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Industry Insights: CIO vision 2025 — bridging the gap between BI and AI

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The journey to retail intelligence at scale

Transforming your brand with data and AI

With more data on their customers, processes and products flowing in than ever before, managing data for use in advanced analytics is essential for retail and consumer goods organizations to keep up.

Data showed that AI leaders are most numerous in the retail and consumer goods industries

As this new survey report by MIT Technology Review Insights points out, AI and data management are essential pillars of enterprise success. In fact, the data showed that AI leaders are most numerous in the retail and consumer goods industries, indicating the industry’s ambition to become more AI-driven. 92% of survey respondents in the retail industry agreed that scaling AI and machine learning use cases to create business value is the top priority of their enterprise data strategy over the next three years, greater than almost every other industry surveyed. But the survey also found that the majority (76%) of respondents cited problems with data as a critical factor that could jeopardize their company’s future AI success.

Because of this, for most organizations, becoming AI-led is a work in progress. “We’ve been aggressive in using AI to transform the digital experiences for customers in our omnichannel network,” says Jeremy Pee, Chief Digital and Data Officer at retailer Marks & Spencer. “But we need to leverage AI to make ourselves better in every way. So, we are starting to use it in the core of how we run the business, how we make decisions, and how we put intelligence and science into that.”

Ultimately, through effective data management on a unified platform (which 78% of retailers believe is crucial to their data strategy), retail and consumer goods organizations can transform the way they operate with more engaging customer experiences, predictive supply chains, an informed product road map and more productive employees.

Case Study

Procter & Gamble

Procter & Gamble aims to automate the entire AI lifecycle to drive greater use case scale and democratize AI throughout their organization. By unifying on a single platform and lowering the barrier to entry for business employees to engage in advanced analytics, P&G can meet its ambitious goals for expanding AI use cases and generating greater value from them across sales, marketing, distribution and more.

Procter and Gamble text logo

 

“We aim to develop more and more AI use cases over the next couple of years. To do that, we need to automate the entire AI lifecycle, including data integration, model development and model maintenance. Automation will allow us to deliver more models with consistent quality while effectively managing bias and risk. Enabling the ‘democratization’ of AI involves building a set of algorithmic platforms that have intuitive front ends.”

—Vittorio Cretella, Chief Information Officer, Procter & Gamble

How to future-proof

The research points to these key attributes to instill in your data and technology foundations: openness, multicloud, democratization. An open and unified platform like the Databricks Lakehouse Platform makes it possible to scale AI efficiently — and ultimately, create business value.