Health
The history of technology demonstrates the displacement impact of automation counterbalanced by technologies that create new skills and tasks in which the workforce has a comparative advantage[1] .
AI enhances efficiency and productivity of care delivery in healthcare. Computer vision applications are spread through multiple sources, from medical imaging analysis to detect diseases, to cell analysis in the human body, thus providing valuable information to medical experts[2] . This enables clinicians and medical practitioners to spend more time in direct contact with the patient. The pandemic has further boosted AI investment in healthcare, in fact, the Mount Sinai Health System uses AI in combination with clinical data and imaging to analyse patients with COVID-19”[3].
Other applications of AI in healthcare in 2021 include the use of Chatbots, Robotic Surgeries, Virtual Nursing Assistants, Precision Medicine and Administrative Workflow Assistance[4] .
Source: https://www.pexels.com/photo/doctor-using-a-smartphone-5214989/
Retail
Large retailers, especially third-party digital marketplace providers, establish Research & Development (R&D) labs worldwide to keep up the pace with the latest digital and AI technologies, experiment with these new technologies and incorporate them into their business models.
Retailers should integrate AI applications throughout their value chain.
Five main management areas may be identified where retailers focus on applying AI, namely:
- Customer service management,
- Store management (physical and virtual),
- Supply chain management,
- Marketing management
- Cybersecurity and Risk management.
1. Customer Service Management
Retailers can use AI-powered solutions for:- Data Management: Artificial Intelligence
systems can be used to manage data, analyze it and extract insights for
various uses for businesses.
- Customer Interaction Management:
Artificial Intelligence enables retailers to use a chatbot solution to
answer customer questions. This means that customers might not need to
call customer service, but rather type their queries into Facebook
Messenger or chatbots on their website.
- Stock Management: AI-powered solutions can
help retailers make the best decisions about inventory, optimize the
amount of stock they should purchase to sell.
- Customers to carry out three main AI-powered searches: semantic, image and voice.
- AI applies deep learning to the customer’s purchase history and shopping behavior to recommend the best product to the customer according to their needs. The algorithm provides suggestions for products, sizes, colors and more.
- Virtual try-on service, which is a virtual reality (VR) based product recommendation service that allows customers to try on clothes virtually and get a preview of how it will look before making a purchase.
- AI also allows retailers to facilitate customer purchasing through targeted shopping assistance and after-sales support using voice command and checkout-free service.
2. Management of physical & virtual stores[1]
Retailers use AI to:- Efficiently manage physical and/or virtual
stores and consolidate ones’ quality shopping experiences. Guarantee that the right products and
quantities are in the right place at the right time.
- Enhance the retailers’ online and offline profit-making by making use of AI-powered visual merchandizing, category management and merchandizing algorithms.
- Carry out in-store repetitive, predictable and manual tasks using robots to free-up staff time which may be used to enhance customer experience. Robotic automation provides autonomous: shelf-scanning and store atmospheric control.
- Support staff to collect real time data to provide tailored recommendations to customers and checks in-stock positions through in-store chatbots and AI-powered sales assistance.
3. Supply chain management
AI empowers retailers to:- Optimize their ordering and replenishment management via two main solutions: AI-powered demand forecasting and autonomous order processing systems.
- Use automated systems, robots, and specialized software to transport materials, perform various tasks and streamline / automate warehouse processes.
- The warehouse robotics can help retailers to improve their warehouse operations’ efficiency. Here, AI provides three main solutions: autonomous mobile robots, AI-powered sorter systems and collaborative robots.
- Optimize and automate their delivery service via three main solutions: drone delivery service, self-driving cars and AI-powered delivery modelling.
4. Marketing management[2]
Since AI may analyse large quantities of evolving data it is an enabler for retailers to make smart marketing decisions such as:- Adjusting prices to regularly offer clients a variety of prices depending on external factors and ones’ buying habits, thus boosting sales and maximising profits, also known as AI pricing.
- Managing communication using autonomous product catalogue creation and AI-powered advertising spending optimisation.
- Store location decision-making which is crucial for risk reduction decisions using location intelligence technology platforms, thereby reducing costs.
5. Cybersecurity and Risk management: are the toughest challenges retailers are facing in the digital economy. Fraud and data breaches may incur significant losses for retailers. Therefore, solutions are required to reduce the time to detect and respond to cyberattacks and avoid the manual triaging of security breaches. An AI-powered security platform solution boosts cybersecurity operational efficiency and efficacy[3] .
6. Further Applications of AI to Retail:
a. Music applied innovatively may positively influence customer experience using AI-based information systems with music as a key measure may in turn provide insight for business decisions. In-store music influence researched thoroughly and linked to a range of predicted marketing outcomes.
b. AI-based biometrics analysing facial recognition against music may identify ones’ preferences. So, AI-induced biometric–social identity through music is an important environmental stimulus that impacts customer behaviour[4] .
