First published on HFM Connect.
By George Ralph, Global Managing Director and CRO
AI is starting to show its versatility and it is becoming more of a disruptive force in day-to-day business. The human resources sector is a good example of this. HR is undergoing a profound shift, and the practice of Human Capital Management (HCM), which focuses on the organisational need to manage identified competencies, including workforce acquisition, workforce management and workforce optimisation according to Gartner. AI also uses data to reveal future trends, predict behaviour and manage the future talent needs of your business. Furthermore, it can automate routine HR tasks, deliver personalised experiences back to your team and help create actionable insights from the data harvested from each employee.
AI and machine learning platforms that constantly consume information to improve the accuracy and efficacy of human tasks hold great potential when paired with a more traditional human resources approach. AI in talent management can help organisations streamline processes, manage workforce productivity, improve functional efficiency, and make more informed people decisions that can directly impact the overall organisation. In a time where hybrid or remote working is the normal day to day function of a business, using data to collate, corroborate and monitor team behaviours is becoming a necessity and much more than a ‘nice to have’.
In a recent IBM survey, 66% of CEOs who were surveyed said they felt cognitive computing could drive significant value in HR, and almost 40% said they expect their HR function to adopt cognitive solutions in the short to medium term. The new approach to AI managed human resources gives firms the ability to measure the resource value of individuals within a business and therefore help a firm manage its growth strategy.
Something as simple as Cortana, Microsoft’s personal productivity assistant, can provide each user with their own daily feedback and help measure performance. It is the same basic principle of machine learning. An individual’s user data is being used to provide details of not only tasks and processes; it also helps the user better manage their time and tasks for maximum output and efficiency. Human-led HR teams simply cannot handle the same number of data and touch points as ML can. But there is a need for both; you need human interaction to measure emotion, and that can be one of the biggest ‘tells’ when you are trying to manage your team, particularly in a remote capacity. While seeking out and reporting on data patterns might be useful in terms of managing your team’s time away from their desk, managing mental health is a human interaction. The more personal contact we have with our teams, particularly in a remote environment, the better chance we have of avoiding negative leaver experiences.
There are real positives to introducing AI and ML as part of your overall digital transformation process in the field of HR in spotting and nurturing talent, managing laser-focused training and searching for connections, patterns, and correlative insights. In a remote working environment, one of the most difficult things to spot is when an employee isn’t happy or is planning to leave. In the current climate, company security perimeters have been pushed further out, decentralising cybersecurity and calling for a need for newer and more advanced end point security tools.
We know, too, that there has been a rise in cyber-attacks, which has increased demand for forensics and incident response needs in cybersecurity, but there is also a need to use behavioural analysis to keep oversight of your team to keep company and client data safe on the inside. Using real-time analytics can not only show the impact that absences and unplanned diary changes might have on KPI’s, it can also allow firms to spot anomalies in when and how an employee logs in, what kind of files they are trying to access or download and any other unusual behaviour that could be cause for concern and might require further investigation by a manager.
Rogue staff or potential bad leavers are a hazard in every firm. RFA’s Managed Detection Response, incorporating Endpoint Detection Response, monitors processes and executables at the endpoint, but also monitors for potential adversarial activity. Leak detection and alerting preserves the integrity of corporate data at the endpoint, and MDR provides predictive alerting while correlating events to also identifying risk. Working to provide a 360-degree view of your technology estate, MDR not only delivers 24/7/365 cyber-attack prevention and management from outside actors, machine learning monitors user behaviour and experiences to flag internal anomalies that may require further investigation. Where data security is elevated due to travel for example, RFA deliver containerised desktops to machines, allowing users to view data, presentations and contracts, but not to download or deliver to external sources via email.
Human interaction isn’t just a necessity it is also a pleasure and while we don’t want our current experiences to have a long term impact on this, it also makes good business sense to consider your HR strategy as part of your overall digital transformation strategy. Using the tools that are available will allow your mangers to have more time available to help develop your employees and support their career, therefore reducing the risk of bad leavers to begin with.