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Digital inclusion

The Key to Designing Inclusive Tech

Report from the Capgemini Research Institute

Creating diverse and inclusive tech teams

Digital technologies are increasingly embedded in all aspects of human life. With the integration of these technologies into products and services, exclusionary and biased outputs are also increasingly common, including biases and discrimination from AI-enabled systems.

Against this backdrop, there has been a rising demand for greater diversity, equity, and inclusion (DEI) in the workforce, especially in technology teams that develop and deploy the technologies with which end users interact. Do organizations understand the interplay between inclusion and diversity of tech workforce and the inclusive design of technologies? We wanted to find out.

For the latest Capgemini Research Institute report, The key to designing inclusive tech: creating diverse and inclusive tech teams we spoke with 500 tech employees, largely women and persons from ethnic minority communities and 500 leadership executives from large organizations across nine countries in key consumer-facing industries. We also spoke to 5,000 consumers, predominantly women and persons from ethnic minority communities. We found that diverse and inclusive tech teams lead to more inclusive tech design, but the current inclusion and diversity practices don’t work.   Leadership executives in organizations perceive processes and practices to be inclusive, whereas diverse employees in tech teams disagree to a large extent. However, this disagreement is lower in organizations who have advanced inclusive practices and culture. In addition, consumers have also experienced discriminatory tech and have expectations from organizations to do better.

Inclusive tech teams foster innovation, creativity, and inclusive design of technologies enable greater scalability of digital products and services, bringing organizations huge potential. But they need to have the right processes, practices, and value systems; they must drive fairness in AI systems and reduce algorithmic bias while also using data, tools, and technologies for better inclusion outcomes.  In addition, organizations must keep users at the center of all tech design practices to build more inclusive tech products and services.