By: Jakob Westh Christensen, Market Analyst at eToro

The one investment megatrend to watch out for is the rollout of AI. There is no doubt that this single megatrend has the potential to reshape companies and economies – and your investments.

As AI automates tasks that workers perform today manually, we will see a significant uptick in productivity in companies and economies. Seeing the megatrend is clear, but positioning your investment is the hard part. We are still in the early stages of this revolution, and I don’t expect we will see a measurable productivity impact on companies’ and economies’ output until 2 to 3 years.

While the earnings growth (and stock price gains) so far are coming from the chip designers and manufacturers, it’s vital for the successful investor to identify the sectors and companies that eventually will benefit from a productivity boost and consequently stronger earnings.

This is likely to be found in companies where they can achieve a high degree of automation, and at the same time have a strong competitive advantage. This ensures that cost cutting results in margin expansion, and not just passing on cost cutting to end users.

For example, the taxi industry could achieve an exceptionally high level of productivity per employee with the introduction of self-driving cars. While initially, the industry could see a margin expansion with a lower employee cost base, this competitive industry could soon see price competition lowering margin to ‘normalised levels’, benefiting the consumer and, to a lesser extent, the investors.

On the other hand, insurance companies could see significant cost reductions in the underwriting process, which can be highly automated. At the same time, customer habits and customer inertia can result in less price competition, benefitting the company and its investors.

By Karim Azar, Regional Vice President – Middle East & Turkey, Cloudera

The digital landscape is evolving at an unprecedented pace, and at the heart of this evolution lies the transformative potential of artificial intelligence (AI). Across industries, AI is not merely a buzzword but a revolutionary force driving innovation, efficiency, and growth. Its impact extends beyond automation, touching every side of business operations and decision-making. It can revolutionize multiple sectors and fundamentally reshape the corporate industry.

Nonetheless, challenges arise with technological evolution, particularly in accessing and overseeing varied datasets across diverse environments. These challenges frequently act as obstacles to achieving successful AI implementation. In response to these challenges, the technology landscape is witnessing significant advancements in open data lakehouse technologies, providing a robust foundation for AI and analytics. Let’s delve into key technological developments and their advantages, focusing on the broader implications rather than specific products.

Unlocking Business Potential

AI has the potential to unleash new opportunities for businesses. McKinsey’s findings reveal that more than 62% of companies in the Gulf Cooperation Council (GCC) region currently utilize Generative AI in some operational aspect. The research underscores the substantial potential of AI to create tangible value in the GCC, with an estimated value of up to $150 billion.

This adoption trend is not without merit; statistics show that 83% of businesses adopting AI report substantial (30%) or moderate (53%) benefits. AI can address various challenges by providing predictive analytics and personalized customer experiences, enabling organizations to make faster and more accurate data-driven decisions.

Despite the obstacles in adopting AI, such as data management complexities and security concerns, offering air-gapped deployment for large language models (LLMs) is still a viable option. This feature boosts security, data privacy, and performance while also lowering customer operational expenses. However, overcoming these challenges requires more than just technological solutions. It demands a comprehensive approach that includes robust data governance frameworks, continuous employee training programs, and collaboration with regulatory bodies to ensure compliance with data protection laws.

AI Across Industries

AI is not a one-size-fits-all solution. It is applied differently across industries and business functions, including healthcare, finance, manufacturing, and retail. The potential uses of AI are vast, from boosting supply chain efficiency to transforming healthcare outcomes and customer service.

For example, in the healthcare industry, AI-powered predictive analytics can help doctors identify patients at high risk of developing certain diseases, allowing for early intervention and personalized treatment plans. AI algorithms can analyze market trends and financial customer behavior to recommend customized investment strategies. In manufacturing, AI-driven predictive maintenance can proactively anticipate equipment failures and schedule maintenance activities, minimizing downtime and reducing costs.

As businesses increasingly adopt AI, they invest in their organization’s future. By promoting innovation and agility, companies can leverage AI to maintain competitiveness in a digital era. Prioritizing data privacy and security helps build trust with customers and stakeholders, ensuring AI technologies’ responsible and ethical use.

AI is a significant transformation in how businesses function and innovate. Embracing AI opens up vast opportunities for organizations to reshape their operations, stimulate growth, and influence the future of business. While the journey may present challenges, the potential benefits are boundless for those willing to embrace the power of AI.

