It is difficult to imagine a sector that hasn’t or will never be disrupted by artificial intelligence (AI). Technology has completely redefined how we work in several industries. From informing better decision making to streamlining operations, it is evident that AI will continue to revolutionize several areas of work across different sectors.
Below we will see, the top eight industries where AI is causing major disruption in 2020 and beyond.
1. Retail and E-commerce
Global retail spending is expected to grow to $7.3 billion per annum by 2022. It is also predicted that by 2020, chatbots will power 25 percent of all customer service interactions. AI chatbots are helping retailers to collect customer data, which they use to provide meaningful insights to retailers. The tools collect enormous data from the digital requests made by shoppers who use technology to make purchases.
In future, these chatbots will improve their conversational abilities, capture moods, audible reactions, emotions, and eventually provide insights to retailers. Ultimately, they will help merchants to offer personalized customer experience to develop customer loyalty.
CRM applications in retail stores are increasingly using AI for automated data entry, ad personalization, account insights, and much more. In future, retailers will use virtual and augmented reality functionality in advertising. Moreover, immersive product catalog visualization is expected to grow dramatically, enabling shoppers to experience products before sharing.
In retail logistics, AI sensors are helping robots to navigate travel paths for delivery. Some retailers have AI-driven technology with sensors to monitor the items that customers pick into their baskets, enabling automatic billing. Walmart has already brought on board thousands of robots to perform tasks such as scrubbing floors, tracking shelf inventory, and unloading trucks.
2. Manufacturing and Production
Artificial intelligence has limitless potential in the world of production. According to McKinsey, the industry “is on the verge of a revolution in which artificial intelligence applications, from virtual assistants to advanced robotics, will disrupt end-to-end value chains amid radicals.”
In manufacturing, AI performs tasks ranging from automation of human jobs to preventative maintenance. The technology is proving more efficient by being less susceptible to error. Pattern recognition tools and machine learning algorithms are playing a significant role in factories and will inevitably shape future manufacturing.
Most manufacturers face the challenge of variable quality despite the stringent quality assurance measures they have in place. AI, through machine vision, uses powerful cameras that spot microscopic nuances in products to ensure that quality is upheld.
3. Transportation and Traffic
As AI disrupts several industries, its impact is also being felt in the transport sector. The greatest challenge the industry has faced over the years has been on modeling according to a predictable pattern. Unpredictable traffic, accidents, and human errors have made it challenging to create models that can help solve traffic problems.
With the integration of artificial intelligence in transport, it is now easy to predict events using available data. The models developed from the data are proving fruitful in traffic management, thereby minimizing accidents and easing traffic in cities.
One of the most revolutionary applications of AI in transport is the autonomous vehicle. Though we were skeptical of the technology at its formative stages, it has now become a reality. Driverless taxis are currently operating in Tokyo, and they look promising in terms of reducing the costs of cab services.
Similarly, The US logistics sector is also embracing autonomous trucks. With trucks transporting 65 percent of goods globally, we are likely to see changes in how transport and logistics will change. Specifically, costs will likely come down, making it cheaper to use road transport for logistics.
In aviation, one of the greatest problems we often experience when we want to fly is flight delays. Airlines are always late to provide alerts on impending flight delays, causing us a lot of inconveniences. In 2018, Google began using machine learning and historical data to forecast flight delays. Future innovations will be useful in forecasting weather patterns and use them with available airline data to predict flight delays.
4. Logistics and Supply Chain
According to a PricewaterhouseCoopers (PwC) forecast , AI will account for almost $15.7 trillion to the global economy by 2030, and this has serious implications for the logistics and supply sector.
The sector is embracing AI in its processes because the tool promises to solve the inherent complexities of global logistics. If implemented correctly, artificial intelligence can enable companies to make agile and smart decisions while foreseeing problems in advance.
AI can streamline everyday procurement jobs through augmentation and automation. For routine tasks, chatbots can speak with suppliers, place purchasing orders, and answer internal questions and file documents.
Logistics firm DHL has partnered with Amazon, allowing you to query the parcel shipment information through the virtual assistant speaker “Alexa“. You simply activate the DHL Parcel “skill” using the Alexa App and ask the speaker to tell you the location of your package.
