Glossary term

Composite AI

The growth of the artificial intelligence industry is undeniable. In 2021, Gartner predicted that the global market would top $62 billion by the end of 2022.  

AI has endless business applications—proven by the fact that nearly 40% of organizations are already using it in some form or another. But, day by day, business problems are only getting more complex, requiring innovative new techniques that can rise to the challenge. 

Enter: Composite AI

In this post, we’ll break down what composite AI is, how it works, and what benefits it provides to businesses that leverage it. 

What Is Composite AI? 

Composite AI refers to the combination of various AI technologies. Traditional AI is a broad sector of machine intelligence and has a wide range of applications, including automation, predictive analytics, machine learning, natural language processing (NLP), and so on.  

In many cases, businesses need to decide which AI applications best fit their use case and how to integrate multiple types of AI for the best outcome. This is where composite AI comes into play. 

Gartner’s 2022 Hype Cycle for Artificial Intelligence puts composite AI in the “innovation trigger” category and has listed it as one of seven techniques expected to see “transformational” benefit in the next 2-5 years. The report cites composite AI’s ability to combine different AI techniques to achieve better results and states that it brings the power of AI to more organizations and helps expand AI applications’ scope. 

Composite AI is on Gartner’s radar, and it should be on yours, too. By embracing this technique, enterprises can build strategies that support the hyper-growth and innovation driving the modern business landscape.  

How Does Composite AI Work? 

Composite AI is not one unique combination of AI techniques, but rather an approach to understanding how an organization can benefit from layering various AI technologies. With the varied applications of AI available, finding a solution for a business is rarely choosing a single strategy. Instead, the best business solutions often require a combination of relevant AI strategies.  

Let’s take, for example, a retail organization seeking to maintain competitive pricing and respond to consumer trends and demands in real-time. Their solution may be to use a combination of predictive models and forecasting techniques to anticipate consumer demand and trends, optimize future pricing, and maintain an edge over competitors. 

Clearly, composite AI allows businesses to level up how they’re using their data. So, how can you make a plan to use composite AI at your organization? 

The Benefits of Composite AI for Business  

Enterprises can use composite AI in countless ways—combining AI techniques is much more effective than relying on just one. A few key benefits include: 

Besides the general advantages that can be reaped across industries, there are specific advantages for each sector as well.  To illustrate this, we’ve laid out examples of composite AI’s impact in financial institutions and manufacturing. 

Financial Services 

By leveraging composite AI, financial services institutions will find they can work with sensitive data faster and more accurately. A few more benefits include: 


Manufacturing is another key area where composite AI is making strides. Here are a few key examples of its potential use cases: 

Wrapping Up 

Composite AI opens up a ton of possibilities for your organization to leverage advanced AI techniques. With the power to combine ML, image recognition, deep learning, NLP, and more with (essentially) no dataset size limits, the world is your oyster. 

But, there’s still one thing missing. How do you best leverage your team’s human expertise to complement data-driven insights? 

We’ve got a few pointers. Check out our blog post, How to Bring Data Science Closer to Your Business, to get some tips on upskilling your workforce so that composite AI (and data science in general!) can effectively spread throughout your organization. 

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