DEI in the age of AI: The business case for gender equity

You might have noticed that Diversity, Inclusion and Equity (‘DEI’) has become deeply politicised in recent months. The US government has banned DEI programmes across the federal government – and plenty of private companies are following suit. Rather than helping companies thrive, the argument goes, these initiatives are posed as divisive and ineffective.

Politics aside, the evidence shows that diversity actually works for business. And I believe that as AI begins to reshape the future of work, it’s more important now than ever to make sure equity is part of workplace and AI development. Decisions taken now could endure for many years.

Measuring ‘Social Return On Investment’

GIST Impact, where I work, is a leading social and environmental impact data and analytics company. We help organisations measure and understand their real-world impact – on people, communities, and the planet – so they can make better, science-backed, and data-driven decisions.

One metric we use is Social Return on Investment (SROI). This goes beyond traditional financial returns to quantify the broader value businesses create (or destroy) for society. SROI converts social and environmental benefits into monetary terms – which is often vital when justifying spending decisions.

For instance, when we analysed the SROI of businesses undertaking Apprenticeships with QA, we demonstrated that £6.89 of social value is generated for every £1 invested. Critically, 62% of this benefit goes to people from lower-income backgrounds, demonstrating the program's role in promoting social equity. This clarity helps companies see the true value of their investments, making the impact impossible to ignore.

Another example is TechHer, a digital skills programme by Microsoft, which aims to help more women enter the tech workforce by running digital bootcamps. We evaluated this programme and found that it is expected to improve the earning potential of women by 33%, which goes a long way towards empowering them and closing the gender pay gap.

The business case for DEI

Importantly, these benefits fall not just on the individual, but on the company. Gender diversity in the workplace isn’t just about fairness; female representation within business translates to higher performance, innovation, and resilience. Diverse teams outperform. McKinsey showed that companies in the top quartile for executive-level gender diversity are 25% more likely to have above-average profitability, compared to the bottom quartile. According to IBM, businesses who lead in gender equity report 19% higher revenue growth.

A study by Catalyst showed that companies with sustained high representation of women in the C-Suite, defined as those with at least 24% diversity in at least four of five years, significantly outperform those with sustained low representation by 37% on Return on Sales (ROS), by 67% on Return on Invested Capital (ROIC), and by 52% on Return on Equity (ROE).

Studies have also shown that when more women hold leadership positions, overall leadership skills improve for everyone, not just women. In addition, research suggests that women in leadership roles tend to make more cautious economic choices, which can reduce risk. As a result, companies with greater female leadership often experience consistently better and more resilient economic results.

Diversity also improves employee loyalty, brand reputation, and talent attraction. This really matters in an age where recruiting and retaining staff is paramoun. Capgemini's formalised Employee Network Groups (ENGs) for Gender, LGBT+, Disability, and Ethnicity, have driven a 10 per cent increase in employee retention. The data is clear: businesses that prioritise gender equity don’t just do good – they do better. 

Why DEI matters now

It is increasingly clear that AI is a force multiplier. It can reinforce existing biases, but it could also be a force for inclusion. AI is already shaping our world, and its role in our future is only set to grow, so it’s on us to ensure it is used for the good of people.

Let me give you an example of a key risk. Vicky Crockett, QA’s Director of Data and AI wrote recently that women are at higher risk of being replaced by AI; they represent a large part of the workforce in professions that may become automated.

Not only that, the development of AI itself, due to a lack of diversity in users (75 per cent of ChatGPT users are men) and in the teams building the models, risks entrenching gender bias further and further. We’re still in the development phase of these models. If AI is a force-multiplier, it’s vital we’re multiplying the right things.

That means, among other priorities, bringing more women on as AI users, elevating women to influence AI-related decision-making , and training up entry-level talent in the AI sector. For AI to remain and become fair, a World Economic Forum report recommends involving women in AI development to identify and reduce biases leading to more equitable impact. We must be intentional about inclusivity; without intervention, the tech gender gap will only widen.

Where do business fit in?

Businesses have an opportunity to fight fire with fire, and use AI as a tool to drive progress. A recent EY report underscores the potential of AI as an 'inclusion catalyst', which can help people maximise their potential. In practice, this can mean using AI assistants to reduce bias in recruitment; improving accessibility for those with disabilities, and ensuring promotions are based on objective data, free from stereotypes about what different groups can or cannot do.   

This can only succeed if we actively track and measure impact – enabling us to course correct towards the most positive outcomes, while ensuring and making sure AI-based solutions are designed and used fairly.

Encouragingly, we can also use AI to improve impact measurement itself, as AI will revolutionise how and where we collect data: we are no longer limited to just static input sources. This allows us to track gender and other forms of diversity in ever more granular ways.

AI can also pinpoint positive impacts hidden in unstructured and textual data. For example, where someone has been through a gender sensitivity course, and their language and tone has since changed to be more inclusive, AI is able to bring this otherwise overlooked datapoint to the fore. These, and many more granular examples, all help to build the case for investments in diversity, upskilling, and inclusive hiring, by quantifying meaningful, measurable impact.

In the age of AI, this isn’t just important – it’s essential. 

Mahima Sukhdev, SVP of Commercial Development, GIST Impact

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