A progressively competitive retail environment, businesses are to continuously explore innovative ways to entice customers and ensure a positive retail experience, and AI will surely continue to evolve this sector.
Source: https://images.app.goo.gl/4GBigkbQkF3zKFuM6
Source: https://www.pexels.com/photo/high-angle-photo-of-robot-2599244/
Source: https://www.youtube.com/watch?v=5YyRERaLGoc
Transport
AI interventions are applications available for vehicles, infrastructure, drivers, or transport users, as well as to ensure their interaction enable a transport system that encourages user empowerment while supporting human–machine interactions.
AI mobility solutions are available to combat traffic, pollution and environmental deterrance allowing for improved, swift, clean, and competitive mobility. This coupled with telecoms energy applications, develop smart cities and urban science.
Some AI applications in transport include:
Connected and Autonomous Vehicles (CAVs) are tangible applications of AI in transport being the natural progression from conventional cars despite the current hesitation. CAVs do not require a driver or teleoperation control, together with connectivity functions they are proactive, cooperative, well-informed and coordinated since they may communicate with their surrounding environment through IoT. CAVs will transform mobility, transport networks and road infrastructure though AI and wireless connectivity capacities thus becoming the next mobility gold standard that transforms cities and cars. for this to take place production lines are expected to change completely, however car manufacturers and ride-hailing and intelligence companies are embarking on this journey.
● Artificial Neural Networks (ANNs),
● Genetic Algorithms (GAs),
● Simulated Annealing (SA),
● Artificial Immune System (AIS),
● the Ant Colony Optimiser (ACO),
● Bee Colony Optimisation (BCO) and
● the Fuzzy Logic Model (FLM).The companies shifting towards CAVs include: Audi, Baidu, BMW, Daimler, Delphi, Didi Chuxing, Ford, General Motors, Honda, Huawei, Hyundai, Jaguar Land Rover, Lyft, Magna, Mercedes-Bosch alliance, Microsoft, nuTonomy, PSA, Renault-Nissan alliance, Samsung, Tesla, Toyota, Uber, Volkswagen Group, Volvo, Waymo (Google’s self-driving cars project), ZF and Zoox.
Intelligence behemoths like Google and ride-hailing like Uber, not currently known as traditional vehicle makers, will drastically alter the dynamics of the sector as new entrants in a more adaptable automotive market where ICT will be the competitive differentiator.If smart cities actively encourage sustainable growth through car ownership reduction, the automotive industry may be incentivised to adopt new business models for sales that prioritize a sharing economy. The US, UK, Australia, New Zealand, Germany, Sweden, and China are providing the legislative framework for CAVs and investing heavily in research and development (R&D), including pilots and trials, to position themselves at the epicenter of the CAV breakthrough[1] .
Health and Safety: In today's climate, safety issues have become crucial for the automotive industry as a result of the increasing number of accidents emanating from increased traffic and the evergrowing popularity of public transit, having larger ramifications for people's quality of life and the government’s bottom line. Once traffic is regulated by electronic devices and algorithms, accidents and financial losses are expected to decrease significantly, especially when eliminating human error. Currently, the Adaptive Cruise Control (ACC), allows the driver to automatically cruise the car based on the user’s behavior.
Mobility-as-a-Service (MaaS) is a powerful concept, still in its early stages of development for full-scale implementation yet rather prominent. MaaS promises digital bundles of personalised multimodal mobility replacing privately owned vehicles with an all-in-one smart online platform providing integrated travel planning, booking, smart ticketing, and real-time information services. If MaaS can function as a true substitute for private automobile ownership, transforming car use into a strictly on-demand service, it may drastically reduce the number of cars on the road, resulting in significant reductions in travel delays, air pollution, noise nuisance, energy consumption, and transportation-related social exclusion, as well as other benefits provide advantages in terms of safety and accident prevention, health and well-being, social cohesion, accessibility, and household spending. It will also shift precious living space currently devoted to cars and auto parking to public and active transportation, as well as other more human-centric built environment improvements[2] .
[1] Nikitas, A., Michalakopoulou, K., Njoya, E.T. and Karampatzakis, D., 2020. Artificial Intelligence, Transport and the Smart City: Definitions and Dimensions of a New Mobility Era. Sustainability, 12(7), pp. 2789.
[2] Severino, A., Curto, S., Barberi, S., Arena, F. and Pau, G., 2021. Autonomous Vehicles: An Analysis Both on Their Distinctiveness and the Potential Impact on Urban Transport Systems. Applied Sciences, 11(8), pp. 3604.
Source: https://images.app.goo.gl/oFbeZSvC3mpUkJcQ8
Source: https://www.pexels.com/photo/timelapse-cityscape-photography-during-night-time-599982/
Source: https://www.youtube.com/watch?v=yS_eLn36tL0