Sizing The Market Value Of Artificial Intelligence

• McKinsey estimates AI techniques have the potential to create between $3.5T and $5.8T in value annually across nine business functions in 19 industries.
• AI will generate up to $2.6T additional value in Marketing and Sales and up to $2T in Supply Chain Management and Manufacturing.
• AI will add $200B in value to Pricing & Promotion and $100B to Customer Service Management in Retail.
• McKinsey predicts AI will have up to an 11.6% impact on Travel industry revenues and up to 10.2% on High Tech.
• A European trucking company reduced fuel costs by 15% using AI to optimize routing of delivery traffic, improving fuel efficiency and reducing delivery times.
• In 69% of the use cases in the study, AI and deep neural networks improved performance beyond what existing analytic techniques were able to deliver.

These and many other fascinating findings and insights are from a recent McKinsey Global Institute (MGI) Discussion Paper, Notes from the AI frontier: Applications and value of deep learning. Titled Notes from the AI Frontier: Insights From Hundreds Of Use Cases (36 pp., PDF, no opt-in) the discussion paper draws on MGI research and the firm’s applied experience with artificial intelligence (AI) of McKinsey Analytics, assessing the practical applications and the economic potential of advanced AI techniques. The discussion paper’s findings are based on intensive MGI analytics collated and integrated with more than 400 use cases across 19 industries and nine business functions.

Key takeaways from the discussion paper include the following:

• McKinsey estimates AI techniques have the potential to create between $3.5T and $5.8T in value annually across nine business functions in 19 industries. The study equates the value-add of between $3.5T to $5.8T as approximately 40% of the overall $9.5T to $15.4T annual impact that could be enabled by all analytical techniques. The following graphic compares AI’s impact in billions of dollars by Al impact as % of total impact derived from analytics.

• In 69% of the use cases in the study, AI and deep neural networks improved performance beyond what existing analytic techniques were able to deliver. Travel, Transport & Logistics, Retail  Automotive and Assembly, High Tech,  Oil & Gas and Chemicals are the industries which have above-average potential based on AI’s contributions.

• McKinsey predicts AI will have up to an 11.6% impact on Travel industry revenues and up to 10.2% on High Tech. The Insurance industry will also see AI have a significant impact on its revenues, with Retail seeing the greatest aggregate dollar impact.

• AI will generate up to $2.6T additional value in Marketing and Sales and up to $2T in Supply Chain Management and Manufacturing.McKinsey found that the greatest opportunities for AI in Marketing and Sales are in the Retail and High Tech industries. The study cites the frequent digital interactions between businesses and customers that generate larger data sets AI techniques rely on to complete analyses. The study team found that e-commerce platforms will specifically benefit as these platforms collect customer information including click data or time spent on a web page, and can then customize promotions, prices, and products for each customer dynamically and in real time.

• Customer Service Management, Pricing & Promotions, Next product to buy (NPTB) individualized offerings, Predictive Maintenance, and Yield Optimization are the functional areas AI can create the most incremental value. Additional Marketing and Sales areas where AI can contribute the most value include Customer Acquisition/Lead Generation, Churn Reduction, Channel Management and Marketing Budget Allocation. The following graphic compares the highest potential impact business problems by functional area. The relative impact of AI on each functional area is represented by the size of each area of the graphic.

• AI will add $200B in value to Pricing & Promotion and $100B to Customer Service Management in Retail. McKinsey estimates AI will increase the value of Marketing & Sales strategies by $500B ($.5T) in Retail alone. The following graphic compares the areas where AI will be making the greatest contribution to the Retail industry.

• AI will add $300B in value to Supply Chain Management (SCM) and Manufacturing and $100B in value in Marketing and Sales in Consumer Packaged Goods (CPG). AI’s greatest potential value contributions to the CPG industry’s SCM and Manufacturing operations include Predictive Maintenance, Inventory and Parts Optimization, and Yield Optimization. McKinsey predicts AI will make up to a $100B contribution to Marketing & Sales in the CPG industry.