The ROI of AI. How to Understand the Commercial Dimension of Artificial Intelligence Projects?

The ROI of AI. How to Understand the Commercial Dimension of Artificial Intelligence Projects?

Patricia Kosterski - May 7, 2021

Artificial Intelligence is taking over almost every industry – companies want to experiment with the possibilities of AI to bring additional value to their product or service. Data from Accenture’s research says that in the upcoming year, more than 65% of companies plan to invest in AI – it’s obvious considering the fact that in some industries, AI will help boost revenue by 30%. But it might be very challenging to get a predictable and positive ROI from AI projects. Research by Capgemini says that only 27% of data-related projects can be considered successful, and up to 85% of AI projects fall without bringing the expected value. That’s why in this article, we would like to make it easier for you and to present the battle-tested list of activities and theories which will help you to get ROI from your AI projects.

What is AI? How to understand the ROI of artificial intelligence projects?

In the beginning, it might be essential to talk about some definitions because many companies consider every data-based project as an AI solution, but this is not working this way. Definition provided by Oxford dictionary explains that AI is “the theory and development of computer systems able to perform tasks normally requiring human intelligence, such as visual perception, speech recognition, decision-making, and translation between languages.” Those activities can be used in many ways to improve multiple areas in almost every company – that’s why business leaders are so excited about AI initiatives. But on the other side, as applying AI solutions at the production level is still relatively new and full of experiments, it might be hard to have a clear vision of ROI.

ROI, or Return on Investment, measures the gain/loss generated by an investment concerning its initial cost. ROI allows us to assess the efficiency and profitability of expenditure and is often used to influence financial decisions, compare a company’s profitability, and analyze investments. Return of Investments in Artificial Intelligence projects can be seen from many different angles, not only as a pure profit in cash. As the survey made by Deloitte says, the top areas where data science projects deliver value include:

  • customer experience and service
  • streamlining processes with automation
  • IT operations and infrastructure
  • planning and decision making
  • building insights and predictions

In what ways can a company benefit from the AI implementation? The same report says that usually, data science implementations deliver value in:

  • higher productivity (for example, by removing repetitive tasks),
  • lower operation costs,
  • increased customer satisfaction and retention,
  • improved employee engagement,
  • improved profitability,
  • resilience in changing environments (predictive and prescriptive data analytics)
  • new products and services.

As previously said, the average expected ROI can reach up to 30% in upcoming years. Still, the average ROI of AI investments is 4,3% (in the case of leaders of the market) and 0,2% in organizations that just started their first AI project. The average time of payback is from 1,2 to 1,6 years.

How to turn AI into a profitable investment?

Although planning the ROI from AI might be challenging, as there is a lot of factors, changes, and experiments, there is a set of rules which can be very useful in predictions:

1. Define needs, business value and set up the goals

Every business has its own characteristics and needs. That’s why the implementation of machine learning should be tailor-made. Find your pain points and define a business case for AI at your organization. You should know what the goal of this implementation is and what your KPIs will be. Also, a method of measurement should be precise.

2. Plan the funding

Like every investment, AI needs funds for implementation, monitoring, and optimization. It would help if you predicted all the costs that your project can take in the time – like costs of tools, technology, team, etc. This is one of the most important factors because as much you will need to invest as high your return should be

3. Verify the skills of your team

Usually, AI applications are more complex, which means you might need additional skills in your team. Your employees might need additional training, the development of new skills, or simply new team members. McKinsey’s study says that more than 30% of employees might need to learn some new skills or change their job in upcoming years.

It is crucial to create a culture of self-development in the company from the very start. If you don’t have an IT department experienced in building and deploying machine learning models, you should consider outsourcing. Think about hiring a team with data scientists, ML experts, MLOps, and managers experienced with AI tech.

4. Plan your data strategy

The more data you will get from your AI product, the better your ML algorithms will be, and you will have more possibilities to optimize it. More than 52% of people surveyed by The Pistoia Alliance stated that the lack of data is their biggest fear in developing AI systems. Without the possibility of taking the data from your AI project, you will not measure ROI.

