Our whole life is now permeated with technology. And the further - the more technologically our reality will become. Those who understood this before others - were on the wave's crest and collected all the bonuses from this.

It is becoming increasingly essential to reimagine business and use digital technologies to create new business processes, cultures, customer experiences, and opportunities. Most custom software development firms quickly adapt to changing technologies and offer state-of-the-art solutions to their clients.

To succeed, digital transformation is inherently necessary and dependent on diversity.

That is why it is essential to be able to be diverse and think outside the box. Forbes notes that companies are forced to reduce labor costs while expanding consumer reach significantly to remain competitive. Still, very little attention is paid to diversity beyond gender and human factors as part of embracing the broader dynamics of change.

Artificial intelligence (AI) is the result of human intelligence. We have transferred all our talent to AI and also created limitations.

Humans are always the most crucial part of artificial intelligence. The diversity of people, and the team of decision-makers in creating AI algorithms, should reflect the diversity of the population as a whole.

And it's not just about giving women opportunities to work in the field of AI and technology. It should also include all aspects of gender, race, ethnicity, skill set, experience, geography, education, attitudes, interests, and more. Why? When you have different teams looking at and analyzing data to make decisions, it reduces the likelihood that their individual and unique human experiences, privileges, and limitations will blind them to the experiences of others.

We must apply artificial intelligence and machine learning to create our unique future. It starts with different teams of people that reflect all the diversity and rich perspectives of our world.

At the same time, the capabilities of artificial intelligence and machine learning are only as good as the data that enters the system.

Statista data says that the global artificial intelligence (AI) software market will multiply in the coming years and reach approximately US$126 billion by 2025.

And this means that we must treat the data with which we work with all attention, especially to the sources from where we take them.

In addition to people and data, it is necessary to provide various tools and methods for creating and producing algorithms. Some AI systems, and products use classification methods that can perpetuate racial or gender bias.

For example, classification methods assume that gender is binary and generally define people as either "male" or "female" based on their physical appearance and stereotypical assumptions, meaning that all other forms of gender identity are obliterated. It is a problem, and everyone in this field, any company or industry, must prevent bias and improve methods to cover all the nuances and ranges of people's lives.

Various people, data, methods, and tools help implement business tasks efficiently and correctly. The diversity of artificial intelligence is one of the last opportunities to continue this legacy and shape the tech industry's future.

Author’s bio: Anastasiia Lastovetska is a technology writer at MLSDev, a software development company that builds web & mobile app solutions from scratch. She researches the area of technology to create great content about app development, UX/UI design, tech & business consulting.