The Artificial Intelligence Revolution in the Digital Era

Artificial intelligence has long been limited to university research projects and technology research and development centers. But in recent years, the inclusion of AI elements in smartphones and online services has begun to spread AI already at the corporate level and is used to improve its internal and external services. Global spending on AI is expected to reach $ 52.24 billion in 2021.

The Middle East, Turkey and Africa are often at the forefront of innovation related to technologies such as mobile phones, the Internet of Things, and Blockchain. Similarly, governments and institutions across the region are adopting artificial intelligence as they look to provide new services and improve efficiency. For example, AI is at the heart of the transformation aspirations of the Kingdom's Vision 2030 initiative, while the UAE has developed the UAE's AI strategy to keep up with the government's aspiration to provide a better quality of life.

AI evokes a new wave of transformation across sectors, fostering demand for new skill sets, guiding dialogue on governance and ethics, and institutions need to identify the most appropriate locations in their operations to use AI, and identify the outcomes they aspire to achieve.

Overview

Over the past year, there has been much discussion and discussion on the use of AI at the global and regional levels. These discussions usually related to new types of research using AI, the successful use of AI to achieve practical results, the potential loss of professional functions due to it, and the subject of machine replacements for humans on an unprecedented scale. These discussions are mainly motivated by the fact that AI is no longer a concept limited to research centers as this technology is increasingly spreading to the level of consumer and corporate services.

What is artificial intelligence?

Artificial intelligence can simply be defined as activities dedicated to making machines intelligent. Artificial intelligence / cognitive intelligence can be defined as “ learnable systems and the use of logic and self-correction . The system assumes possible answers and shapes them based on the available evidence .

Artificial intelligence is already being used in many technology, e-commerce and social media companies to either provide new services or improve their existing services. For example, smart digital PDAs such as Apple's Siri, Amazon's Alexa, Microsoft's Cortana, and OK Google are included in a variety of Of devices and systems. Other examples of current use of AI include facial recognition when uploading an image on social media sites, recommending products on e-commerce sites, spam protection in postal systems, and even identifying the best ways for motorists during peak hours.

There are many factors driving institutions to use AI in many industries, including:

• Accelerated data growth: Global data is expected to reach 163 zetabytes by 2025, up from 16 zetabytes a year, and there is an increasing need to understand and analyze these data for strategic results or immediate decision-making. The use of artificial intelligence will allow companies to analyze and manage their data faster, with the possibility of repeating the process several times and with minimal human effort. This data can also be used to train AI systems to provide improved results / services, or for organizations to engage in in-depth learning.
• The desire to improve productivity : Automating tasks to save time for knowledge workers to be able to focus on the most important and productive tasks is a key driver for embracing AI across multiple industries. This level of automation also helps address gaps in the skills of employees within their facilities. Knowledge staff can be retrained to perform other tasks.

Institutions across the region are involved in experimental models and conceptual experiments that utilize various forms of AI technology and evaluate different types of use cases. Artificial intelligence is a broad term encompassing aspects such as machine learning, in-depth learning, local language processing, image recognition, and recommendation systems. The best way to understand this is to consider AI as an umbrella term that includes machine learning and local language processing. Then branch out from machine learning in-depth learning.

• Machine learning is defined as the process of creating a statistical model of different types of data, and performs multiple tasks without having to program it. Machine learning models are "trained" by many different types of data. Machine learning typically involves three types of learning (supervised, unsupervised, enhanced). Examples of machine learning include order prediction systems, recommendation systems (used to propose products for e-commerce site users), and fraud detection.
• In-depth learning is basically deep learning or layers of learning, and is part of machine learning. Examples of in-depth learning include self-driving, image recognition, video surveillance, and diagnostics.

Local language processing is the ability to extract people, places, and objects (also known as entities) as well as verbs and relationships (also known as intentions) from unstructured sentences and passages. Include local language understanding and generation. Local language generation is the ability to build text / conversational narratives from structured or semi-structured data. Examples include analysis of opinions, answering questions, and machine translation.

Sometimes the use of different AIs may include the use of different elements of each of these techniques depending on the form of automation or the desired outcome.