Machine learning, coupled with supply chain planning, can help in forecasting inventory, demand, and supply. If done correctly, AI can revolutionize the optimization and agility of supply chain decision making.
Supplier selection is a great concern for most organizations because it determines supply chain sustainability. Using data sets from supplier audits, assessments, and credit scoring can provide valuable insights into the reliability of a particular supplier. Machine learning can analyze the data to make it actionable during the selection process.
The use of smart warehouses can significantly reduce the cost of running a storage facility in the form of reduced labor costs. The system that uses automated storage and retrieval systems brings inventory into and out of the warehouse.
Alibaba and Amazon have made great strides in the use of robots in their warehouses. Alibaba has already adopted the use of automated storage and retrieval systems in China, where robots replace human labor. The machines have proved useful in bringing inventory to employees for packing. Amazon has also rolled out robots to work alongside humans to increase efficiency and productivity.
Telecommunication is among the fastest-growing industries and has, over the years, been an enabler of disruption in several sectors. It uses artificial intelligence in many aspects of business, ranging from predictive maintenance and improving network reliability to enhancing customer experience.
Telecoms are incredibly using AI to improve customer service through chatbots and virtual assistants. Virtual assistants help telecoms to respond to the support requests they receive from companies. After introducing chatbot TOBi, Vodafone recorded an improvement in customer satisfaction. Nokia’s virtual assistant MIKA provides solutions to network issues, resulting in improvements in its resolution rate.
Nokia launched an AI-based cloud-based network management solution named AVA platform, predict service degradations, and help in capacity planning. AT&T has an innovative solution that uses AI to support its maintenance actions. The telco is experimenting with drone technology to expand its LTE network coverage. It intends to use video data from the drones to provide maintenance support from its cell towers.
6. Healthcare and Medical
Although in its formative stages of the AI adoption journey, healthcare presents boundless opportunities for the use of the technology. Machine learning looks promising by showing patterns within a population, while natural language processing (NLP) is applicable in drug safety. Moreover, AI-powered platforms can provide possible treatment options for patients.
AI also provides help in automating basic administrative tasks, freeing up healthcare providers’ time to focus on better patient experience. The incorporation of smart billing reduces revenue losses, helping health facilities to seal losses.
Currently, AI is used in predicting diseases, identifying high-risk patient groups, and in offering automatic diagnostic tests. Also, user-friendly bots are now assisting patients in health diagnosis while robots perform operations with precision. Even in DNA analysis, AI is playing a significant role.
7. Banking and Financial Services
It’s an exciting time for banking and financial services. AI is brewing up a turbulent storm of disruption within the industry. Banks are more focused on using AI to better themselves and gain a competitive advantage in an increasingly dynamic operating environment. Generally, the industry seeks to use AI capabilities to realize improvements in speed, accuracy, cost, and efficiency, while also meeting customer needs.
AI adoption in the banking industry is buoyed by the ability of machines to do and exceed what humans are capable of. The technology can collect and analyze data to identify patterns, which enable banks to become more efficient. Moreover, machine learning helps financial institutions to predict events, allowing the banks to plan advance.
Currently, AI is increasingly useful in risk management, regulatory compliance, sales, payments, back-office operations, and many areas. Specifically, it is applicable in providing personalized insights, AI biometrics in conversational banking, smart contracts in risk underwriting, and anti-fraud initiatives.
8. Insurance and Wellness
A huge workforce performing repetitive manual tasks characterizes the insurance industry. It is a sector that is ripe for disruption. AI adoption promises to revolutionize its operations by providing a unique customer experience while increasing coverage.
Already, chatbots are playing a vital role in providing an automated buying experience. Moreover, AI enables insurance providers to customize insurance coverage, thereby providing on-demand insurance products. Additionally, the emergence of virtual claims adjusters facilitates the expedient claims settling process, limiting incidents of fraud.
AI is also useful in enabling behavioral policy pricing. For example, insurance carriers can now reduce auto premiums for safe drivers or lessen the health premiums for people who practice a healthy lifestyle.