Artificial intelligence (AI) is showing potential across a wide variety of industries, including retail and manufacturing. AI has the potential to incrementally add more than 10 percent or around $15 trillion by 2030 to current global economic output. Of this, $6 trillion is likely to come from increased productivity from automating business processes and from augmenting their existing labor force with AI technologies as well as $9 trillion is likely to come from increased consumer demand resulting from the availability of personalized or higher-quality AI-enhanced products and services.
AI is clearly a growing force with giants such as Google already investing heavily into new AI initiatives. Google’s recent $500m purchase of start-up DeepMind is an investment in its people intended to gain business advantages, for instance, by applying deep learning to improve energy efficiency of Google’s data centers or to enhance Google products with AI.
Artificial intelligence is the science of making machines do things that would require intelligence if done by men.
Most executives believe AI will allow their companies to obtain or sustain a competitive advantage. But only about one in five companies has incorporated AI in some offerings or processes. Disruption from artificial intelligence (AI) is here, but many companies aren’t sure what to expect from AI or how it fits into their business model. Yet with change coming at breakneck speed, the time to identify your company’s AI strategy is now.
Over the past decade, almost all aspects of how we work and how we live – from retail to manufacturing to healthcare – have become increasingly digitized. This has led to a vast amount of data which in turn is setting up the next wave of digital. AI will exploit the digital data from people and things to automate and assist in what we do today, as well as find new ways of doing things that we’ve not imagined before.
Specifically, we see massive, digital-driven breakthroughs happening across four fronts:
1. Predictive sales
Data is the fuel for any business. But, just having data isn’t enough. Companies must possess tools that will generate information from such data. AI can be used to glean meaningful insights from data. One of the hallmarks of AI is that it is highly dynamic. When exposed to new data, AI systems learn and adapt, allowing companies to generate more value from the information already at hand. AI systems gather data in real time and analyze it keeping in mind the existing information.
Predictive sales is one of the biggest disruption opportunities in commerce. Today, AI-powered software can gather historical data about past purchases and help sales departments drive conclusions for easier decision-making. Such as identifying the most and least popular products during an exact period of time, suggesting products that can be successfully promoted on a given date, and calculating probability of a purchase to give short-term views on turnover. Being able to tell how much of a given product can be sold by a certain date allows shops to stock inventories more efficiently and eliminate large sums of unwanted costs. It’s especially valuable working with perishable products, which include not only groceries, but also concert and transportation tickets – anything that makes you lose money when it’s unsold.
2. Automated customer service and chatbots
AI can be used to provide assistance to users via a virtual platform. Remote assistance is now a reality through usage of AI systems. Gartner forecasts that 85% of customer interaction will be handled without a human by 2020. By integrating AI with various social media platforms such as Facebook and Twitter, users can be updated about product delivery schedules, potential delays, promotional offers and more.
AI-based chat bots are programmed to communicate with customers in a personalized manner. E-commerce chatbots help buyers in looking for the right product, checking product availability, comparing multiple products, and finally, helping make the payment. Chatbots also help connect customers with the appropriate service personnel in case of any complaints or queries. Buyers can ‘talk’ with these machines via text, voice, and sometimes even pictures. And because bots don’t need sleep or days off, chatbots will help retailers provide more reliable customer support and save some of the $1.3 trillion it costs every year to answer customer calls. For retailers that need it, 24-hour customer support would be in reach. An example of great implementation of AI in business is Emirates Airlines, which uses chatbots to connect with millions of fliers across the world in real time.
3. Automated personalized content
Writing accurate and search engine optimized (SEO) descriptions for every product is time-consuming and expensive when it necessitates hiring writers to slog through every individual product. Instead of manually writing content or simply guessing what customers would like to see, machine learning and intelligent analytics can be used to analyze key features and to provide up-to-date and personalized content, and to scale this to the vast amount of touch points, channels, brands and countries. For example, real estate site Trulia optimized its usage of natural language generation to generate location descriptions by applying thresholds, rankings, information retrieval (TF-IDF) and seed sentences. Most importantly, they conducted blind tests of AI and human-generated content and found the quality to be comparable.
