According the report, Application of BlockChain Along with A.I. has Increasingly Practiced by the Major Players in the Industry is one of the primary growth factors for the market. A.I. Help in Reducing and Optimizing the Operational and Shipping Cost is also expected to contribute significantly to the Artificial Intelligence in Supply Chain market. Overall, Operational Procurement applications of Artificial Intelligence in Supply Chain, and the growing awareness of them, is what makes this segment of the industry important to its overall growth.

AMA’s Analyst on the Global Artificial Intelligence in Supply Chain market identified that the demand is rising in many different parts of the world as "Autonomous Vehicles is one of the Biggest Opportunities of the Decade Due to Intense Research and Development as well as Investments in this Field ". Furthermore, some recent industry insights like "In 2021, Google, Global tech and A.I. giant has announced a strategic alliance with J.B. Hunt Transport Services, Inc., the market leader in transportation logistics in North America. The two signed a strategic alliance to accelerate next and innovate in the next generate digital supply chain platform. Both the companies look at combining their synergies and expertise through their innovative products such as Google's Data Cloud, and J.B. Hunt 360. The two companies look at enabling A.I., and Machine learning tools to enhance logistics and supply chain management." is constantly making the industry dynamic. One of the challenges that industry facing is "Lack of Trust in A.I. Due to Inexperience of Human Expertise in A.I., High Initial Cost of Setup, Lack of Experts or Skilled Professionals in Industry who can Operate A.I. Enabled Systems or Mechanisms or Tools in Supply Chain, A.I. is still in its Embryo Stage and is Evolving and Difficulties in Understanding and Application of Complex Algorithms with Different Set of Objectives"

The End Users, such as Retail, is boosting the Artificial Intelligence in Supply Chain market. Additionally, the rising demand from SMEs and various industry verticals, macro-economic growth are the prime factors driving the growth of the market.

The Technology, such as Machine Learning (MP), is boosting the Artificial Intelligence in Supply Chain market. Additionally, the rising demand from SMEs and various industry verticals, macro-economic growth are the prime factors driving the growth of the market.

The Offerings, such as Software, is boosting the Artificial Intelligence in Supply Chain market. Additionally, the rising demand from SMEs and various industry verticals, macro-economic growth are the prime factors driving the growth of the market.

The report provides an in-depth analysis and forecast about the industry covering the following key features:
o Industry outlook including current and future market trends, drivers, restraints, and emerging technologies
o Analyses the Global Artificial Intelligence in Supply Chain market according to Type, Application, and regions
o Analyzes the top 10 players in terms of market reach, business strategy, and business focus
o Provides stakeholders’ insights and key drivers & trends of the market

Market Size Estimation
In market engineering method, both top-down and bottom-up approaches have been used, along with various data triangulation process, to predict and validate the market size of the Artificial Intelligence in Supply Chain market and other related sub-markets covered in the study.

o Key & emerging players in the Artificial Intelligence in Supply Chain market have been observed through secondary research.
o The industry’s supply chain and overall market size, in terms of value, have been derived through primary and secondary research processes.
o All percentage shares, splits, and breakdowns have been determined using secondary sources and verified through primary sources.

Data Triangulation
The overall Artificial Intelligence in Supply Chain market size is calculated using market estimation process, the Artificial Intelligence in Supply Chain market was further split into various segments and sub-segments. To complete the overall market engineering and arriving at the exact statistics for all segments and sub-segments, the market breakdown and data triangulation procedures have been utilized, wherever applicable. The data have been triangulated by studying various influencing factors and trends identified from both demand and supply sides of various applications involved in the study. Along with this, the Global Artificial Intelligence in Supply Chain market size has been validated using both top-down and bottom-up approaches.