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Marketing. Companies that are seeking to enhance their advertising efforts can use AI-powered tools to determine which customer groups are more likely to respond to which marketing offers. With AI tools, they can collect real-time reactions and provide analysis to improve customer experience. In the best-case scenario, using AI recommendations could lead to a higher return on marketing investment.
Supply Chain. Similarly, companies that use AI to optimise their supply chains can reduce costs and increase efficiency since AI gives them a competitive edge over rivals who still rely on traditional supply chain management methods in today's complex supply chain environment. One of the most vivid examples is Uptake, a company that uses AI and machine learning technologies to analyse data for telematics in order to forecast failure and avoid delays for a variety of vehicles and machinery. Uptake's most illustrative cases include increased fleet uptime with four-fold ROI growth or 34% longer time between unscheduled maintenance for its clients.
Finance. Companies in the financial industry, for their part, can use AI to design new investment products and investment or trading strategies by identifying trends, data patterns, and trading signals. As such, Artificial intelligence can benefit both large corporations and startups that build their products around this technology. For example, one of such startups, Underwrite.ai, a company that analyses thousands of data points to assess credit risk for loan applicants, helped one of its clients maintain a default rate of 8.5% for the first three payments, compared to the industry average of 35%. []
Automation in Banking. Companies have already begun to use artificial intelligence to automate repetitive tasks and make better, data-driven decisions. In this way, they can free up resources and focus those resources on growing their businesses by streamlining operations and increasing efficiency. JP Morgan, for example, used an ML-powered programme for automated compliance agreement processing that takes several seconds to review over a thousand agreements, compared to previously spending 360,000 hours on this process by employees. []
Fashion. Similarly, businesses are already using natural language processing on Internet text to gain insights into customer sentiment and preferences. Leading fashion brands are competing to be the first to identify emerging trends on social media in order to forecast what will be popular in the coming season and gain a better understanding of their customers' preferences. Based on this data, they make more informed decisions about what type of garments to produce and how much to produce, raising their chances of success in a given season. This assists them not only in identifying trends, but also in operational optimization by reducing markdowns, excess inventory, and associated logistics costs, while ensuring faster inventory turnover.
Healthcare. Companies in the healthcare industry can use blockchain technology to securely store and share patient data, which can improve patient outcomes and lower costs.
Food. The food industry can benefit from using blockchain to predict and prevent food safety issues. For example, the United States Food and Drug Administration used the aforementioned technologies, including blockchain, to receive critical tracking events and key data elements from partners in order to prevent food illness outbreaks and alert clients in real time before they consume contaminated foods. []
Education. A variety of educational record-keeping documents, such as diplomas, transcripts, and certificates, often require validation from a third party. In turn, blockchain can automatically verify them through instant document approval, greatly easing the application process for a job or a university programme. []
Retail. Due to its ability to quickly bring together all retail chain members and provide them with real-time information without giving prevailing control to one of the parties, blockchain provides a unique opportunity for retail. In this regard, Walmart applied blockchain technology as a foundation for an automated network system for managing invoices from and payments to its 70 third-party freight carriers. Before that, Walmart had 70% of disrupted invoices with more than 200 tracking data points factored in invoices and large quantities of transported goods. This number dropped to 1% after the system was set up. []
Customer insights. IoT enables businesses to collect and analyse data on how their products and services are used in the real world, which can aid in cost reduction and workflow optimization. For example, a company that uses IoT to create a connected product can gain valuable insights into how customers use the product. Think of Amazon’s Alexa today communicating with home’s thermostats, lightning systems, TV, speaker systems, etc.
Consumption analysis. Besides, IoT can assist the company in identifying areas where the product can be improved and meeting customer expectations in terms of new features. Consider a company that uses Bluetooth beacons to analyse customer movements in a store once they are connected to WiFi. This information allows them to predict new trends and identify the most popular items by identifying the most visited store departments and products.
New revenue streams. Additionally, the company can use the data collected from the IoT-enabled product to generate new revenue streams, such as selling the data to third parties or creating new products and services.
Monitoring and connection. As another example, companies can use the Internet of Things operationally to connect and monitor various devices and systems within an organisation, allowing for greater efficiency and cost savings. IoT is widely used in the logistics industry for this purpose, such as connecting deliverymen and customers, storing product-related information in a digital product memory or a smart label, and overseeing various business processes with this information - topics researched or even implemented by DHL and its partners. []
Cost. One of the most significant is the cost of implementing these. Many of these emerging technologies necessitate significant investments in new hardware, software, and talent, which can be a significant challenge for businesses, particularly small and medium-sized businesses (SMBs).
Expertise. Another challenge is ensuring that the company's existing talent pool can manage and implement these new technologies. Companies may need to invest in formal training programmes and other ways to support their existing employees to ensure this.
Regulation. Finally, when adopting emerging technologies, businesses may face legal and regulatory challenges. Depending on the industry, the use of personal data may be subject to strict regulations, and businesses may need to invest in compliance measures to ensure they are meeting these requirements.