As artificial intelligence and machine learning increasingly offer significant improvements to the way organisations manage their workforces, what are the opportunities and potential risks of AI-enabled HCM solutions?
The world of work is changing faster than ever, with machine intelligence and artificial intelligence set to fundamentally alter the way work is done worldwide. The depth of this shift should not be underestimated and over the next decade is likely to significantly impact a swathe of professions and industries, including human capital management (HCM).
Indeed, looking globally, the estimated share of existing jobs that could be automated by the 2030s due to AI varies across countries, but ranges from around 22 per cent in Finland and South Korea to up to a staggering 44 per cent of jobs in the central European nation of Slovakia, according to PWC research. Australia, too, is set to feel the effects of the AI revolution, with research Frost & Sullivan predicting more than 40 per cent of high-routine and low-skilled tasks will be automated in Australia by 2030 thanks to advances in AI.
Human capital management (HCM) practitioners are not immune from the rapid advances in technology in the form of improvements in artificial intelligence and machine learning. In fact, the impact of AI is already being felt in the sector as more companies deploy AI-driven tools as part of their HCM technical stack. This is borne out by recent research revealing the number of companies using AI to a high or very high degree in the HR industry hit 10 per cent in 2018. That number is set to rise further, according to the HR.com research, with nearly 46 per cent of firms expecting to see high or very high usage of AI by 2024.
Using AI to Solve HCM Challenges
Against this backdrop of significant market disruption, there nonetheless exists the potential for HCM practitioners to harness the potential of artificial intelligence and machine learning to solve current challenges. This may include, for instance, deploying AI to assist with tasks like scheduling, workforce optimisation, applying varying award rates and EBA agreement rates, and managing the needs of personnel against ongoing business requirements.
Importantly, reframing AI in this way — as an opportunity rather than a threat — requires HCM practitioners inside firms who are willing, and courageous enough, to take a fresh look at how to use AI to improve efficiencies, cut red tape, and improve their HCM workflows.
Here are some examples of how AI can be integrated by companies for their HCM workflows.
- Talent acquisition: AI is being deployed to better recruit and process candidates, including identifying and tracking top applicants’ characteristics. Simply put, AI can pinpoint the best CVs and highlight them from potentially hundreds, or thousands, of CVs received, accelerating the hiring process and bringing down the often-substantial time and financial cost of a resource-intensive process.
- Employee experience/engagement: AI can provide insight on the company and its employees. For instance, HCM systems can use AI to give practitioners greater access to data-driven statistics and reports to gain a clearer picture of a workforce and then be used to augment training, professional development, and workplace settings.
- Regulatory/compliance functions: AI can be integrated to reduce costs and speed up time in maintaining regulatory compliance. Machine learning allows, for instance, the monitoring of payroll systems for compliance and is also able to automatically update systems based on changing regulations. What’s more, AI has the capacity to not only monitor changing rules, but also to automatically make corrections and updates.
Getting the AI Right
Reconceptualising AI in this manner – as a tool that empowers HCM practitioners with their daily tasks – is not the end of the story. That’s because for AI to be truly useful in workplaces both in Australia and globally it needs to be thoughtfully designed and fit for purpose.
Here, it is critical that decision-makers do not rush to AI technology without first understanding the composition of their workforce and how their company engages with elements of the business such as payroll, rostering, operations and HR. Taking this initial step will mean that the business is in a better position to ensure any AI solution can seamlessly interact, learn and deploy solutions at different locations within the business.
To this end, an AI HCM solution will vary from company to company depending on factors such as where employee data resides and how it must be extracted. Some considerations at this stage may include: identifying pain-points, performing a data-audit to ensure data integrity, documenting KPIs and expected outcomes, and creating a change-management strategy for stakeholders.
After evaluation, the options can be clearly assessed to determine what, if any, AI-based tool is the right option. There are many off the shelf products currently on the market that are increasingly integrating AI, with global workforce management organisation Kronos along with Ceridian, Success Factors, and Oracle all moving fast on AI within their HCM offerings. Additionally, there has been a spate of strategic acquisitions by large HCM systems providers of smaller companies with AI expertise, for instance, Oracle adding DataScience.com to its fold in 2018, suggesting that investment in the area is set to accelerate.
Irrespective of the approach companies determine is best for them, what’s clear is that with advances in AI and machine learning set to increase in the period ahead, it’s essential that HCM practitioners assess how AI can be used to harness, not hinder, HCM workflows.
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