Survey finds AI projects in digital commerce are successful

Gartner conducted a survey of 307 digital commerce organisations that are currently using or piloting AI to understand the adoption, value, success and challenges of AI in digital commerce. Respondents included organisations in the US, Canada, Brazil, France, Germany, the UK, Australia, New Zealand, India and China.

Three-quarters of respondents said they are seeing double-digit improvements in the outcomes they measure. The most common metrics used to measure the business impact of AI are customer satisfaction, revenue and cost reduction. For customer satisfaction, revenue and cost reduction specifically, respondents cited improvements of 19%, 15% and 15%, respectively.

Gartner predicts that by 2020, AI will be used by at least 60% of digital commerce organisations and that 30% of digital commerce revenue growth will be attributable to AI technologies.

“Digital commerce is fertile ground for AI technologies, thanks to an abundance of multidimensional data in both customer-facing and back-office operations,” said Sandy Shen, research director at Gartner.

The survey found a wide range of applications for AI in digital commerce.
The top three uses are:

1. Customer segmentation;
2. Product categorisation; and

3. Fraud detection.
   

Top challenges

Despite early success, digital commerce organisations face significant challenges implementing AI. The survey shows that a lack of quality training data (29%) and in-house skills (27%) are the top challenges in deploying AI in digital commerce. AI skills are scarce and many organisations don’t have such skills in-house and will have to hire from outside or seek help from external partners.

On average, 43% of respondents chose to custom-build the solutions developed in-house or by a service provider. In comparison, 63% of the more successful organisations are leveraging a commercial AI solution.
“Solutions of proven performance can give you higher assurance as those have been tested in multiple deployments, and there is a dedicated team maintaining and improving the model,” said Shen.

“Organisations looking to implement AI in digital commerce need to start simple,” said Shen. “Many have high expectations for AI and set multiple business objectives for a single project, making it too complex to deliver high performance. Many also run AI projects for more than 12 months, meaning they are unable to quickly apply lessons learned from one project to another.”

On average, respondents spent $1.3m in development for an AI project in digital commerce. However, of the more successful organisations, 52% spent less than $1m on development, 20% spent between $1-2m, and 9% spent more than $5m.

To increase the likelihood of success, Gartner advises digital commerce leaders to:

Assess talent. If there is insufficient AI talent in-house to develop and maintain a high-performance solution, go with a commercial solution of proven performance.

Aim for under 12 months for a single AI project. Divide larger projects into phases and aim for under 12 months for the first phase, from planning, development and integration to complete launch.

Ensure enough funding. Allocate the majority of the budget to talent acquisition, data management and processing, as well as integration with existing infrastructure and processes. Enough funding also helps secure high-performance solutions.

Use the minimum viable product approach. Break down complex business problems and develop targeted solutions to drive home business outcomes. Use AI to optimise existing technologies and processes rather than to try to develop breakthrough solutions.