The MENA AI Software market is expected to grow with a robust CAGR of more than 24% during the period 2019-2028. AI combines computer science with various datasets to create programs with problem-solving skills. AI can be used to perform complex tasks which require learning and memory. An AI can learn from experience and continue to improve its skills with time due to its capability to build up memory and understand advanced logic.
The cost benefits from automation, leaping advancement in deep learning leading to diverse use cases across industries, and increasing adaption of IoT technology and AI -based applications in everyday life are some major drivers fueling the growth of the AI market globally. Rising jobs in the data science, AI, and ML fields are a clear indication of the fast-growing industry. AI has gained popularity across industries such as marketing, sales, manufacturing, business management, BFSI, and others. It enables the user to boost efficiency without impacting its quality resulting in lower costs, better time management, and lesser supervisory requirements.
AI is now being used in complex processes such as surgeries. Robots have now been performing complex medical surgeries with the help of artificial intelligence which has proved to be quite a successful endeavor as they are less likely to commit errors and can calculate the potential decision that has to be taken in relevance to a given situation quickly. The retail sector is employing AI at a large scale to boost customer experience and understand customer preferences better resulting in better demand forecasting and inventory optimization which has been a boon to this sector. The unknown facet of advanced logic and intelligence in AI, AI spurred job loss, high initial investment cost and lack of expertise in terms of implementing AI solutions are the key restraints that hamper the growth of this industry.
Machine learning playing significant role for AI Software and its adoption in MENA
According to Microsoft, the most used AI technology among the surveyed companies in the Middle East and African markets is machine learning. This is due to its wide-ranging applicability, making it relevant for several use-cases across the value chain. Of the various types of machine learning, the most common is supervised machine learning, where software is fed structured data and finds patterns that can be used to understand and interpret new observations.
While companies in the region have primarily used internal data for supervised machine learning, most have now begun exploring the possibility of combining internal and external datasets to produce even deeper insights. As consumer trends and demands in the region change rapidly, companies face challenges in creating or transforming products and services tailored to current competitive landscape needs. Executives see significant value in using complex algorithms and unsupervised machine learning to assist in analyzing the diverse data sets to create high margin services for product portfolios.
The Middle East’s traditional business mindset has taken a significant detour from oil, retail, and property to IT and digital advancements. With the latest investments, strategies, and products in fields like IoT, cloud, and e-commerce, the Middle East nations have shown their intent to stay ahead in the game of technological advancements. They are ready to embrace developing technologies, such as machine learning by creating efficient plans and capital investments.
UAE is largely dominating the GCC market, with an estimated share of 54.5% in 2022, driven by heavy investment in the country’s AI sector by stakeholders
UAE leads the region in terms of AI spending due to it being the forerunner in articulating and implementing AI growth strategy in the country. The UAE has spent more than US$ 2.5 billion on AI directed mostly toward social media and IoT projects. Saudi Arabia follows closely and has pledged a US$ 2 Billion in government investment with the aim of establishing 300 AI-based startups by 2030.
Turkey is experiencing rapid growth along the same lines as the top 2 countries, with a well-articulated and dedicated AI strategy in place. Countries like Egypt, Qatar, and Kuwait are diverting their investments away from traditional oil and gas sources towards renewables utilizing smart solutions from AI to support their futuristic goals. The rest of MENA is experiencing the wave of AI software implementation in a similar way, driven by the changing economic mood and outlook in the region. However political instability and terrorism remain key threats to the economic growth, development, and AI software-enabled transformation into a data-driven economic region.
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Key Market Segmentation
Rationalstat has segmented the MENA AI Software Market on the basis of type, deployment, end user, and region.
- By Type
- AI Applications
- AI ERP
- AI CRM
- Rest of AI Apps
- AI System Infrastructure Software
- AI Platforms
- AI Applications
- By Deployment
- On-premise
- Cloud
- By End User
- Manufacturing
- Natural Resources and Material (Oil & Gas and Mining)
- Telecom, Media & Services
- Consumer Goods & Retail
- Healthcare & Life Sciences
- Automobile & Transportation
- BFSI
- Energy
- Others (Government, Trade etc.)
- By Region
- Middle East (ME)
- GCC
- Turkey
- Rest of ME
- Israel
- Iraq
- North Africa (NA)
- Egypt
- Morocco
- Algeria
- Rest of North Africa
- Middle East (ME)
Research Methodology
RationalStat has developed a state-of-the-art research methodology to crunch numbers and provide the best possible real-time insights to clients. We combine a varied range of industry experience, data analytics, and experts’ viewpoint to create a research methodology for market sizing and forecasting.
RationalStat combines a mix of secondary sources as well as primary research to assess the market size and develop a forecast. Key steps involved in accurately deriving the market numbers are:
- Defining the problem by understanding the type of market and data required by the client.
- Data gathering and collection through relevant paid databases, publicly available sources, company reports, annual reports, surveys, and interviews.
- Formulating a hypothesis to create market numbers, forecast, influencing factors, and their relevance.
- Evaluating and analyzing the data by referring to data sources utilized and leveraged.
- Validating, interpreting, and finalizing the data by combining the details gathered from primary and secondary sources with the help of experienced analysts.
Secondary Sources
- Annual reports, company filings, investor presentations, product catalogs, and company documents
- Industry and market-related documents available in the public domain
- Paid database including Bloomberg, Factiva, S&P Capital IQ, FactSet, Refinitiv Eikon, ICIS, EUWID, and Thomson Reuters, among others
- Whitepapers, research papers, and industry blogs.
Why Buy this Report?
The report is intended for AI software providers and suppliers, aviation companies, government organizations, educational organizations, regulatory agencies, and market research firms, among others. The report provides an in-depth analysis of market size, consumption patterns, ongoing market trends and challenges, and future market opportunities. The report will serve as a source for a 360-degree analysis of the market thoroughly delivering insights to clients to find the right answers to their business questions.
Frequently Asked Questions (FAQs)
The MENA AI Software market is expected to grow at a CAGR of more than 24% from 2022-2028.
Middle East (UAE leads the domestic market) is the leading region in MENA AI Software Market in 2022.
The market value of the MENA AI Software market was US$ 1.8 billion in 2022.
- Cost efficiency of automation.
- Increasing use cases of deep learning and machine learning
- Increasing popularity of IoT devices.
Leading companies operating in the MENA AI Software market are Amazon, IBM Corporation, Microsoft Corporation, Oracle Corporation, NEXTracker, Druid, Nvidia, Group 42, Palantur Technologies, Applied Artificial Intelligence Corporation, SAS Institute, Axilion Smart Mobility Ltd., Mobileye, Moovit, Appinventiv, Splash Software, Fusion Informatics Limited, etc.