Implementing AI across the hire-to-retire journey

As of January 2024, 38 per cent of HR leaders were already piloting, implementing, or considering implementing generative AI (GenAI) solutions in the workplace, according to a Gartner study. This was twice the proportion of HR leaders surveyed in June 2023, marking a significant increase in adoption rates.

“AI is no longer a nice-to-have in HR. AI is actually coming into play in the moments that matter, across the hire-to-retire journey,” shared HCLTech’s Senior Vice President and Country Head, Malaysia, Anuradha Khosla.

These include recruiting the right talent with AI-enabled tools, implementing co-pilots and other AI tools to make employees’ lives easier, helping to retain talent, and in conducting sentiment analysis to monitor employee wellness, she explained.

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Supporting HR productivity

HR leaders need to prioritise the areas where AI can provide the most business value, noted leaders from HCLTech.

“The biggest advantage that we are seeing is that GenAI is significantly improving employee productivity,” shared HCLTech’s Practice Director of Data and AI, Murugan Anantharaman.

He noted that HR employees can use AI to automate and streamline their tasks.

Khosla added that AI can speed up repetitive HR tasks such as screening resumes and scheduling interviews. This can streamline the recruitment process, reduce recruiter workload and improve productivity. In turn, HR professionals can focus on more strategic tasks over operational tasks.

There is also potential to provide AI-powered self-service platforms across many business functions in HR operations, call centers, and service delivery centers, she said. For example, HCLTech worked with a customer to develop GenAI-enabled chatbots that can provide support to employees on policies and operations, improving employe productivity.

Personalising employee experience

AI can also improve employee experience through personalisation, Anantharaman said.

HR leaders can use AI to regularly analyse employee feedback through sentiment analyses, and summarise large volumes of such data, extracting key insights and opportunities for intervention, Khosla added.

“Those inputs can go back into personalised training programmes, to enhance employee performance and improve overall job satisfaction,” she said.

Leaders can use predictive models to forecast talent trends and support them in making more informed HR decisions. For instance, leaders can use GenAI to analyse external data and summarise millions of open jobs to develop competitive pay, incentives, and other benefit programmes to support talent attraction and retention.

There is also potential for leaders to deploy AI to support DEI initiatives and reduce bias in hiring, Khosla said. These AI tools can remove gender bias, age bias, racial bias, and more during the recruitment process.

According to recent Gartner research, the top use cases for GenAI in HR include employee-facing chatbots as well as supporting HR operations and recruitment efforts.

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Picking the right tool

HCLTech noted that it is important to pick the right tool for the right task.

For instance, leaders can tap on AI tools that come as part of an end-to-end suite or build standalone tools which can extract insights for specific needs.

“If I look at it from a DEI lens, AI tools instantly provide insights and inputs, where I would otherwise have been using multiple pivot tables and so on. It accelerates the pace of the changes that you're trying to drive,” said Khosla.

HCLTech works with organisations to build custom AI models to solve specific problems, such improving performance analysis, said Anantharaman.

He added that these tools can help to answer questions like: “What is it that the employee can do better? What are the areas which need more focus?”

Once leaders have these insights, they can create action plans on the spot to solve any concerns in a timely manner, added Khosla. Traditionally, HR leaders would otherwise have to wait for the results of annual surveys before implementing interventions.

Guarding against AI risks

Of course, it is critical to ensure that custom models remain safe from concerns such as hallucinations, bias, or toxicity.

One way to do this is through a human-in-the-loop approach, where HR leaders analyse and validate AI outputs.

“No matter how well defined a process that you have, how clean the data that you have is, or how well you create your models, the human-in-the-loop element makes all the difference,” said Anantharaman.

This is particularly true for HR, as decisions can impact careers and employee’s lives, he noted.

“HR organisations are a reflection of an organisation’s health as well as the morale of employees.”

Getting started

It is important to prioritise which HR use cases to pursue by evaluating the potential impact of GenAI capabilities, before assessing technical feasibility, Khosla explained.

And implementing AI cannot be a one-off exercise – it requires sustained efforts on the part of HR leaders, said Khosla.

Leaders need to regularly check in on the adoption rate of new initiatives and identify roadblocks – could it be that the tools are not providing the business value they were expected to, or are employees’ mindsets getting in the way?

Once these obstacles are identified, leaders may need to go back to the drawing board and re-evaluate their rollout, Khosla explained.

For instance, employees may be concerned that AI will replace their jobs, and leaders need to demonstrate that AI will make their lives easier, noted Anantharaman. Leaders can also implement an AI playbook to support HR in using AI in their day-to-day work.