A similar story is becoming apparent within the marketing industry, as the advancement of technology has evolved consumer expectations to a point where marketers are challenged to keep up the pace amidst all the complexity. Whether we are referring to rules-based automation, natural language processing, machine learning or AI, the point is we need help managing some hard tasks. Marketers should focus on the value we're trying to realise: Delivering more relevant experiences for customers, improving business outcomes because of that relevance, and doing it efficiently to get more from our budgets. Machine learning and smart automation are beginning to prove value in an increasing number of areas including optimisation, personalisation, customer segmentation, and contextual intelligence.
In the supply chain, AI can analyze large data sets and recommend customer service and operations improvements while supporting better working capital management. As corporate systems become more interconnected, providing access to a wider breadth of supply chain data, the opportunity to leverage AI increases. Let's look at the potential benefits of using AI to link transportation data with order data: A logistics enterprise ensures the delivery of a product within two days. This information supplies customer service and supply chain professionals with proactive alerts of potential fulfillment challenges.
If the people replaced by AI and robots aren't retrained well, they'll be forced to apply for low-skilled jobs, leading to an oversupply of workers at that level and depressing those wages even further. We also need to acknowledge the uneven geographic impact of automation and take steps, as businesses and collectively as a society, to increase opportunity in geographic areas that are affected adversely. In the 21st century, we're facing a massive change in the technologies and types of jobs available, similar to that faced by our grandparents in the early 20th century. That way we will ensure that AI technology creates opportunity for all, not just for a lucky few.
Lately, a number of Silicon Valley luminaries -- Mark Zuckerberg and Elon Musk, among them -- have embraced the idea of a Universal Basic Income (UBI), which would put all of us on the dole, regardless of need. Hughes wants to encourage national brainstorming on the issue and has committed to using the proceeds of the book to fund a UBI pilot in a small American city. Some, including Helen Razer, also writing in Quartz, say that UBI is a pipe dream and "just a bedtime story Elon Musk tells himself to help the super-wealthy sleep." No one on a stagnant wage can currently buy the things that Musk -- and the rest of Silicon Valley -- wants to sell them.
The truth is somewhere in-between; while it is unlikely to entirely eliminate many occupations over the next ten years, AI and machine learning will impact almost all industries, jobs and business to varying degrees. These systems dramatically improving performance, save time, and free up your expensive human talent to focus on strategic tasks. McKinsey estimates that 59 percent of all manufacturing activities could be automated, while a whopping 73 percent percent of the activities that food service workers perform have the potential for automation. Forrester Research expects "enterprise interest in, and use of, AI to increase as software vendors roll out AI platforms and build AI capabilities into applications," as "enterprises that plan to invest in AI expect to improve customer experiences, improve products and services, and disrupt their industry with new business models."
Both types of devices provide an interactive experience for the users due to Natural Language Processing technology. ML technology is able to develop insights that are beyond human capabilities based on the patterns it derives from Big Data. The immense volume of support tickets makes the task lengthy and time-consuming. If automated via ML, the HR can let the machine predict candidate suitability by providing it with a job description and the candidate's CV.
All these processes and sensors work simultaneously, processing large data sets to redefine the driving experience. Chat bots too require complex understanding to simulate human behaviour for efficient customer service. Data analytics can provide significant value to chat bot technology by leveraging large data sets that form the basics to simulate human behaviour. While automation technologies like driverless cars and chat bots may disrupt our lives in the future, each one of these could potentially create avenues and opportunities for individuals and businesses.
The new job roles that will dominate the IT workforce are within digital domains such as big data, artificial intelligence, Internet of Things (IoT), cloud computing and cybersecurity, according to the report "How Automation is Changing Work Choices: The Future of IT Jobs in India" released this month by Simplilearn. "While there is a risk to jobs due to these trends, the good news is that a huge number of new jobs are getting created as well in areas like cybersecurity, cloud, big data, machine learning and AI," said Kashyap Dalal, chief business officer,Simplilearn, in a statement. Piyush Mishra, technology leader -- food security, Tata Services, said that the group was working on a precision agriculture technology where an unmanned aerial vehicle or a drone can be used for aerial spraying on farms. "In addition to labour, it (spraying) has multiple impacts on farmer life -- from health to efficiency and productivity," said Mr. Mishra at the CII event.
This shows no sign of stopping in 2017, with new and existing technologies allowing institutions to ultimately offer more unique banking experiences. From my meetings with decision-making executives at the world's leading banks, here are the top five trends dominating their technology investment discussions: In 2017, several banks will undoubtedly take their first steps toward "conversational commerce," a term coined by Chris Messina of Uber to describe the future of messaging within apps. They will also inspire meaningful change within the bank's organizational structure with the continued rise in executive power of the chief digital officer, chief marketing officer and chief data officer. However, for this to happen, the role of the procurement team will also need reevaluation -- a process that could result in new vendor evaluation processes that focus on agility, innovation and time to market, rather than just on vendor consolidation and cost negotiation.
It is an industry that has functioned largely without changes for the past hundred years, but with the emergence of technologies such as artificial intelligence, self-driving and robotics, the basic paradigm of the industry is expected to change. While the Tesla Gigafactory 1 is just one of many examples of auto companies increasingly employing robots in production, it is the strongest indication that as the auto industry moves toward automation and robotics, human employment in the industry is set to decrease. According to the Information Handling Services (IHS) Technology's Automotive Electronics Roadmap Report, the use of AI based driver-assistance systems in vehicles is set to jump from 7 million a couple of years ago to 122 million by 2025. Since cars are increasingly expected to be equipped with hardware such as camera-based machine units, radar-detection units and driver evaluation units, AI will serve as the connecting interface between the regular car machinery and such hardware -- e.g., advance brake warnings using object detection feedback from the onboard cameras.