5. Choose the right technology

AI implementation should always be an answer to the existing problem. If you know what your issues are, you can verify different technologies available on the market. This will give you an overview and check if the development of these solutions with other technologies will not be a better option.

6. Test it before scaling

You might need to verify your ideas before final development. This approach will help you reduce costs – for example, when the technology will fail.

How to reduce the risk of investment in machine learning?

There are ways to reduce the risk of not getting value from AI-based applications. Both are based on a deep understanding of the needs of the projects and the possibilities of current AI technologies. Read more about it here.

AI Design Sprint

It is our own approach to AI development. AI Design Sprint is a hands-on experience where, together, we identify potential AI use-cases for your business and explore the business opportunities available to you. We have created a set of tools for each step of the design-thinking process to help our clients look deeper into their data and processes and turn AI into social, user, and business value. Within just two days, the client team, supported by our AI Engineers and Design Facilitators, learns and understands the power of emerging technologies, spots AI opportunities, and creates new ideas and visions. You can find more detailed information on the AI Design Sprint here.

AI Proof of Concept

Creating the proof of concept can be a perfect way to demonstrate the business value for all the stakeholders and decision-makers. In this approach, you don’t need to develop the whole project but verify your idea and the idea possibilities on a tight budget and in a short time. It might also have a limited amount of features, but enough to prove that the final project will work and bring the expected value. For AI development, it is crucial to embrace the culture of the iterative experiments. Each experiment focuses on evaluating data haves and the creation of an AI model. AI Proof of Concept helps consider the benchmarks and the possibilities of a full-grown model working with new data at scale. It lets you decide at an early stage whether AI on production would give you the desired value and is worth the investment.

How to measure the ROI of AI?

It might be very challenging to develop internal standards, goals, and KPIs inside your AI project. We want to put your focus on a few crucial factors:

Costs – as previously said, building a custom AI system is almost always a significant investment. You need to invest your resources to bring you profit. High costs of development will influence your ROI. Don’t forget about including the costs of team, licenses, security, platforms, algorithm, model design, data, etc.

Savings – this might be one of the most important ways to measure the ROI of AI. Sometimes the AI project can bring you profit in reduced costs of your company’s daily activities instead of a pure income in cash.

Soft profits – not only profits or savings can be the benefit of a machine learning project. With the support of AI, you can improve your company in countless areas like, for example, productivity, product quality, customer satisfaction, and this can lead your company to increased profits later.

Goals and KPIs – try to predict the purpose of your project, especially from the financial perspective. We suggest you think about the point in time when your investment in the AI project will be equal to your benefits from it.

Future profits – very often, the implementation of AI in the company generates a new revenue stream, so you should also consider them before predicting the ROI of AI investment.


For sure, Artificial Intelligence will influence our businesses in upcoming years. Companies want to invest their cash in AI development to bring revenue for them or make some areas of their work much better. But there is no guarantee that a custom AI software will get this expected value or the total cost will not be too high to handle. That is why a detailed planning phase and an iterative approach are crucial in every project with AI. Only in this way will you be able to predict the cost, income, and break-even points of your development. To move forward, we should seek for business people to pay closer attention to understanding data science and AI, getting more active in the current, quite a lively AI discussion. Their contribution in areas like refined commercial and business models and tactics can help companies gain more competitiveness from AI. A more multifaceted conversation on the subject would help all of us address AI as a multidisciplinary question outside the silo of software development and data science. Increasing interest from C-level executives and managers in AI capabilities will result in better dialogue around delivering value and commercial aspects of AI and the true success of future AI endeavors.


Financial Analysis Dictionary | InvestingAnswers

About the author

Patricia Kosterski

Patricia Kosterski

Business Development Specialist

Linkedin profile

Patricia's focus is on building client relationships and cooperation potential to grow revenue streams. Patricia also operates along with the marketing team on demystifying the term AI.
She specializes in working closely with clients and developing new opportunities through prospecting, networking, and relationship management—her favorite thing about her job: working on client AI-based projects that will help them do better business.

