AI and technology

Digital technologies, including artificial intelligence (AI), are pervasive in the modern workplace. People professionals need to understand the range of technologies available and how to use them responsibly to enhance their practice. This factsheet provides an overview aligned to the technology and people core standard in the CIPD Profession Map.

It explains common technology and HR terms, explores how AI and other digital tools are shaping work and roles, outlines principles for selecting and using technology, and considers the role of people professionals in digital transformation.

Figure 1

Relationship diagram displaying the relationship between technology, automation, AI and generative AI

Generative AI (GenAI)

Generative AI is a type of AI that creates content from existing patterns of data such as text, video and audio. Prompt engineering is about writing clear instructions or prompts to get the best outputs from the generative AI tool.

Artificial intelligence (AI)

AI is the automation of cognition, that is automating the collection, processing and interpretation of information. AI is also a wide field of study which includes:

Machine learning - Teaching computers to learn from data.
Natural language processing - Teaching computers to interpret and generate human language.
Computer vision - Teaching computers to interpret images and videos.

AI algorithms, models and systems

An AI algorithm is a step-by-step guide for a computer to follow (like a recipe). An AI model is a representation of patterns in data, created using algorithms.

Some AI models use probabilities to handle uncertainty, which means their outputs can sometimes be wrong – as with anything designed and built by people.

A Large Language Model (LLM) predicts which words come next in sentences. It uses neural networks to recognise patterns in language from large amounts of data. A neural network is a way for a computer to learn patterns from data by changing its internal connections, inspired by how brains work.

Generative AI tools like ChatGPT, Claude and Copilot are built on large language models that can be adapted for many tasks. A model trained on large datasets that can be adapted for many tasks is also known as a foundation model or general-purpose AI system.

Automation and hyperautomation

Automation is about using technology to do tasks without (or with reduced) human assistance. AI, Robotic Process Automation (RPA) and even washing machines are examples of automation. RPA is used for repetitive tasks that people do on computers, like copying and pasting data between spreadsheets.

Intelligent automation (or hyperautomation) is about connecting technologies to execute business processes automatically on behalf of knowledge workers. For example, automatically updating a new joiner’s details on HR, payroll and IT systems when onboarding. Others say that hyperautomation takes it a step a further by automating a whole business process as much as possible. In onboarding, this could include automating the update of details on several systems through to the sending of relevant information to the line manager and new joiner.

Agentic AI is about setting a goal without prescribing the steps, so the AI works out how to achieve it and adapts as needed within the boundaries given. Agentic here means giving AI some agency or autonomy to act independently, while ensuring people review key decisions and approve important actions. Widespread use of generative AI tools has revived interest in agentic AI because you can tell the AI what you need in human language. Building on the onboarding example, if there’s no spare laptop, the AI onboarding agent might order an approved laptop model, inform the line manager and update the onboarding progress tracker.

Technology

Technology is the application of knowledge or processes to achieve practical goals that are reproducible. This includes automation and other tools which aren’t necessarily about reducing human involvement. Examples include communication technologies like the internet and videoconferencing tools.

Digital transformation

Digital transformation is the ongoing work of aligning technology, people, culture, structure and tasks so that an organisation can thrive. Kane et al describe this continual realignment as becoming more digitally mature as an organisation.

The range of HR technologies

An HR information system (HRIS) is the most common type of HR software used in organisations. Other terms used for an HRIS include:

core HR software,
employee information system (EIS),
human capital management (HCM) solution, and,
HR management system (HRMS).

A good HRIS helps an organisation to collect, store, update and retrieve employee data efficiently, and integrate with other software. An all-in-one HRIS that has all (or most of) the capabilities HR needs is the top consideration when choosing HR software. It avoids the added costs of buying more software as well as the complexity of integrating and maintaining several systems.

Many HR software vendors are expanding the range of HR modules on offer. Our articles on implementing an HRIS in small and medium-sized enterprises (SMEs) and large organisations captured learning points for people professionals.

Other HR software and platforms are commonly used for payroll, learning management systems, applicant tracking systems and employee surveys. Peer recognition and workforce planning software and platforms are less commonly used.

Our guide using technology responsibly, outlines how people professionals can use technology effectively in recruitment, performance management and other areas of people practice.