4. Customer-centric search and recommendations
AI has found its way into the earliest stages of the customer purchasing journey. With AI, customers now have the power to spot an item, scan it into their mobile device and instantly be directed to its e-commerce page. In the consumer market, for example, Pinterest Lens brings AI to the forefront of new product discovery. Users perform 600 million visual searches with Lens every month to identify or buy things they see online or in the physical world. Users can photograph, for instance, a meal at a restaurant or snap a clothing item they see on TV. The Lens will find them content with recipes or links to buy the item online. The visual search technology now understands more than five times as many things as it did a year ago. This means that you can now search for recipes, clothes, and countless objects for your home with increasing accuracy.
E-commerce sites also integrate AI into their marketing techniques to recommend products to customers. The deep learning capabilities of AI can collect data on customers’ previous purchases, returns and other buying habits. It can also suggest similar products based on these preferences. This method is fast and easy. It allows customers to find items of interest without spending time and effort searching for them.
How Businesses Can Evolve
The idea of AI is not new, but the pace of recent breakthroughs is. Machine-learning algorithms have progressed in recent years, especially through the development of deep learning and reinforcement-learning techniques based on neural networks. Computing capacity has become available to train larger and more accurate models much faster. Massive amounts of data that can be used to train machine learning models are being generated, for example through daily creation of billions of images, online click streams, voice and video, mobile locations, and sensors embedded in the Internet of Things. For companies, successful adoption of these evolving technologies will significantly enhance performance. Some of the gains will come from labor substitution, but automation also has the potential to enhance productivity, raise throughput, improve predictions, outcomes, accuracy, and optimization, as well expand the discovery of new solutions in massively complex areas such as synthetic biology and material science.
Companies must digitally transform one or more of these three areas:
1. Business models
To make full use of the power of AI requires a thorough reimagining of business models and processes. The drivers of competitive advantage have shifted from pure IP to talent and category leadership with AI. Unlike almost any other field, companies profiting from AI are forced to compete on a playing field where IP – both algorithms and, to a lesser extent, data – is not scarce. The two things that are scarce are talent and category leadership in the sense of having the best product. Companies that do well in AI have learned to exploit these scarcities. The AI-first business model is about using data and algorithms to create better products, to augment humans, and to reduce costs.
2. Digital capability
We found that industries leading in AI adoption—such as high tech, telecom, and automotive—are also the ones that are the most digitized. Likewise, within any industry, the companies that are early adopters of AI have already invested in digital capabilities, including cloud infrastructure and big data. These assets and capabilities, both hard and soft, are increasingly becoming a competitive differentiator and platforms for innovation and disruption. Each business regardless of industry and sector will likely need to assess how distinctive its digital assets and capabilities are vs. those of competitors.
In any case, you don’t have to go it alone on AI—partner for capability and capacity. With the AI field recently picking up its pace of innovation after the decades-long “AI winter,” technical expertise and capabilities are in short supply. Even large digital natives such as Amazon and Google have turned to companies and talent outside their confines to shore up their AI skills. Consider, for example, Google’s acquisition of DeepMind, which is using its machine-learning skills to help the tech giant improve even core businesses such as search optimization.
3. Augmented Reality
Overall half of the activities that people are paid almost $15 trillion to do in the global economy have the potential to be automated further augmenting human work with technology. All occupations will be affected. Every third activity in 60% of occupations could be automated. This means that many workers will work alongside rapidly evolving machines, which will require worker skills to evolve also. The rapid evolution in the nature of work will affect everyone from welders to landscape gardeners, to mortgage brokers to doctors and CEOs. For instance, manufacturers are using AI to work alongside humans to complete routine tasks and processes. This can free up employees’ time and allow them to focus on more high-value tasks, saving time and money. The service industry is also using AI to automate processes, provide recommendations and use voice-controlled technology. For example, insurance providers use chatbots as a way to provide 24/7 customer service or complete routine tasks like renewing policies.
It’s widely anticipated that AI is set to go into turbo drive transforming business and industries in the next couple of years. From AI-powered voice assistants like Amazon Alexa to intelligent chatbots and mobile apps like those provided by Sephora and Starbucks, consumer brands are capturing insights from machine data and customer interactions, using them to create better customer experiences. AI is beginning to embed itself into all aspects of our lives. From the growing number of self-checkout cash registers to advanced security checks at the airport to predictive sales and enhanced production planning in manufacturing firms; artificial intelligence is just about everywhere.
Does your industry look for AI talent and capability? Is it time for your company to get off the sideline and consider AI strategically? Contact Upside Digital to learn how we can help your organization to succeed in the digital era.
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