This article is a part of

Becoming AI Driven
92 articles

Becoming AI Driven

Artificial Intelligence solutions are becoming the next competitive edge for many companies within various industries. How do you know if your company should invest time into emerging tech? How to discover and benefit from AI opportunities? How to run AI projects?

Follow our article series to learn how to get on a path towards AI adoption. Join us as we explore the benefits and challenges that come with AI implementation and guide business leaders in creating AI-based companies.

check it out

Becoming AI Driven

Insights on practical AI applications just one click away

Sign up for our newsletter and don't miss out on the latest insights, trends and innovations from this sector.


Thanks for joining the newsletter

Check your inbox for the confirmation email & enjoy the read!

This site uses cookies for analytical purposes.

Accept Privacy Policy

In the interests of your safety and to implement the principle of lawful, reliable and transparent processing of your personal data when using our services, we developed this document called the Privacy Policy. This document regulates the processing and protection of Users’ personal data in connection with their use of the Website and has been prepared by Nexocode.

To ensure the protection of Users' personal data, Nexocode applies appropriate organizational and technical solutions to prevent privacy breaches. Nexocode implements measures to ensure security at the level which ensures compliance with applicable Polish and European laws such as:

  1. Regulation (EU) 2016/679 of the European Parliament and of the Council of 27 April 2016 on the protection of natural persons with regard to the processing of personal data and on the free movement of such data, and repealing Directive 95/46/EC (General Data Protection Regulation) (published in the Official Journal of the European Union L 119, p 1); Act of 10 May 2018 on personal data protection (published in the Journal of Laws of 2018, item 1000);
  2. Act of 18 July 2002 on providing services by electronic means;
  3. Telecommunications Law of 16 July 2004.

The Website is secured by the SSL protocol, which provides secure data transmission on the Internet.

1. Definitions

  1. User – a person that uses the Website, i.e. a natural person with full legal capacity, a legal person, or an organizational unit which is not a legal person to which specific provisions grant legal capacity.
  2. Nexocode – NEXOCODE sp. z o.o. with its registered office in Kraków, ul. Wadowicka 7, 30-347 Kraków, entered into the Register of Entrepreneurs of the National Court Register kept by the District Court for Kraków-Śródmieście in Kraków, 11th Commercial Department of the National Court Register, under the KRS number: 0000686992, NIP: 6762533324.
  3. Website – website run by Nexocode, at the URL: whose content is available to authorized persons.
  4. Cookies – small files saved by the server on the User's computer, which the server can read when when the website is accessed from the computer.
  5. SSL protocol – a special standard for transmitting data on the Internet which unlike ordinary methods of data transmission encrypts data transmission.
  6. System log – the information that the User's computer transmits to the server which may contain various data (e.g. the user’s IP number), allowing to determine the approximate location where the connection came from.
  7. IP address – individual number which is usually assigned to every computer connected to the Internet. The IP number can be permanently associated with the computer (static) or assigned to a given connection (dynamic).
  8. GDPR – Regulation 2016/679 of the European Parliament and of the Council of 27 April 2016 on the protection of individuals regarding the processing of personal data and onthe free transmission of such data, repealing Directive 95/46 / EC (General Data Protection Regulation).
  9. Personal data – information about an identified or identifiable natural person ("data subject"). An identifiable natural person is a person who can be directly or indirectly identified, in particular on the basis of identifiers such as name, identification number, location data, online identifiers or one or more specific factors determining the physical, physiological, genetic, mental, economic, cultural or social identity of a natural person.
  10. Processing – any operations performed on personal data, such as collecting, recording, storing, developing, modifying, sharing, and deleting, especially when performed in IT systems.

2. Cookies

The Website is secured by the SSL protocol, which provides secure data transmission on the Internet. The Website, in accordance with art. 173 of the Telecommunications Act of 16 July 2004 of the Republic of Poland, uses Cookies, i.e. data, in particular text files, stored on the User's end device.
Cookies are used to:

  1. improve user experience and facilitate navigation on the site;
  2. help to identify returning Users who access the website using the device on which Cookies were saved;
  3. creating statistics which help to understand how the Users use websites, which allows to improve their structure and content;
  4. adjusting the content of the Website pages to specific User’s preferences and optimizing the websites website experience to the each User's individual needs.