Besides specialist HR software, you should consider where existing business software and free tools can be used to enhance your people practices. For example:

Business intelligence software (eg Power BI, Tableau, Looker) can help with reporting and sharing key people insights with business leaders.
Collaboration platforms (eg Teams, Zoom, Slack) can be useful for engaging with hybrid teams.
Social networking platforms like Glassdoor and Google Reviews can provide insight into what people think of your organisation, while LinkedIn can be useful for sourcing and connecting with candidates.
Generative AI tools like ChatGPT, Claude and Copilot can be useful for many things including brainstorming ideas and drafting text. Meanwhile AI research tools like Consensus and Semantic Scholar can support with evidence-based HR by helping you discover relevant literature quickly.

How AI and other technologies are changing jobs

Technology is one of the five PESTLE drivers for change in the world of work.

AI and other technologies can change how people work in six ways. With each type of impact comes different considerations for your organisation. In the media, discussions normally focus on whether these technologies will replace people's jobs or augment people's capabilities. But technology can also create new jobs, intensify the pace of work, transfer tasks to other people, or enable work to be carried out remotely (telepresence) – see Figure 2. According to Professor Stuart Russell, technology can help improve productivity for a particular task and result in impacts such as job creation. But further improvements in productivity can eventually lead to those jobs being eliminated (substitution).

Each type of impact isn’t inherently good or bad. With work intensification, for example, being able to respond to multiple chats superfast might be thrilling for some people, but it’s problematic for those who can’t cope with the pace. In the latter case, this is about ensuring people have the necessary skills to use the chat function effectively and ensuring that work performance expectations are realistic.

See stage two of our five-stage framework for how to choose the right technology for your business for key questions you need to ask. Thinking this through early and revisiting the questions as necessary helps to flag potential benefits and risks for people, and helps you refocus efforts.

Figure 2

Diagram of ways that technology impacts jobs: listing 'substitution', 'transference', 'telepresence', 'creation', 'augmentation' and 'intensification'

Source: How to choose the right technology for your business, originally developed in partnership with Carnegie UK and the Institute for the Future of Work.

Guiding principles for choosing and using technology

AI is good at identifying patterns and processing large amounts of data quickly, it also enables you to gather, analyse and respond to biases resulting from people management processes efficiently. However, there is need for caution to ensure that AI is not the source of discrimination.

Your guiding principles for choosing to use such technology may include:

Being clear on what problem you’re trying to solve.
Ensuring the right people are involved in key aspects of design decision-making and delivery.
Considering how technology will impact jobs and the way things are done.
Consulting with employees to identify unforeseen risks and gain buy-in.
Understanding how technical functions work and what ongoing management is available before buying a technology solution.
Ensuring data security and other compliance practices consider people principles.

For more information about these guiding principles, as well as the benefits and risks of using technology in key areas of people practice, see our using technology responsibly guide.

While there's no standard approach to regulating AI, there's a global push towards creating AI governance frameworks and coordinating efforts across countries. Many countries support the OECD AI principles and UNESCO ethical AI policy. In the UK there’s a patchwork of legislation and case law that governs the use of AI and other technologies in the workplace. This includes health and safety, data protection and equality laws.

For companies with operations or employees in Europe, the EU AI Act, which came into force on 2 August 2024, is a more comprehensive and risk-based approach to regulating AI. Recruitment and employment activities are classed as high risk under the Act but may be downgraded to limited risk if it meets certain criteria - see the EU AI Act compliance checker questionnaire.

The people profession’s role in digital transformation

Although AI and other technologies are rapidly evolving, people professionals can still lean on familiar change initiatives to support people to adapt effectively. People professionals can get involved in AI governance, AI skills planning or more broadly workforce planning wherever a transformation could have a people impact. Digital transformation in organisations need not always be driven by IT or departments that invested in them.

While large digital transformations tend to be led by other departments (eg a programme management office), there are inspiring examples of HR professionals who’ve expanded their roles and added value in the process. To become a tech savvy people professional, you need to use technology and people data in ways that improve people’s working lives.

The CIPD Good Work Index 2025 found that using AI to complete repetitive tasks was generally welcomed by survey respondents, who felt it enhanced their performance. They also reported better job satisfaction and mental health. When looking for opportunities to leverage AI, focus on automating repetitive tasks, freeing up employees' time to do higher value or more enjoyable tasks.

Useful contacts and further reading