Use cases of artificial intelligence

When it comes to using innovative technologies such as artificial intelligence, it is important for organizations to identify the “use case” they seek to ensure to achieve the desired result. This approach focuses primarily on the commercial value resulting from the use of technology, not the technology itself. There are currently many cases of AI use across a variety of industries including:

• Automated Customer Service Programs : The goal is to provide customer service through a learning program that understands customer needs and problems. It seeks to reduce the time and resources consumed in responding to customer queries and solving their problems. This represents a widespread use case across sectors such as banking, insurance, retail, government, healthcare, telecommunications and media. Examples include chat robots on e-commerce sites, or artificial intelligence tools such as EVA used by Emirates NBD in the UAE.
• Organizational Intelligence : Artificial intelligence allows companies to address immediate regulatory compliance in real-time by providing actionable insights, reducing risks and addressing problems as they arise. This situation is prominent at the level of regulated sectors such as banking, finance, energy and utilities. Artificial intelligence is also used to combat money laundering and fraud detection purposes.
• Software consultants and recommendation systems : Artificial intelligence / cognitive abilities are used to support user interaction or processing by matching user needs with the most appropriate product or service. This case is used by banks, retailers, governments, insurance companies and telecom operators. Examples include recommendations made to customers based on their online purchases, and the way banks and insurance companies propose appropriate products / services after asking a set of questions to their customers.
• Intelligent Automated Protection and Protection System: Artificial intelligence is used to process information reports, extract critical parts of information, and connect points of contact between different information such as threats to databases, systems, sites, etc. Examples include the use of artificial intelligence to monitor networks and monitor threats.
• Government Intelligence, Investigation, Counterterrorism and Defense Systems : Artificial intelligence systems are used to support security services at the local, state, and federal levels by identifying, monitoring, and responding to threats against personnel, assets and infrastructure. Examples include the use of artificial intelligence to improve surveillance systems and the availability of border identification, as well as the use of robots to improve security in public places.
• Diagnosis and treatment: This includes diagnosing cases and providing personalized treatment to patients at the individual level by providing feedback on a variety of data sets, including medical records, analysis results, clinical studies and radiology.
• Automated Preventive Maintenance System : This system uses automated log data from various sources and contributes to a model that provides forecasts and alerts of potential maintenance needs.
• Recommendations and automation of sales processes : Artificial intelligence and cognitive engines work with CRM systems to find out what is best for the customer in real time, and recommend sales agents steps that are most appropriate in each case to help them attract customers or complete a sale.
• Adaptive Learning : This system modifies how teaching materials are delivered to suit student performance. Thus, it adapts to different directions immediately when each student interacts during and between lessons. ALF, the UAE's artificial intelligence platform, provides an interactive system that allows students to enhance self-learning.
• Digital Knowledge Tools for Enterprise Knowledge Officers : Digital assistance tools help employees answer questions, anticipate future events, and provide internal workplace recommendations. These intelligent systems apply machine learning to large data sets, enhancing employee innovation, collaboration and greater productivity, thereby maximizing the return on information assets.

Use cases help organizations optimize their operations, improve customer / user experience, ensure cost savings, and even create new products and services. Artificial intelligence will become more widespread in society with the inclusion of artificial intelligence capabilities in consumer devices, public transport, healthcare systems, education, and citizen services.

Adopting AI in the Middle East, Turkey and Africa

Artificial intelligence is a transformative technology for enterprises in the Middle East, Turkey and Africa, with annual spending in the region expected to reach $ 156 million by 2021, representing a five-year compound annual growth rate of 40.7 percent. Images of AI adoption vary in the region. Countries such as Saudi Arabia, the UAE and South Africa have already implemented specific use cases or are developing long-term development strategies and plans to adopt AI.

The UAE has developed a strategic roadmap to incorporate AI in various sectors, highlighting its commitment to innovation by appointing a minister of artificial intelligence, the first of its kind in the world. One of the first cases of AI use in the UAE was Rashid, a bilingual AI-based system in Dubai, which served as a single point of contact to guide users by providing information about government and citizen services. Artificial intelligence agents for customer service have since been deployed in the banking and utilities sectors, and there are also examples of the use of artificial intelligence in the practice of medicine, emergency assistance, crisis management, and flight facilitation. Artificial intelligence in Africa is used in the banking and insurance sectors, while use cases have also emerged in areas as diverse as wildlife conservation and remote drug delivery.

Artificial intelligence in the Kingdom plays a key role in realizing the transformation aspirations of Vision 2030 and driving innovation in general. The ambitious $ 500 million Neum project will be fully managed by AI, while AI, IoT and cloud services will lead many connected services, which will benefit residents and visitors to facilitate a smooth and sophisticated experience. In October 2017, the Kingdom reaffirmed its commitment to promoting the advancement of artificial intelligence by granting citizenship to a “human-like” robot named “Sofia”.

AI robots will undoubtedly play a key role in the future of the Kingdom, from being in Neum to embedding them in day-to-day operations in several key sectors. The Kingdom has also highlighted its commitment to innovation by investing in the Japanese firm Softbank, which has created human-like robots such as Pepper and Now, which are used at the sector level for customer service and information purposes.

