AI Use Cases 

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.

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)

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).

Map communications across the firm to understand key nodes of influence - Eg: to identify key communicators and experts internally and externally. The stated aim is usually to analyse the meta-data of communications (eg who talks to who, when) rather than the content (what they say to each other) and how this impacts team productivity.

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.

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.

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

Use chatbot to address common queries from employees about benefits, payroll, policies etc

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

Automate delivery of employee benefit programmes - ensuring that personalised recommendations are made across options (eg based on location, expressed preferences etc) which can then be automatically delivered (in the form of coupons, localised offers etc). These might include personal development, retail, well-being or charitable activities.

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.

Monitor employee communication to identify key topics of conversation - this should help management head of emerging issues or better understand key organisational challenges.

Gather, collate and display critical information for performance management. Key performance indicators can be calculated and displayed, including information on outliers.

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

Use latest algorithms to provide better predictive modelling and classification than current techniques.

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.

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.

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.

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

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.

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

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.

Doing expenses is a pain point for many workers. Taking a photo of the relevant receipts and automatically generating an expense report can save considerable time (for individual and organisation) and potentially reduce mistakes or issues. Operationally some operators may be relatively reliant on Mechanical Turk workteams to deliver supervised learning which has raised potential confidentiality issues,