How AI Democratization Will Change In the Next 10 Years | Razor Think

How AI Democratization Will Change In the Next 10 Years


Once a thing of science fiction, artificial intelligence (AI) is now a reality and steadily improving, providing companies with greater benefits as the technology develops. Machine learning makes it so AI can continue to learn and expand based on the data it processes. In the next 10 years, companies have the opportunity to make data more available through democratization and help AI learn at a faster rate as a result.

As you learn more about the democratization of artificial intelligence and its potential for the not too distant future, you first need to know what it is and why it’s so important. You should also be aware of some steps companies can take to help AI become more democratized and the potential democratization has for the world.

What Does Democratizing AI Mean?

The democratization of AI is one of the most promising developments in technology and machine learning. Like in democratic societies where all people are meant to be represented, the democratization AI is built around making it possible for everyone to access AI.

In a business context, AI democratization refers to the ability for all organizations to use AI, with the possibility of every employee using it as well. With the machine learning tools, AI incorporates both software and hardware to take action based on information learned by listening to and watching patterns. The future will only see more of this, with AI democratization potentially allowing everyone within an industry to reap the benefits of this technology.

Why-is-AI-democratization-importantWhy Is AI Democratization Important?

In a recent study, only 60% of European startups are using AI to affect their value proposition. In other words, 40% of startups aren’t using AI well enough to make them more attractive to potential clients or customers. If we were to factor in established companies attached to old processes and ways of thinking, it’s likely we’d see even more companies not getting enough value out of AI.

With so many companies not reaping the benefits of AI, it’s natural to wonder why they are failing to use AI to its full potential. Taking a closer look at AI, it becomes obvious why many businesses aren’t getting the most out of the technology. Effectively using AI requires a company to have knowledge in a variety of areas, including data analysis, statistics and coding, among other industry-specific knowledge.

Besides the skills companies should have to get the most out of AI, there’s also the issue of AI models needing tons of data to process and learn from. Without this data, the AI can’t be effectively trained, as its machine learning tools aren’t fully utilized. Additionally, companies may not be willing to make the initial investment into their data infrastructure to make the AI work effectively.

AI democratization has the potential to solve many of these problems. If the technology is available to a wider range of companies, they can better utilize AI and do so at lower costs. The democratization of machine learning and AI takes the technology out of the hands of the few and makes it accessible for all. With greater accessibility, more people can interact with AI, using it for industry-specific tasks.

How Can AI Democratization Impact Our Future?

The future impact of AI democratization could have huge benefits to businesses all around the globe and society at large. If AI continues to be democratized, a broader segment of the population is likely to use it, and its cost will probably come down. Learn more about the impact of democratizing AI below:

  • More AI users: One of the main tenets of democratizing AI is making sure that everyone has access to it. As AI is democratized, more companies, organizations and users can utilize it to complete tasks faster and assist with a wider variety of operations. Since AI can be paired with machine learning tools, it can better learn how to help your business and improve your bottom line. With AI democratized, its potential can be reached faster, allowing for greater profits and efficiency for all.
  • Aiding societal issues: The democratization of AI gives nonprofits, governmental agencies and individuals the ability to tackle tough issues. As AI continues to learn more and those results are shared, users can get greater insights into the issue they hope to address. For example, AI can be used in health care to develop standards of care and eliminate disparities between men and women’s health.
  • More affordable AI: Currently, companies have to pay top dollar to get the best data and AI specialists in the industry to help them. By making AI more available to companies, cloud technologies can offer more tools and reduce the need to pay for a data specialist. This greater availability will bring down AI’s overall costs.

How Do We Get There?

While all these benefits are probably something you’d like to receive, you may not know how to get to the point where AI’s costs are lower and the data is more accessible to various users. Below are some of the main steps to making AI more democratic:

1. Improved Data Quality and Greater Accessibility

One of the first steps to democratizing AI is making data more available and improving its quality. Currently, companies usually have limited data to work with as they look to build AI models, which can make it difficult to be accurate. Additionally, companies often have to work with data that’s not complete, leading to AI models that could be misleading or unstable.

Since AI needs accurate data, as well as a large supply of it, to produce reliable results, it’s crucial that democratizing AI starts with democratizing data management. To make sure more data is available to companies and that the quality is high, everyone must be taught about the importance of data organization, quality assurance and preservation. With this awareness, individuals and organizations will be more willing to share data and more likely to ensure their data is accurate.

2. Accessible Interfaces

AI is built on complex coding, which can be intimidating for those who aren’t coders. Many people may want to work with AI, but everyone can’t suddenly become a coder. Instead, the democratization process makes AI more accessible for everyone, from coding experts to novices.

To make AI accessible to people other than coders, user-friendly interfaces that provide coding tools are absolutely crucial. These interfaces will give users access to data and the ability to interact with it without being an expert.

3. More Understandable Results

Similar to the need for accessible interfaces, the results of AI data analyses need to be more understandable to a wider audience. It’s important that as AI grows, people work in cross-functional teams to develop ways to better explain the results of data models to those in the company who may not know how to read models and grasp their conclusions. By making AI’s results more understandable, more people will be able to see AI’s potential and commit to using it regularly.

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