Adoption of AI in Middle East may slow down due to some key challenges

Although the widespread use of artificial intelligence (AI) in business is still in its infancy and questions remain open about the pace of progress, the lack of adequate skills to support AI projects, immature market ecosystem, lack of clean data and regulatory implications are the key challenges which might slow down the adoption in the Middle East, an industry expert said.

Speaking to TechRadar Middle East, Manish Ranjan, Program Manager for software and cloud at research firm International Data Corporation (IDC), said that there are a lot of AI-centric initiatives and mega projects in various stages in the Gulf countries.

In the UAE, there is UAE AI Strategy and various AI research labs by public and private sectors (ADDA, Dewa, Huawei and Smart Dubai), and AI university.

Saudi Arabia recently unveiled a new National Centre for AI, a national AI regulator, a National Data Management Office and is already delivering its first AI college.

“Organisations, especially from government, banking and finance, retail and resource industries are increasingly leveraging AI and ML to automate and optimise their businesses and operations,” Ranjan said.

The use cases around AI is still evolving where organisations are using various sub-sets of the AI technologies such as natural language processing (NLP), image/video analytics, machine learning (ML), and other technologies to answer questions, discover insights, and provide recommendations.

Many believe there may not be a single technology that will shape our world more in the next 50 years than AI, Sam Blatteis, CEO of The MENA Catalysts, a public policy consulting firm for government innovation arms and high tech multinationals, said and added that it has rapidly evolved into the hottest area in legislation in the Gulf.

This is the first time governments around the world are simultaneously releasing national plans to develop the same field, he said.

Being a subset of AI techniques, Ranjan said that ML enables computer systems to learn from past experiences by analysing a huge amount of data and improve their behaviour for a given task.

Many global vendors have started embedding AI, ML, and cognitive applications to provide ultimate business benefits to their users.

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Lack of adequate data

In general, globally or regionally, Ranjan said that organisations are leveraging data and information (both structured and unstructured data/information) to educate their AI platforms to bring automation and improve operational efficiency—this has put data as a focal point.

“Data is instrumental for AI platforms and solutions to help the system become more intelligent by learning fast. If there is a lack of adequate and variety of data, AI would reflect a slow learning curve and the accuracy might also be impacted. The AI systems which can be able to process a vast amount of data in real-time would show greater results,” he said.

According to a survey conducted on CIOs by IDC, over 50% of organisations across the Middle East highlighted their plans to leverage cognitive and AI solutions by 2020.

“Definitely, the year 2020 would highlight some of the AI projects which were in proof of concept or sandboxing phase last year. We will see more commercial AI use cases emerging as the market matures,” Ranjan said.

According to IDC, spending on artificial intelligence systems for the UAE and Saudi Arabia combined is forecast to reach $132.3 million in 2020, witnessing an increase of 23.8% compared to 2019.

The spending in the UAE for next year is forecast to be $73.6m and $58.6m for Saudi Arabia.

  “The AI software applications and AI platforms markets continue to show steady growth in the Middle East and Africa region, and we expect this momentum to continue over the forecast period,” Ranjan said.

The top use cases of AI solutions in the UAE and Saudi Arabia are automated threat intelligence and prevention systems, automated customer service agents, IT automation, fraud analysis and investigation, defence, terrorism, investigation and government intelligence systems, and digital assistants for enterprise knowledge workers.

However, Ranjan said that even if AI matures in future, “we can still not think of complete seclusion from human intelligence. We will have bots and machines taking the workloads which would be extremely efficient and at one point almost error-free; however, we would still require human intelligence.”

“How we legislate AI will become one of the defining themes of the next five years,” the CEO of the MENA Catalysts said. “We need to set strategic ‘rules of the road’ from the start — not to over-regulate, but to provide regulatory predictability to attract expertise, ideas, and capital.”

Moreover, if the Gulf is to develop knowledge industries of the future, he said that education here must be reimagined.

“We have to think about how we can ‘hack education’ to reprogram our education system, change course and plot a new education strategy. We should be teaching physics to kindergartners, robotics and computer programming in every school,” Blatteis said.

Machine learning, deep learning and big data are some of the most highly sought-after skills in the industry.

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