By: Dr Ryad Soobhany, Associate Professor, School of Mathematical & Computer Sciences, Heriot-Watt University Dubai

Intelligent Transportation Systems (ITS) have emerged as a transformative solution in urban areas, tackling challenges such as high traffic and pollution. These systems, incorporating a network of static and mobile sensors, including cameras on buildings or vehicles/drones, embedded in the smart city infrastructure, are revolutionizing traffic management. By harnessing data from cameras, in-vehicle GPS systems, in-vehicle Near Field Communication (NFC), IoT devices, and Artificial Intelligence (AI), ITS enable the monitoring and tracking of vehicles for Intelligent Traffic Management Systems (ITMS) or Public Transportation Management Systems (PTMS).

While intelligent transportation systems offer significant benefits, it’s crucial to acknowledge the challenges and risks they pose. ITMS provides real-time monitoring of traffic on roads and at junctions, while PTMS focus on managing transportation fleet and passenger information services. Emergency Response Management Systems (ERMS) primarily monitor the emergency responders of the smart city. The use of intelligent vehicle surveillance systems improves traffic management, public safety, and urban planning, but it also raises concerns about the data privacy and security of users and infrastructure, a risk that must be carefully managed.

Benefits

There are several benefits from the implementation of vehicle surveillance systems in urban areas and the most obvious one is a better vehicle traffic flow by using ITMS. Cameras placed strategically across the city monitor traffic to identify congested areas and road traffic incidents (e.g. accidents). Implementing dynamic traffic lights systems at junctions and temporary speed limits can improve traffic flow. Using AI, predictive traffic routing forecasts traffic bottlenecks and suggests alternative routing.  The use of PTMS leads to enhanced scheduling of public transportation; for example, the arrival/departure of trains/metro at the station is synchronized to feeder buses or taxis being stationed outside the station. There is an improvement in customer satisfaction and journey planning with real-time updates for public transport. Traffic flow is also improved by monitoring of cycle and pedestrian lanes, where safer cycle lanes will encourage road users to adopt cycling in certain urban areas adapted for cycling.

There is an overall improvement in public safety by better traffic management, with better response time to emergency situations by the ERMS, such as ambulances. LPR/ANPR (Licence Plate Recognition/Automatic Number Plate Recognition systems and GPS tracking systems in cars allow the monitoring of vehicles while they are located withing the bounds of the smart city. Stolen or wanted vehicles can be detected and followed through the city. The use of surveillance cameras, LPR/ANPR systems and GPS tracking can improve identification of criminal activities, which should enhance the response of law enforcement. Under-Vehicle Surveillance Systems (UVSS), which are cameras placed at strategic places on roads in the city take pictures or videos of the underside of vehicles to check the chassis for stolen cars. UVSS can also be used to detect contraband at ports or entry/exit points in smart cities.

The use of LPR/ANPR systems ease the management of Low Emission zones, which are areas where low emission vehicles (e.g. electric or hybrid vehicles) can circulate without charges and vehicles with higher emission rates have to pay an hourly or daily charge. The implementation of Low Emission zones can bring environmental benefits. The improved traffic flow in the urban areas can also lead to environmental benefits with less emissions in traffic jams and long traffic queues at junctions. Apart from environmental benefits, there are economic benefits linked to better health and overall happiness of citizens and visitors.

Risks

Several risks are associated with the amount of data collected from the vehicle surveillance systems. The main concern is the privacy of the smart city’s car drivers and car owners. Vehicles and their drivers are tracked everywhere they travel around the city and the speed they travel. This can lead to tracking drivers and without proper legal frameworks, the data collected can be used to encroach on the users’ privacy. The large amount of collected and stored data can be quite attractive to cyber criminals and might lead to cyber-attacks. Any data breach from these attacks might expose the personal information of drivers and their vehicles. Cyber-criminals can target the surveillance systems, for example hacking the intelligent dynamic traffic speed system and changing the traffic speed around the city.

Having video surveillance around the urban areas recording the public can lead to ethical issues. Most of the time, drivers might not have provided informed consent to participate in the vehicle surveillance systems. The lack of consent from users can lead to non-compliance with regulatory bodies and can result in legal challenges from user groups. Users need to be made aware that they are entering a vehicle surveillance zone and their data might be recorded. Vehicle surveillance systems can be used to discriminate against certain sections of the community, for example, young drivers might be unfairly targeted by the vehicle surveillance systems because they allegedly drive fast and dangerously, which allegedly cause accidents. Any cyber security attack or data intrusion can lead to users losing trust in the vehicle surveillance system.

The use of vehicle surveillance systems can benefit smart cities and enhance the quality of life of residents and visitors, but the authorities must respect the personal privacy of the public by ensuring that data are collected and processed ethically and guarded against any cyber-attack. Security policies and mitigation plans are primordial for vehicle surveillance systems.