Cookies usually contain the name of the website from which they originate, their storage time on the end device and a unique number. On our Website, we use the following types of Cookies:

  • "Session" – cookie files stored on the User's end device until the Uses logs out, leaves the website or turns off the web browser;
  • "Persistent" – cookie files stored on the User's end device for the time specified in the Cookie file parameters or until they are deleted by the User;
  • "Performance" – cookies used specifically for gathering data on how visitors use a website to measure the performance of a website;
  • "Strictly necessary" – essential for browsing the website and using its features, such as accessing secure areas of the site;
  • "Functional" – cookies enabling remembering the settings selected by the User and personalizing the User interface;
  • "First-party" – cookies stored by the Website;
  • "Third-party" – cookies derived from a website other than the Website;
  • "Facebook cookies" – You should read Facebook cookies policy:
  • "Other Google cookies" – Refer to Google cookie policy:

3. How System Logs work on the Website

User's activity on the Website, including the User’s Personal Data, is recorded in System Logs. The information collected in the Logs is processed primarily for purposes related to the provision of services, i.e. for the purposes of:

  • analytics – to improve the quality of services provided by us as part of the Website and adapt its functionalities to the needs of the Users. The legal basis for processing in this case is the legitimate interest of Nexocode consisting in analyzing Users' activities and their preferences;
  • fraud detection, identification and countering threats to stability and correct operation of the Website.

4. Cookie mechanism on the Website

Our site uses basic cookies that facilitate the use of its resources. Cookies contain useful information and are stored on the User's computer – our server can read them when connecting to this computer again. Most web browsers allow cookies to be stored on the User's end device by default. Each User can change their Cookie settings in the web browser settings menu: Google ChromeOpen the menu (click the three-dot icon in the upper right corner), Settings > Advanced. In the "Privacy and security" section, click the Content Settings button. In the "Cookies and site date" section you can change the following Cookie settings:

  • Deleting cookies,
  • Blocking cookies by default,
  • Default permission for cookies,
  • Saving Cookies and website data by default and clearing them when the browser is closed,
  • Specifying exceptions for Cookies for specific websites or domains

Internet Explorer 6.0 and 7.0
From the browser menu (upper right corner): Tools > Internet Options > Privacy, click the Sites button. Use the slider to set the desired level, confirm the change with the OK button.

Mozilla Firefox
browser menu: Tools > Options > Privacy and security. Activate the “Custom” field. From there, you can check a relevant field to decide whether or not to accept cookies.

Open the browser’s settings menu: Go to the Advanced section > Site Settings > Cookies and site data. From there, adjust the setting: Allow sites to save and read cookie data

In the Safari drop-down menu, select Preferences and click the Security icon.From there, select the desired security level in the "Accept cookies" area.

Disabling Cookies in your browser does not deprive you of access to the resources of the Website. Web browsers, by default, allow storing Cookies on the User's end device. Website Users can freely adjust cookie settings. The web browser allows you to delete cookies. It is also possible to automatically block cookies. Detailed information on this subject is provided in the help or documentation of the specific web browser used by the User. The User can decide not to receive Cookies by changing browser settings. However, disabling Cookies necessary for authentication, security or remembering User preferences may impact user experience, or even make the Website unusable.

5. Additional information

External links may be placed on the Website enabling Users to directly reach other website. Also, while using the Website, cookies may also be placed on the User’s device from other entities, in particular from third parties such as Google, in order to enable the use the functionalities of the Website integrated with these third parties. Each of such providers sets out the rules for the use of cookies in their privacy policy, so for security reasons we recommend that you read the privacy policy document before using these pages. We reserve the right to change this privacy policy at any time by publishing an updated version on our Website. After making the change, the privacy policy will be published on the page with a new date. For more information on the conditions of providing services, in particular the rules of using the Website, contracting, as well as the conditions of accessing content and using the Website, please refer to the the Website’s Terms and Conditions.

Nexocode Team


Want to unlock the full potential of Artificial Intelligence technology?

Download our ebook and learn how to drive AI adoption in your business.