Artificial intelligence (AI) is the ability of a computer or a computer-controlled robotic system to do activities that usually require human intelligence and judgment, such as speech recognition, learning & problem solving, and planning.
Machine learning is a type of data analysis that automates the creation of analytical models. Machine learning is a field computer-based artificial intelligence that can learn from data, recognize patterns, and make judgments with little or no human ability. Advanced machine learning technology is used by businesses to improve their customer experience, services, and budgets. It offers process automation solutions that can replace regular manual labor. AI and advanced machine learning help reduce credit default scams by monitoring transactions and identifying suspicious transactions with compliance issues.
Market Scope and Structure Analysis
Description
End users are increasingly focusing on customized financial services owning to rise in chatbot usage across banks and increased rivalry among BFSI enterprises for market share. Various BFSI companies offer machine learning-based budget management applications. This helps clients in meeting their financial goals and improving their money management process, hence boosting market development. Furthermore, robo-advisors are a significant trend in customized financial services because they are designed to manage money for investors with limited resources, such as individuals and small and medium-sized businesses. Traditional data processing techniques are used by machine learning-based robo-advisors to develop financial portfolios and solutions for their clients, such as trading, investments, and retirement plans. Similarly, with the advent of usage-based insurance, machine learning and AI technologies are assisting in calculating the premium that is appropriate for each individual. These factors are driving the growth of AI and advanced machine learning in the BFSI market.
COVID-19 Impact analysis
- The COVID-19 pandemic ceased the production of various products in the artificial intelligence and machine learning industry, which is attributed to the global lockdown. This has hampered the growth of artificial intelligence and machine learning market from the last few months and is likely to continue through 2022.
- COVID-19 affected the sales of artificial intelligence and machine learning in the first quarter of 2022 and is anticipated to cause a negative impact on the market growth throughout the year.
- The major demand for artificial intelligence and machine learning was previously noticed from giant manufacturing countries, such as North America, Europe, Asia-Pacific, and South America, which are negatively affected by the spread of the coronavirus.
- Further, potential impact of the lockdown is currently vague and financial recovery of companies is totally based on their cash reserves. Artificial intelligence and machine learning manufacturers can afford a full lockdown only for a few months, after which the players have to modify their investment plans. For instance, various players in the market halted their production activities for several weeks to reduce their expenses. On the contrary, few players adopted employee lay-offs to sustain themselves during the COVID-19 health crisis.
- Artificial intelligence and machine learning manufacturers are expected to focus on protecting their workforce, operations, and supply chains to respond to immediate crises and find new ways of working after COVID-19. For instance, provision of sanitizers, maintaining social distance, and ensuring the vaccination of every employee in the company can assist in promoting the health & safety of the workforce.
Top Impacting Factors
AI solutions and services are being adopted and machine learning is facilitated for a variety of reasons, including the expansion of database-driven AI, advances in deep learning, and need to acquire robot autonomy to stay competitive in the global market. The robotics industry is transforming as a result of AI, computer vision, and machine learning. To stay ahead of the global market, firms began to develop completely autonomous robots that can interact, sense, and conceive the environment around them. Artificial networks are used in deep learning models to handle various amounts of data, such as texts, photos, and sounds, to provide correct analysis. AI-driven automation proves to be beneficial in a variety of areas, including agriculture, aviation, energy, medicine, and material handling. Artificial intelligence is used to automate operations, diagnose equipment failures, and detect product irregularities.Furthermore, increase in applications and simple deployment techniques drew governments' attention to AI technology, resulting in increased government expenditures in AI and related technologies.
- In August 2021, the U.S. Government committed more than $1 billion to fund for AI and quantum information science research laboratories. Similarly, in March 2021, the Canadian Government announced $518 million to expand its innovative technology research infrastructure.
- In January 2022, Amazon Elastic Container Service launched new clusters and task definition creation procedures. Users are expected to take advantage of the new streamlined processes, which include customizable default settings and the ability to configure features for container applications. The new task definition creates advanced experience by removing complexity of application. It further offers customizable defaults and automatically defines the responsibilities required to perform tasks.
- In December 2021, FICO and Sistemas Criticos launched BSafe Platform SaaS. It combines fraud prevention technology from FICO, Falcon Fraud Manager and TenS. It is a real-time solution that integrates artificial intelligence and predictive analytics to deliver complete fraud prevention, security, and compliance management with an emphasis on the customer lifecycle. This best-in-class technology is already being utilized by a number of businesses across the world to assist them to decrease fraud risk.
Key Benefits of the Report
- This study presents the analytical depiction of the artificial intelligence and machine learning industry along with the current trends and future estimations to determine the future investment pockets.
- The report presents detailed information related to key drivers, restraints, opportunities, and market share of artificial intelligence and machine learning.
- A quantitative analysis highlights the artificial intelligence and machine learning growth scenario.
- Porter’s five forces analysis illustrates the potency of buyers & suppliers in the market.
- The report provides a detailed artificial intelligence and machine learning analysis based on competitive intensity and how the competition will take shape in coming years.
Key Market Segments
- By Component
- By Deployment Model
- By Enterprise Size
- By Industry Vertical
- BFSI
- Healthcare and Life Sciences
- Retail
- IT and Telecommunications
- Government and Defense
- Manufacturing
- Energy and Utilities
- Others
- By Region
- North America
- Europe
- France
- Germany
- Italy
- Spain
- UK
- Russia
- Rest of Europe
- Asia-Pacific
- China
- Japan
- India
- South Korea
- Australia
- Rest of Asia-Pacific
- LAMEA
- Latin America
- Middle East
- Africa
Key Market Players
- Alyuda
- Qualcomm
- Microsoft
- GMDH, LLC
- Intel
- Ward Systems
- Oracle
- Google
- IBM
- Starmind