The Rise of Artificial Intelligence (ai) in the Digital Era

Published: 2021-06-17 09:55:48
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The Rise of AI in the Digital Era
Executive Summary
For a long time, artificial intelligence (AI) was restricted to university research projects and the R&D labs of technology vendors. However, in recent years elements of AI have begun to be integrated within smart devices and web services. Indeed, AI is becoming pervasive across businesses and is being used to enhance both internal and external services. According to IDC, global spending on AI is expected to reach $52.24 billion in 2021.
The Middle East, Turkey, and Africa (META) region is often at the forefront of innovation when it comes to technologies such as mobile devices, the Internet of Things (IoT), and blockchain. Similarly, AI is being embraced by governments and organizations across the region as they look to create new services and improve their levels of efficiency. For example, AI sits at the core of the transformation ambitions outlined in Saudi Arabia’s Vision 2030 initiative, while the United Arab Emirates has established the UAE Strategy for Artificial Intelligence to tie in with the government’s ambition of enabling a superior quality of life.AI is bringing about a new wave of transformation across industries, fueling demand for new types of skills sets, and driving dialogue around governance and ethics, and organizations must determine where AI can be used within their processes and identify the outcomes they wish to achieve.
Situation Overview
Over the past year, numerous debates and discussions have taken place around the use of AI, both globally and regionally. Typically, these discussions have revolved around the new types of research involving AI, the successful use of AI for business outcomes, the potential job losses that could be caused by AI, and the ever-popular topic of machines taking over humans. The major driver of these discussions is the fact that AI is no longer a concept limited to the research lab, with the technology becoming increasingly pervasive across consumer and business services.
What is AI?
In simple terms, artificial intelligence can be defined as activities devoted to making machines intelligent. Cognitive/artificial intelligence can be defined as “systems that learn, reason, and self-correct. The system hypothesizes and formulates possible answers based on available evidence, can be trained through the ingestion of vast amounts of content, and automatically adapts and learns from its mistakes and failures.” AI is already being utilized by many technology, ecommerce, and social media companies to either create a new service or enhance their existing services. Take, for example, the smart virtual assistants such as Apple’s Siri, Amazon’s Alexa, Microsoft’s Cortona, and OK Google that have been embedded within a variety of devices and systems. Other examples of AI already in use include facial recognition upon uploading an image to social media, recommendations of products on ecommerce sites, spam filters on email systems, and even being able to map optimum traffic routes during peak rush hours.
Several factors are driving the use of AI by organizations across multiple industries, including:

Exponential Data Growth: According to IDC forecasts, global data volumes will reach 163 zettabytes (ZB) by 2025, up from 16 zettabytes in 2016. And there is a growing need to comprehend and analyze this data for strategic outcomes or real-time decision making. The use of AI will enable companies to analyze and manage their data much faster and across multiple iterations with minimum human intervention. This data can also be utilized to train AI systems for improved outcomes/services or for organizations to engage in deep learning.
The Desire to Improve Productivity: Automating tasks to free up the time of knowledge workers so they can focus on more strategic and productive tasks is a major driver of AI adoption across many industries. This level of automation also helps address the recurring skills gap within organizations; knowledge workers can be retrained to undertake other tasks within their organizations.
Advancements in Technology: One of the biggest enablers for the use of AI is the accessibility to increased compute power at lower prices. This can be in terms of access to GPUs, cost-effective servers, and cloud services.
All these factors have contributed to more and more organizations utilizing or exploring the use of AI within their organizations. AI is increasingly being considered as a major technology for the realization of digital transformation, which is when organizations use innovative technologies whereby to facilitate new operating models, create or enhance services, and gain a competitive edge to stay relevant in today’s hypercompetitive world. IDC’s META CIO Summit Survey 2017 showed that nearly 91% of organizations in the region are engaging in or planning to engage in digital transformation.

