<strong>How Artificial Intelligence can drive diversity, equity, and inclusion in the workplace</strong>

Diversity, equity, and inclusion (DEI) have become crucial to a successful workplace. It is also no secret – a fact that’s supported by several reports – that diverse companies are likely to have financial returns above their national industry medians.

Indeed, we have come a long way since 2014, when McKinsey released Diversity Matters, its very first report on diversity. More organisations today are seeing the value in diversity, and many are leveraging AI to accelerate and enhance their DEI efforts.

At the heart of this endeavor is people analytics, which can offer HR leaders data insights on matters relevant to their staff. It can also help them identify diversity gaps in the organisation.

Here is how AI could potentially revolutionise the landscape of diversity, equity, and inclusion in workplaces.

AI-based recruitment can be shorn of human biases and unconscious discrimination

Unconscious biases are the biggest hindrance to diversity, especially when hiring. It is a seemingly easy choice when the toss-up is between a bright candidate from an elite university or a bright candidate from an average one. But could it be that the latter didn’t go to an elite university because they couldn’t afford it?

An AI algorithm can easily highlight privilege by analysing the two candidates’ resumes. The postal code of their respective schools, for instance, can offer a view into their socio-economic background thus empowering the manager to arrive at a more educated decision with the hiring.

AI can help reduce the pay gap

According to the World Economic Forum, the gender pay gap will take another 136 years to close. AI can help eliminate this by offering insights into an employee’s performance and aspirations.

For instance, a female employee spending fewer hours at the workplace than her male counterpart could highlight efficiency rather than his ‘dedication’.An AI algorithm could sift through data to highlight this efficiency gap and empower their manager to make a case to plug the pay gap.

AI can identify the right employees and aid employee development and upskilling

Often, an employee’s aspirations, background, and abilities are stored in silos within the same organisation. People analytics software can link these three data points and provide a comprehensive view to HR managers into the employee’s past and current performance as well as where they want to be basis the certifications they’ve applied for.HR managers can help employees not just upskill themselves but also find them the right (or better) job.

AI can facilitate seamless communication among diverse teams

AI can help global companies operating from diverse geographies, break down language barriers, and foster a sense of inclusivity. It can assist people with disabilities by providing accessibility support like captioning and empowering them to fully participate in the workplace.

AI-powered AR/VR collaboration spaces for flexible working

To truly create an inclusive workspace, enterprises must be sensitive to the needs of different groups and offer adequate flexibility. Enterprises have struggled to provide different modes of working like hybrid work, because achieving a seamless collaboration with geographically dispersed teams has always been a challenge.

However, due to the latest advances in AI and AR/VR/XR, exceptional solutions are now available. In projects that require designing and construction, immersive 3D experiences powered by VR-assisted AI platforms can deliver much better value than traditional video conferencing tools. Additionally, interacting with virtual life-like avatars that can mimic your real actions can help geographically disparate team members maintain the human connection, and communicate on a deeper level.

AI-Powered Personalized Assistants augmenting “Return to Work” initiatives

Generative AI-powered assistants can provide personalized guidance in terms of training and re-skilling, improving employee experience in functions like onboarding and acting as a personalized mentor. This can bolster the effectiveness of programs like “Return to Work”, where a lot of initial handholding might be needed for a smooth transition.

Challenges with AI

As with everything else, AI has its own challenges. An algorithm can only be unbiased if its creators are unbiased. This presents a unique challenge and creates a potential loop. To break this, it is important to create unbiased data sets so AI can make more balanced decisions.

This can be accomplished by introducing transparency and accountability in AI algorithms. Implementing Explainable AI (XAI) principles helps in removing the biases at an early stage.

Diverse businesses make for successful businesses. By building a case study around this principle, CIOs can get internal stakeholders on board, sign off on budgets, and ultimately, leverage technology to create an unbiased, inclusive, and equitable workplace.

Authored By:

Lax Gopisetty, Vice President, Global Practice Head for Microsoft Business Applications & Digital Workplace Services, Infosys