Metrics for Measuring the Business Impact for AI


Taking stock of AI ROI can be quite challenging but equally crucial. Various industry observers and IT observers lend their insights on how to get a clear picture of whether the Artificial Intelligence (AI) efforts are in fact paying off.

At present, AI is in transitional phase, both as a technology and in how it is being used. Organizations are increasingly deploying AI pilots at scale, and some are seeing excellent benefits as a result. Irrespective of the uncertainty surrounding AI, there is a risk that organizations following the traditional methods may start losing out.

But how can one know if an AI project will sabotage or help a company? Without the real ROI numbers, organizations have to find ways to know for certain. Read on to understand the metrics we can use to measure the impact of AI.

How to Measure the Business Impact of AI

Assessing the business value of any technology or initiative is not always a linear calculation. AI is no exception, particularly when degrees of maturity and business potential have to be taken into consideration. Following are the ways to measure the business impact of AI:

AI Measurement and its Spheres of Influence

When there is no direct way to assess the business impact of an AI project, organizations mine data from the related key performance indicators (KPIs). These proxy variables typically relate to business objectives and can include time to market, customer satisfaction,  or employee retention rates.

Focus on Business Benefits

Measuring the success of AI can be subjective as well. Assessing an AI project is an art as much as developing the AI itself, states Eugenio Zuccarelli – an AI research scientist at MIT who also works as a data scientist within the retail industry. Still, it is crucial to be able to describe the impact that AI is having on the business, Zuccarelli says. KPIs should revolve around the business and people metrics, which should be the end objectives of the project. Otherwise, it can be too easy to pick a technical metric that seems to show success but, in reality, would not translate to an effective impact on the company.

Measuring Success Incrementally

Automation that results in cost reduction is the easiest way to display the economic benefits of AI, states Sanjay Srivastava. He is the chief digital strategist of Genpact, a global professional services firm. But AI can also simplify new revenue streams, or also transform a company’s business model. For example, with AI, an aircraft engine manufacturer sees that it can get better at forecasting failures and enhancing logistics so it can start offering engines as a service. For the ultimate consumer, it is better to buy miles flown than the engine itself,” he says. This is a new business model. It changes the way a company operates because AI enables it.

Alignment with Strategic Vision 

One always has to be aware of the reality that some AI projects cannot offer any benefits in the short term, but are still important in the long term. For example, a company that rolls out a customer service chatbot can eliminate mundane tasks. But chatbots can be harmful because some employees are good at upselling and want to engage with people,” states Gartner analyst Whit Andrews. “So, the organization might not want that.” It boils down to the kind of company you want to be.


Pushing an AI initiative into production before it is ready, or expanding an AI strategy beyond an initial phase before vetting its results can cost can be detrimental to the business. Proven variables such as data mining, investment, cost and training savings and the ability to facilitate new uses — influence decisions when it comes to acceptable ROI. However, trusting the technology, no matter how new or established, is essential.