It is commonly acknowledged that AI is leveraged by companies to engage their customers, but little is accomplished by way of technology to keep their own employees satisfied. This is slowly changing. More and more organisations are exploring the potential of AI in keeping their workforce more productive – by keeping them happier. 

Talking about how technologies like AI can deliver multiple benefits to employees in their day-to-day work, Shivani Rai Gupta of Capgemini addressed a gathering of over 250 people at Rising 2019. Gupta, who heads AI and data science in financial services at the tech major, spoke at length about AI’s ability to perform both high-value and mundane tasks for employees with greater levels of effectiveness.

Why Chase Employee Satisfaction?

Companies strongly feel that happy employees create high business value for them and hence, help in influencing revenues and generating overall success. According to a report released by Deloitte, only 23% of companies believe that their employees are aligned with their goals. This indicates that a massive chunk is not happy with the work they are doing, and are thus, not being productive at work. 

According to Gupta, one way of cutting through this slack is by reducing technological difficulties faced by employees. This includes operational challenges as well as software errors – both of which should be minimised.

Chatbots are increasingly being channelised by companies to solve these internal issues. This eliminates the need to chase people since the technology already handles the problem for you. Another common approach is tech-enabled search engine machinery for simple use cases like policy information, insurance details etc.

But this is just skimming the surface. Can repetitive and mundane tasks of employees be automated?

AI Minimising Cumbersome Tasks

Employees, especially those who travel on a routine basis, file their reimbursement claims regularly. A technique to automate that end-to-end process, which saves you time and energy is long overdue. It will also enable employees to use that time in a more productive manner. HR departments are constantly looking to AI for creative ideas. Transitioning to soft copies and going paperless was a start. But there is space for more innovation here.

Automating employee onboarding process in one.

Every time people switch jobs, they spend about 3-4 hours on an average filling out forms documenting their educational background, previous company details, salary certificates, and bank statements, among others. These forms are processed and validated by a team, who may reach out to a third party for background verification, and/or compare it with the information provided in the resume.

This entire process can be automated and made seamless without any human intervention.

This is one of the biggest applications, where the industry is leveraging AI to ultimately satisfy its employees. With this, they only need to take pictures of their documents, upload it onto a portal and the rest will be taken care of by the AI engine. 

It also solves the problem of reading information across a wide range of formats. For instance, university mark sheets come in different forms and sizes, and even languages. Another example is salary slips – no two companies share the same structural format of this document. But AI can be trained to go around these differences and still extract the required information.

Identifying Right Learning Programs

With reskilling being the need of the hour, it is a good practice for employees to take advantage of learning programs facilitated by their companies. This is typically done in two ways – either employee identifies what fits well with their career growth, or companies give them a list of training programs, which is more from a demand perspective. 

For instance, if you are a SaaS expert, but there is a demand for python, in all likelihood, companies will send everyone to python training, whether they are interested or not. But this is slowly changing. Today, companies have started evaluating both demand and employee personalities when allocating such programs. And AI has enabled this.

Using AI, employees’ learning curve can be traced and analysed to give insights on what the best programs would be for them. For instance, if you are an ETL expert, and you want to get into the data science field, you can now understand the different steps you may have to take to conquer that path. Additionally, you will also get information around how people with a similar background have succeeded in this journey and what their learning path was like.