Projects to adopt AI in digital commerce are proving successful, according to Gartner.
Seventy percent of digital commerce companies report that their AI projects are either very successful or extremely successful, according to a survey of 307 companies in the sector conducted by the analyst company.
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, with the top three uses being customer segmentation; product categorization; and fraud detection.
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 $1.3 million in development for an AI project in digital commerce. However, of the more successful organisations, 52% spent less than $1 million on development, 20% spent between $1 to 2 million, and 9% spent more than $5 million.
Gartner recommends that companies in the sector that are launching AI projects should assess in-house AI talent to ensure they can develop and maintain a suitable solution, or source outside talent; create AI projects that will take less than 12 months, or where major stages can be completed in 12 months; and ensure that there is adequate funding, primarily for talent acquisition, data management and processing, as well as integration with existing infrastructure and processes. Budgets also need to include high-performance solutions.
Companies should use the minimum viable product (MVP) approach, to break down complex business problems and develop targeted solutions to drive home business outcomes. AI should be deployed to optimize existing technologies and processes rather than to try to develop breakthrough solutions.