Enterprise AI
HR tech
Also known as: HR technology, human resources technology, people tech
HR tech is the category of software used to hire, pay, manage and develop people, covering areas such as applicant tracking, payroll, performance management and learning. Buyers are usually HR, talent or operations leaders, often supported by IT and finance. The market is crowded, so comparison and review content plays a large part in how buyers shortlist.
What it is
HR technology spans core systems of record, such as HRIS and payroll, and point solutions for recruitment, engagement surveys, scheduling, benefits and learning. Many vendors now add AI features for CV screening, interview scheduling, skills matching and policy question answering. Integration with existing payroll and identity systems is usually the deciding factor in a purchase.
Why it matters
HR tech buying journeys start with problem-led questions and move through category research, shortlists and peer validation, which makes the category highly exposed to AI assistants that summarise options. If your product is absent from review sites, comparison pages and independent directories, assistants will describe the market without you. Compliance and data handling questions also appear early, so accurate public documentation influences whether you make a shortlist.
How it works
Practitioners map the buying committee and produce content for each role, including integration detail for IT, pricing structure for finance and workflow detail for HR. They keep listings on review platforms and directories current because these sources are frequently cited in AI answers, and they publish clear pages for each use case rather than one broad product page. Sales teams feed back the questions buyers actually ask so those questions can be answered publicly.
When it applies
It applies to vendors selling into HR and talent functions, and to consultants and agencies advising on selection, implementation and change management.
Examples
- An applicant tracking vendor publishes a page comparing itself against three named alternatives, including limitations it does not cover.
- A payroll provider documents supported integrations and data residency in a plain page rather than a gated PDF.
- A learning platform answers "how long does implementation take" with a realistic phased timeline by company size.
How it is measured
- Share of AI assistant answers for category questions that name the product
- Presence and rating currency on the review sites buyers cite
- Demo requests attributed to comparison and integration pages
- Pipeline influenced by questions raised during evaluation, tracked from sales notes
Insights on HR tech
Related terms in Enterprise AI
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- AI chipsAI chips are processors designed or optimised to run machine learning workloads, especially the large matrix operations behind training and inference. The category covers GPUs, tensor and neural processing units, and custom ASICs, usually paired with high-bandwidth memory and fast interconnects. They are also called AI accelerators or AI semiconductors.
- AI cost managementAI cost management is the practice of tracking, forecasting and controlling what an organisation spends on AI systems, including model API calls, inference compute, vector storage and the tooling around them. It applies familiar financial discipline to usage that is variable, token based and easy to scale without noticing. The goal is predictable spend at an acceptable level of quality and latency, rather than the lowest possible bill.
- AI drug discoveryAI drug discovery is the use of machine learning and computational models to support the early stages of finding and refining new medicines. Models are applied to tasks such as predicting protein structures, identifying candidate molecules, prioritising targets and estimating properties like toxicity or binding affinity. The aim is to narrow a very large search space before expensive laboratory and clinical work begins.
- AI infrastructureAI infrastructure is the stack of hardware, networking, storage and software needed to train, fine-tune and serve AI models at scale. It spans accelerators such as GPUs, the data centres and power that house them, and the orchestration and serving layers that turn raw compute into working model endpoints. For most marketing teams it is a cost and capacity constraint they consume through APIs rather than something they build.
- AI procurementAI procurement is the process of evaluating, buying and contracting artificial intelligence tools and services, from assistants and content platforms to models accessed through an application programming interface. It covers commercial terms alongside security, data protection, accuracy and integration questions that do not arise with ordinary software. Most organisations run it as a structured review with pilots, stakeholder sign off and defined exit conditions.
Primary research · August 2026
How ChatGPT Shortlists Software Brands
An audit across 10 categories and 60 buying questions. I recorded what ChatGPT reads, throws away and links to when a buyer asks it which software to buy, and what that decides.
- 60
- Questions asked
- 10
- Software markets
- 2,680
- Results read
- 367
- Links shown
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