The AI industry is booming - Make sure your technology is ahead of the competition

The AI industry is booming - Make sure your technology is ahead of the competition

The artificial intelligence (AI) and machine learning (ML) industries were set for growth even before the COVID-19 pandemic transpired. But with a global health crisis like that in our midst and an even greater demand for automated solutions, these industries are forecasted to boom in the years ahead.

Even now, it makes up almost one-fifth of the United States’ GDP and about a quarter of China’s. The global AI market grew by 154% in 2019 and even before the dire need for more automated solutions, it was forecasted to grow to $126 billion by 2025.

This growing demand for automation is not a belief or a prediction. It’s already happening.

In the retail industry, a new study by Bain & Company showed that companies had to use automation for business continuity during the coronavirus outbreak. Processes like payroll management, diagnosing customer experience and IT service issues had to be automated while offices were closed.

Some retail companies are even investing in robots to be a part of their workforce, taking over jobs that may be too risky for humans to do. But this trend isn’t just unique to the retail industry. Many other sectors are looking to automation as a solution to keep their businesses running.

Even before the pandemic, automation was a step for the agriculture industry to work its way into becoming more sustainable and efficient. In this current landscape, automation within the food supply chain could be what saves independent restaurants that are currently struggling for survival.

This is great news for the entire AI/ML sector, but it’s also a ray of light for everyone else. Increased demand for automation technology means sector growth, business continuity in other industries, and higher quality jobs in the job market. The cherry on top is that people would also get to stay off the street and go about their lives safely.

However, as the demand grows, there will also be a mushrooming of AI companies that offer the same type of automation, competing in a market that although vast, has its limits.

With the growing competition, there is a dire need for AI companies to maintain quality machines that perform at high accuracies. As more and more players flood the market, only the top-notch companies with the best machines will be able to stand out from the crowd.

Creating an AI business that stands out

In order to stand out, a business that offers AI/ML services needs to ensure that it provides a wonderful customer experience from end-to-end.

From the moment a client makes an inquiry up to the delivery of the AI/ML model, the entire process must be completed efficiently, while maintaining quality

For this to happen, a business must have the best talent on board to drive technology and innovation, as well as sales and customer service.

Whether their software engineers, marketers, or part of the sales team, creating and growing a team of highly qualified individuals can take your business to the next level.

On top of that, your technology has to work for your clients. It needs to be easy to use and at the same time perform at the highest levels of accuracy.

One half of the puzzle to achieving high accuracy is perfecting the algorithms needed for the machine to operate. The other half of it is equipping the machine with a high accuracy model.

This is only possible if a company has access to high-quality data training sets, which require some strategic planning to obtain.

The machine is what you feed it

There are several common solutions that AI companies can look at for producing high-quality data training sets. Some companies choose to crowdsource, others conduct the labeling in-house. Others still decide to use partners with fully managed teams.

Each of these solutions has its pros and cons and an AI company that’s on the lookout for the right solution has to consider its own resources and requirements, and after deciding on a solution, ask some pertinent questions.

Some of the things to consider before choosing a solution are time frame, budget, scalability, quality, diversity, and management capacity.

Important questions to ask during this process are: How soon does the project need to be up and running? How big is the budget? How fast would the solution have to scale?

What level of quality do you need and is data labeler diversity relevant for this particular project? What kind of manpower and bandwidth do you have available to manage the data-labeling task force so that they’re able to achieve desirable results?

No matter what solution AI companies go with, they should continue to make assessments and ensure that their models continue to be of high enough quality to meet their needs.

The most important step any AI company can take to make the most of this industry boom (that’s already happening) is to have the most accurate models and the most accurate AI machines. This is only possible with the most accurate training data sets.

While the increased demand for automation presents a huge opportunity, it will also lead to a growing amount of competition. As the competition becomes fiercer than ever, it is vital for AI businesses to take action and make sure they stand out.