What is the ROI on AI?

We have gathered the facts about the ROI of AI to help decision makers clarify what can be its contribution to their business profitability

When starting with an AI project, companies often wonder what will be the ROI on the initial proposal. Return on Investment (ROI) is a performance measure used to evaluate the efficiency of an investment. It is a good approach to calculate how much the overall investment would yield. We have gathered some facts about the ROI of AI to help decision makers clarify what can be the short and the long term contribution of AI to their business profitability.

Some macro figures

At a global scale, AI has the potential to deliver additional economic activity of around $13 trillion by 2030, or around 16 percent higher cumulative GDP compared with today.

Developed countries

Many developed countries could gain an additional 20 to 15 percent in net economic benefits, and could use AI to gain higher productivity growth while their overall GDP growth slows down as a result of slowly approaching steady-state.

Emerging economies

On the other hand, emerging economies, that often suffer from inefficient delivery of basic services could use AI to improve and make a significant “leap” in their infrastructures. Artificial Intelligence and Machine Learning offer the opportunity to redefine how the infrastructure of these countries could work (like finance, education and health, for example). This could accelerate the process of GDP growth without necessarily imitating the steps of mature economies.

Different countries might need to implement different strategies for AI-adoption, as the macroeconomic environment among countries vary.

Per sector

Business functions already generating ROI from AI

Lately, the benefits of incorporating Artificial Intelligence and Machine Learning are seen far beyond the IT functions. Business functions like marketing and sales, supply chain, and finance have the highest Economic Value Added(EVA) potential from implementing AI in the next 20 years.

Industries increasingly using AI

Different sectors exhibit dynamics in terms of adopting and absorbing AI, leading to different levels of growth. Accenture estimates that if companies across all industries invest in AI and in human-machine collaboration, they could boost company revenues by 38 percent by 2022. According to the research, sectors that may experience the highest rate of revenue growth by implementing AI are: consumer goods sector with 51%, health sector with 49%, telecommunications with 46% and the retail sector with 41% increase in revenue by the end of 2022. Other sectors that may benefit substantially from AI are professional services, financial services, chemical and automotive sector. Not surprisingly, data intensive industries are the ones that continue to hold the lead in implementing AI technologies.

ROI at company level

Companies that are rapidly implementing AI tools could potentially double their cash flow by the year 2030. On the other hand, companies that will not adopt AI-based solutions by 2030 might suffer from 20 percent decline in their cash flow compared to present-day levels. In other words, it is probable that AI could lead to a performance gap between companies that fully enforce AI tools across their enterprises, and companies that do not adopt AI technologies. The benefits of AI for companies can especially build up in the later years, bearing competitive advantage at the expense of companies that have limited or no adoption of the technology.

Choosing well your business case, to guarantee a high ROI

As with any technology, AI should be carefully implemented to a specific business problem or in an area with an identified opportunity. The first step in guaranteeing high ROI, is choosing well your business case. This may look obvious but is sometimes disregarded. In choosing the proper business case, it all comes down of the alignment in the company strategy and challenges. Every business is unique. Hence, it does not exist a strict step of implementing AI use cases within a company. As a company, if you are hesitating between several use cases, you can consider developing an initial AI roadmap.

Including a pilot stage

After having chosen one or several relevant use cases, the next step, for many companies, is to start with a Proof of Concept (PoC). Call it a PoC, a pilot project, a pilot programme or a pilot initiative - the name does not matter as much as the purpose, which is to get your organization started with AI. A Proof of Concept aims to explore and validate how well a particular business problem can be solved by AI. This is a good practice in order to minimize the risk and maximize the Return on Investment. The POC can be divided in 3 stages: preparation, development and validation of the AI-based project. A Proof of Concept is a best practice to guarantee high ROI on an AI project, and to ensure that the companies’ expectations are being met with the end results. If this is the case, you can deploy your AI model into production. This means that you will integrate a machine learning model into an existing production environment so it can run on a continuous or regular basis. It is one of the last stages in the machine learning life cycle You can read more about what is a Proof of Concept (and how to make the most of it) in one of our articles.

ROI on AI may increase with time

What makes Artificial Intelligence so special, is its ability to constantly learn from its own experience as more data is being processed by the model. Hence, the more data is fed to the model, the more accurate the model becomes. It’s a virtuous cycle, that can only increase the ROI over time. Meaning, your AI-based model will only become ‘smarter’ as the years go by, and will output more and more accurate predictions distributing the Return of Investment curve exponentially.

Our goal is to help companies grow even more with Artificial Intelligence. We build personalized AI-based solutions that can improve your business, and we provide consultancy services on how to start implementing AI within your organization. If you are curious to find out how AI can help grow your business, feel free to leave us a message and our team will be back with you soon! Or book a 15 min slot to discuss your challenges and potential ideas (on English, French or Dutch).


How much data is needed to build an AI solution
We explain different AI use cases and the amount of data each of these AI algorithms needs in order to be trained and work properly.Read More
Short overview of Machine Learning techniques
In this article we cover four major types of machine learning techniques, we explain their applications and help you differentiate themRead More
Difference between Data Science, Machine Learning and Artificial Intelligence
We help in understanding the difference between DS, ML and AI and when to use each of themRead More
How to start with AI?
We explain some clear steps to undertake before starting an AI project.Read More
Data sources that can be used in Artificial Intelligence
We explain the different types of data and data sources companies can leverage to implement Artificial Intelligence and improve the decision making processRead More
AI Applications in Pharma and Biotech
Over the last years, the use of Artificial Intelligence in pharma and biotech industry is redefining how scientists develop new drugs, tackle disease and moreRead More
What is a Proof of Concept (and how to make the most of it)?
We explain what is a Proof of Concept, and how can it be leveraged in order to minimize risk and maximize ROIRead More
What is Explainable AI?
Algorithms are making more decisions for us. Should we care about understanding how they come to their conclusions?Read More


The EU Focus Group on AI is launched
Kantify has been selected to be a member of this group of European AI experts who will give input into the EU policy on Artificial Intelligence.Read more
Kantify joins the European Commission / Digital SME Focus Group on Artificial Intelligence
Kantify is an official member of the Group that will monitor the progress of AI technology and regulations in EuropeRead more
Trophées Montaigne 2020 : Our CEO wins the Trophée ‘Enterprise'
Our CEO Ségolène Martin was awarded the Trophy Montaigne for the category ‘Enterprise'.Read more