Organizations across the region are engaging in pilots and proof of concepts (PoCs) utilizing various types of AI technologies and evaluating different types of use cases. AI is a broad term that encompasses many aspects such as machine learning, deep learning, natural language processing, image recognition, and recommender systems. The best way to comprehend this is to consider AI as an overarching term that incorporates machine learning and natural language processing. Then as a further subset of machine learning there is deep learning.
Machine learning is the process of creating a statistical model from various types of data that performs various functions without having to be programmed by a human. Machine learning models are “trained” by various types of data (often, lots of data). Machine learning usually involves three types of learning (i.e., supervised, unsupervised, and reinforcement learning). Examples of machine learning include demand forecasting, recommender systems (used to provide suggestions within ecommerce sites), and fraud detection.
Deep learning is essentially in-depth learning or layers of learning and is part of machine learning. Examples for the use of deep learning includes autonomous driving, image recognition, video surveillance, and diagnostics.
Natural language processing (NLP) is the ability to extract people, places, and things (also known as entities) as well as actions and relationships (also known as intents) from sentences and passages of unstructured text. It is inclusive of natural language understanding and natural language generation. Natural language generation is the ability to construct textual/conversational narratives from structured or semi-structured data. Examples of NLP includes sentiment analysis, question answering, and machine translation.
Different AI uses cases may, at times, use different elements of each of these technologies based on the automation or outcome that needs to be achieved.
Use Cases for AI
When it comes to the utilization of innovative technologies such as AI, it is critical for organizations to define the “use case” they are seeking to implement in order to ensure the right type of outcome. This approach essentially considers the business value created from the utilization of the technology rather than the technology itself. Several AI use cases are currently being utilized across various industries, including:
– Automated Customer Service Agents: The aim is to provide customer service via a learning program that understands customer needs and problems. It aims to reduce the time and resources spent in addressing customer queries and resolving customer issues. This is a popular use case across several sectors such as banking, insurance, retail, government, healthcare, telecommunications, and media. Example include chatbots on ecommerce sites or AI agents such as “Eva” being used by Emirates NBD in the UAE.
– Regulatory Intelligence: AI allows companies to more efficiently address their immediate regulatory compliance in real time by delivering actionable insights, limiting their exposure, and addressing issues as they arise. This use case is prominent across regulated sectors such as banking and finance, energy, and utilities. AI is also being used for anti-money laundering and fraud detection purposes.
– Program Advisors and Recommender Systems: In this use case, AI/cognitive capabilities are utilized to assist with user interaction or processing by matching the user’s needs to the right type or product or service. This is a use case being used by banks, retailers, governments, insurance firms, and telecom operators. Examples include the recommendations that are given to customers based on their online purchases and the way in which banks and insurance firms suggest suitable products/services after asking their customers to answer a series of questions.
– Automated Threat Intelligence and Prevention Systems: AI is used to process intelligence reports, extract critical pieces of information, and connect the dots between different pieces of information such as threats to databases, systems, website, and so forth. Examples include the use of AI for network and threat monitoring.
– Defense, Terrorism, Investigation, and Government Intelligence Systems: AI systems are used to help federal/state/local security services to identify, monitor, and respond to threats against personnel, assets, and infrastructure. Examples include using AI to enhance surveillance systems and enable identification at borders, as well as the use of robots for improving security in public places.
– Diagnosis and Treatment: This involves diagnosing conditions and enabling the provision of personalized treatment at the individual patient level by extracting insights from the intersection of diverse data sets, including medical records, lab tests, clinical studies, and medical images.
– Automated Preventive Maintenance: This system uses machine log data from various sources, contributing to a model that in turn will enable predictions and alerts around potential maintenance needs.
– Sales Process Recommendation and Automation: AI/cognitive engines work with the customer relationship management (CRM) systems to understand customer context in real time and recommend actions to the sales agents that are most relevant to the specific interactions in order to help them qualify or close a sale.
– Adaptive Learning: This system modifies the presentation of material in response to student performance. It also adapts trends in real time based on every interaction a student makes both during and in between lessons. Alef, an AI platform in the UAE, provides an interactive system that enables enhanced self-learning for students.
– Digital Assistants for Enterprise Knowledge Workers: Digital assistants help workers answer questions, predict future events, and provide recommendations internal to the workplace. These intelligent systems leverage machine learning on large data sets, enabling innovation, collaboration, and higher employee productivity, thereby maximizing the return on information assets.
These use cases help organizations to optimize their processes, enhance their customer/user experience, ensure savings, and even create new products and services. AI will become increasingly pervasive in society at large with AI capabilities being included in consumer devices, public transportation vehicles, healthcare systems, education, and citizen services.
Adoption of AI in the META region
AI is a major transformational technology for organizations in the META region, with annual spending in this area expected to reach $156 million by 2021, which represents a five-year compound annual growth rate (CAGR) of 40.7%. The adoption of AI varies across the region, with countries such as Saudi Arabia, the UAE, and South Africa either already implementing certain use cases or putting in place strategies and long-term development plans for the adoption of AI.
The UAE has a strategic roadmap in place to drive the inclusion of AI across different sectors, and the country further highlighted its commitment to innovation by appointing a Minister of State for Artificial Intelligence, a first for any country in the world. One of the early AI use cases in the UAE was that of “Rashid”, a bilingual AI-based system or advisor in Dubai that serves as a single point of contact to guide users by providing information relating to various citizen and government services. AI customer service agents have since become commonplace in the banking and utilities sectors, while there are also examples of AI being used to dispense medicine, assist with emergency and crisis management.

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