Advances in AI will be important to ensure the successful integration of robots into society. These robots are different from manufacturing robots since artificial intelligence will be used to teach them the skills of interaction and human participation. Artificial intelligence will be used to ensure these robots can communicate in different languages ​​and perform many routine tasks. Early use of AI robots has been widely associated with customer service, patient care, and general assistance.

These are stereoscopic robots. They are different from “software” robots, also known as automating robotic processes; a program that simulates human actions and is used to automate any simple task. It is based on rules defined for the system. But artificial intelligence goes far beyond that. It consists of rules-based systems and ensures that the machine can learn from and respond to humans. It is also much faster and able to respond to unexpected scenarios. Many robotic automation service providers are optimizing these functions using artificial intelligence.

This demand for AI creates a new system consisting of specialized applications and processes based on AI / cognitive technologies, AI / Cognitive-based services / processes between companies, and consumer services based on AI / Cognitive technologies. This trend towards the adoption of AI / Cognitive technology solutions has led to the establishment of many startups in the region that promote innovation and economic diversification on a larger scale.

Challenges related to the adoption of artificial intelligence

AI challenges are largely related to the way data will be managed and used to train the system.

Bias : Institutions should ensure that the data used to train the system has the least possible bias. Structured and cached data sets are necessary to ensure the correct response from the system. Any bias given to the system can produce unexpected and undesirable results.

Privacy: One of the biggest instances of using AI is to improve consumer services and participation. This requires organizations to ensure the privacy and security of data when collected to provide such services. It is important for organizations to ensure compliance with global data privacy standards such as the European Public Data Protection System. These systems provide customers with greater control over their data and how it is used to improve overall transparency when using the services.

Trust : In a world of self-service, trust is important. Driverless cars bring this problem to the forefront. If the car doesn't respond in time and in the right way, it can be deadly. Users need to trust that the system will respond to accidents properly and promptly.

Skills : Skills are a major challenge for customers, suppliers and partners. Technology providers in the region are working with governments and educational institutions to train students in AI. Partners and customers should consider retraining staff in the same field as well.

Communication companies and artificial intelligence

Telecommunication companies will play a key role in ensuring that many cases of AI are achieved. Even IoT-enhanced AI projects require telecom operators to play a key role. These include autonomous vehicles, intelligent transport management systems, and the use of drones for preventive maintenance. In order to implement these projects effectively, they must rely heavily on telecommunications companies that can provide superior connectivity services such as 5G services.

Telecom companies are increasingly using AI to improve their network and customer services, such as using chat robots to interact with customers, and using AI to provide self-repair and secure networks. Self-repair networks can maximize operational efficiency and choose the right course of action to ensure readiness without the need for human intervention. The use of AI in telecom companies also improves the overall customer experience.

Telecom companies are increasingly diversifying their service packages and becoming a key IT services partner for their corporate customers. With AI, operators will not only be able to support their customers in implementing AI services, but will also provide platforms that enable their customers to use AI services.

Telecommunication companies clearly benefit from AI, optimizing their internal processes and delivering improved services.

Conclusion

Artificial intelligence will undoubtedly lead to a new wave of superior and innovative user / client experiences. But despite the obvious benefits of artificial intelligence, many argue that its spread necessarily means job loss and, in rare cases, robot control of the world. Artificial intelligence, like other technologies, will lead to a shift in the kind of jobs humans will perform, not large-scale layoffs. Those with skills that are no longer required will need to be retrained; AI will create demand for new jobs such as AI trainers, machine interaction model designers, and business analysts who can ensure the smooth integration of AI into business functions.

As AI continues to advance, popular media tends to highlight the problem of robots replacing humans, but this is quite unlikely to happen. The term "uniqueness" describes the situation when artificial intelligence is equal or superior to humans, but achieving this level of use will require tremendous progress in the power of computing, logarithms, and supporting legislation. While such advances may be possible in the very distant future, it is not even a remote possibility in the near term.

It seems clear that the way organizations deliver services is evolving. In many cases, customers do not realize they are interacting with AI systems, but the technology will greatly enhance customer expectations. Artificial intelligence in the Middle East, Turkey and Africa has already radically changed the way banks, telecommunications companies and government entities provide customer service, image recognition is used for security purposes, and recommendation systems are used to improve e-commerce services. The benefits of using AI are clear, and if organizations are determined to achieve the goals of their digital transformation and maintain their importance in a changing digital economy, they must adopt a proactive approach in determining which cases of AI are most useful in their particular circumstances.