Automatically assess candidates, including emotions, from automated video interviews.

Proactive sourcing of potential candidates for roles using social media, industry databases and other sources like news feeds

Inadvertent wording of job listings can alienate potential candidates who may feel that the employer is not looking for employees with their profile. Using NLP to improve job listings can help remove one barrier to more diverse applications.

Leverage AI to automate the onboarding process of new employees - e.g. data extraction, and capture, form auto-generation, process management

Scan resumes to improve diversity and quality of candidate pool for recruitment. This will both challenge unconscious bias but also help challenge key gaps in candidate sourcing practice.

Automating responses to questions candidates have regarding the position and company during the application process to help assessment of position and candidate fit potential earlier on

When job seeking there is difficulty in reflecting on and improving a CV after having worked on it for a lot of time: candidates can use technology to do that for them before they apply for jobs. The technology will have been trained on successful CVs and resumes to identify how the content has been articulated. Therefore, such a system can compare the input with its database and identify areas for improvement. Increasingly this is effectively about reverse engineering recruitment algorithms.

Identify the characteristics and behaviours of the most successful and effective employees. This is an area of potential algorithmic bias risk.

Delivery of relevant training materials, reinforced with feedback loops to make sure that progress is appropriate. Feedback loop can then drive subject matter iteration, progress to new content or a structured focus to reinforce skills gaps - likely with additional human intervention. Clarity on what is being measured and captured is a critical definitional challenge - as is the extent to which educational professionals are in the loop.

Use 3D sensors to support the decision making process for judges in sports that require scoring or judgement calls. An example of this would be gymnastics where the tool can be trained on routine peformances. These tools may also be used to support individual's althletic training regimes.

Recommends specific training based on performance review data

Predict which employees are likely to churn and improve their job satisfaction to retain them

Assess compatibility of employees or candidates to form efficient teams using data collected from personality quizzes

Develop plans with deep historic insights into previous plans and performance to generate forward looking insights.

Monitor employee actions to determine non productive and personal activities. Some of these may be specifically unacceptable - accessing inappropriate material on work equipment for example - but others may simply be a measure of productivity lost to social media.

HR analytics are used to analyse and measure a variety of factors to predict likely staff satisfaction and predict potential trajectories. Models can be used to assess likely factors driving key business metrics - for example the impact on staff retention.

Collect and measure physical behaviour how people moved through the day, who they interacted with, what their tone of voice was like, if they leaned into listen and other types of interactions that happen at every company every day. Use this to determine whether there are opportunities to improve team productivity.

Employees in conversation record an account of their concerns and issues which is automatically captured and transcribed. HR gets a detailed report and can conduct follow-up interviews through the bot. Potentially, employees can stay anonymous if they so choose.

Monitor employees engagement with chatbot for better productivity measurement. This may be a role better carried out by managers but this can provide additional oversight and insight.

Provide payroll and other employee remuneration services with standard services such as information requests or updates handled on an automated basis.

Using historic performance data (typically personal and comparable cohort), skills learnt and exhibited and forward looking information on likely organisational skills or resource requirements to predict potential future performance of individuals. This can potentially be used to support resource planning - and could potentially open the organisation to legal risks (depending on implementation; e.g. should this be used to drive compensation).

Using robotic sensors to capture surgeons' performances during robot-assisted surgery and analysing resulting performance data. This has a knock-on impact of potentially reducing medical malpractice liability exposure.

Build on feedback from residents to create optimal mood-related visual stimuli in residential or office settings. This may include support for better interior design (using associated technologies including augmented reality) but also may lead to annoying whale music.

Sensors and advanced analytics improve building management- - e.g. space management, health and safety

Using wifi signals to identify which individuals are moving - even through physical barriers such as walls. Potential real world uses will include security or facilities tasks - and in the medium term various healthcare or interactive gaming scenarios.

Use real time sensors and data tracking to monitor staff presence and alertness (e.g. are they falling asleep on the job) to ensure maximum productivity and reduce risk (of process and output). Will also likely be used as an input to staff assessment, health and safety planning and overall workforce planning.

HIgh quality candidates may not be chosen for the roles that they applied for initially. CVs that are kept "on file" can be triaged for different roles.

Automate background checking for potential employees using social media, news feeds, references and relevant databases (credit scores, criminal record)

Optimise job posting descriptions to attract better and more diverse candidates by testing and then applying (for example) more gender neutral descriptive words and phrasing.

Score resumes based on the outcomes of past job interviews and hires with textual analysis