Categories: Blog Content Marketing Data/Analytics Logistics Marketing Strategy Supply Chain

Supply Chain and Marketing/Sales Are AI’s First Big Opportunities for Business Use

The results are in: Artificial intelligence (AI) has significant value for many business sectors. But what are the most effective ways to apply AI to your supply chain management company?

Executives of many leading companies are looking for ways to integrate AI into their operations. A recent McKinsey & Co. study estimates that 40% of the potential value associated with data analytics today comes from techniques called “deep learning.” Deep learning refers to AI that can monitor a system and make adjustments rather than simply repeate a single task. Industry use of deep learning techniques remains relatively low as companies determine how best to use AI to meet business needs.

Supply chain management is one of the business sectors that can get the most value out of deep learning techniques. Brick-and-mortar retailers tend to see a 1-2% increase in sales revenue when they use AI to personalize promotions based on customer data analytics. Supply chain management organizations can expect to see greater benefit from AI that forecasts demand by analyzing the underlying market factors. Using AI this way can improve forecasting accuracy by 10-20%, allowing companies to reduce inventory costs by as much as 5% and generate 2-3% increased revenue.

In addition to reducing inventory costs in supply chain management organizations, deep learning can create trillions of dollars in value in marketing and sales revenue and save costs through predictive maintenance. The best way to determine how AI can serve your needs is to look at how your organization uses traditional analytics techniques: AI can often provide higher performance in conducting analytics and introduce additional layers of analysis. The technology is always improving, so the potential value for companies adopting deep learning techniques is expected to continue to rise.

There are, however, obstacles facing companies looking for ways to use AI techniques. It is essential to plan for the security and privacy issues of data analytics. Deep learning works best with large-scale datasets, which not all organizations can assemble or access. The level of expertise necessary to implement and service AI technology comes with added expenses, but determining the right way to apply AI to your organization makes these costs and challenges a rewarding investment.

Related posts:

Published by
Elizabeth Hines

Recent Posts

  • Blog
  • Logistics
  • Marketing
  • SEO

How logistics companies get recommended by ChatGPT and AI search

A shipper used to Google "3PL in Atlanta" and click through ten websites. Now they…

3 days ago
  • Blog
  • Marketing
  • Strategy
  • Supply Chain

How to choose a supply chain marketing agency: 10 questions to ask

The 10 questions to ask before hiring a supply chain marketing agency, plus red flags…

2 weeks ago
  • Blog
  • Manufacturing & Distribution
  • Marketing
  • Strategy

Manufacturing marketing: a lead generation playbook for industrial companies

A step-by-step lead generation playbook for manufacturers: ICPs, buying committees, websites that convert, SEO, paid…

2 weeks ago
  • Blog
  • Logistics
  • Marketing
  • Strategy

SEO for logistics companies: a practical guide to getting found by shippers

A practical SEO guide for 3PLs, freight brokers, and carriers: keywords, service and location pages,…

2 weeks ago
  • Blog
  • Content Marketing
  • Logistics
  • Supply Chain
  • Transportation & Trucking

The best logistics and supply chain blogs to follow in 2026

There's no shortage of supply chain content out there. The hard part is knowing which…

3 weeks ago
  • Blog
  • Content Marketing
  • Leadership
  • Logistics
  • Marketing
  • Supply Chain
  • Talent

Why CSR matters: 4 benefits of corporate social responsibility for supply chain companies

Editor's note: This post was originally published in June 2018 and has been updated for…

1 month ago