questions

How has technology changed HR?

It moved HR from manual calculation and paper records to shared databases, self-service portals, cloud platforms, analytics and now AI-assisted tools, shifting HR staff toward analysis and advising.

What is an HRIS?

A human resources information system: software that stores employee records and supports tasks such as payroll, benefits, time off and reporting.

What are the eras of HR technology?

One academic review groups them as mainframe, client-server, ERP and Web-based, and cloud-based systems. Many writers add a recent layer of AI-assisted tools.

How is AI used in HR?

For sorting applications, scheduling, answering employee questions, recommending training and spotting patterns in data. Use varies widely by organization.

Is it legal to use AI to screen job candidates?

It depends on the place. Some jurisdictions require bias audits and notices, and general anti-discrimination law applies everywhere. Check local rules and get legal advice.

What is a bias audit?

A check of whether an automated tool advances people from different groups at noticeably different rates. New York City’s law requires one within a year before a covered tool is used.

Will technology replace HR professionals?

It automates routine tasks, but decisions about people, sensitive cases and trust still need people. The mix of skills in HR is shifting toward data and technology literacy.