The future of retail looks dire, as more brick-and-mortar stores close their doors. U.S. retailers have announced 8,558 store closures so far this year, with total U.S. store closures reaching 12,000 by the end of 2019, Cordite Research reported Friday.
While the Internet and automation are usually responsible for these closures, the same technology could be a solution for physical store locations, said Paul Winsor, general manager at Data Robot.
“If retailers want to stay open at the current stores they operate in, my recommendation to them is: Do they understand the changing habits of those customers, and how are they shopping with them, in those places?” Said Winsor.
“To survive in a tough, tough retail market, you have to start your business and make predictions based on learning from your historical data,” he says. “It’s all about learning from your historical data.”
After being in the retail industry for more than 30 years, Winsor said that artificial intelligence (AI) and machine learning are tools retailers must use to get ahead — and to stay open.
How businesses have been open in the past
“Data-driven retail is not new. Technology is around to help companies understand their business from a data perspective,” says Winsor. “Data is not as personal and accurate as machine learning can help you.”
To make predictions in the past, retailers look at daily and weekly transaction data and draw conclusions from it, Winsor said.
As technology has evolved and convenience has become a priority, online stores have become the primary way to shop. As technology has captured the shopping experience, it has also taken the approach of retailers to draw conclusions and expectations about their services. If retailers refuse to grow and adapt to emerging retail infrastructure, they will inevitably fall behind.
AI helps retailers in three ways
“With AI, we are dealing with machines that can simulate intelligent behavior or simulate intelligent human behavior, that is, sense, reason, action, and adaptation,” said Altimeter lead analyst Brian Solis. “One of the most popular ways that leading brands use AI today is machine learning.”
“The difference is that with machine learning, systems can differentiate models from pure data sets, and with the right management, learn from those data to predict and predict results and improve performance over time,” Solis says. “It helps retailers learn how to personalize engagement, offers, and the next best move, as well as guide product and service development.”
1. Understanding the customer
Machine learning helps retailers understand their customers and predict future behaviors, Winsor said.
“We want to be more comfortable with the way we shop and we want to be, we want more convenience, and we want to shop across multiple channels,” Winsor said. “As consumers, we are constantly changing our habits, so we know what machine learning and AI are doing in this space.”
2. Estimate
“The really effective part is around the assessment,” Winsor said. “We are now seeing retailers using AI and automated machine learning to manage their demand forecasting to understand the real volume that is needed today based on demand from customers.”
This not only increases accuracy but also increases operational efficiency, saving both time and money for the organization.
“It really increases your accuracy because you’re taking over, you’re learning from the past, and you’re predicting what that size will be in the future,” Winsor said. “Operational efficiency is definitely key because we’re talking about an industry that runs its business at very low operating margins.”
3. Regulating product supply and development
Machine learning and AI play an important role in determining retail supply and development plans.
Machine learning can answer a few questions, according to Winsor: Are retailers selling the right products today based on the customer’s demands and expectations? And are they priced right? And are they the right products — in the right place, in the right assortment in the right stores.
The future of AI in the retail sector
The future of retail is more automated and more personalized, Solis said. “Consumers’ choice becomes less confusing and stressful.”
“Screens, connected dressing rooms, and virtual racks are the most promising and realistic future scenarios for me based on my personal, data-defined personality,” Solis says. “It only shares things that I consider based on past history and connected to personal preferences. You can play that scene in the retail sector, ie automotive, accessories, etc.”
In U.S Drivers add 81 extra hours to their arrival each year due to traffic.
The other U.S. cities are also worse, these cities are known for difficult driving conditions with hills, bridges, and bikers.Diverse road conditions cause heavy traffic, but companies like Uber are coming to Pittsburgh to test autonomous vehicles.
And, besides the AV, that traffic technology includes an AI system called Sertrack, which allows traffic lights to be adapted to traffic conditions without having to rely on pre-programmed wheels.At installed lights, the team behind the system estimated that travel time was reduced by 25%, braking by 30%, and idle by more than 40%.
It costs about $ 20,000 to wire up and install Surtrack at the intersection.Sertrack works by tracking traffic and creating attendance models.
First, hardware including a computer, camera, or radar device is installed at the intersection.
Through communication with the below models, the processing is done in a way that creates a local plan from multiple data sources.
In 2016, the calculable worth additional by the agriculture business was calculable at but one percent people GDP.
Factors like global climate change, increase and food security considerations have pushed the business to hunt a lot of innovative approaches to safeguard and improve crop yields.
As a result, AI is bit by bit evolving as a part of the technology evolution of the business.In this article we have a tendency to explore the applications of computer science to know current and rising trends for business leaders, and gift representative samples of common applications.Artificial Intelligence within the Agricultural business - Insights Before:Based on our analysis, the foremost common applications of AI in agriculture make up 3 main categories:Agricultural robots: - corporation’s area unit developing autonomous robots to perform the required agricultural tasks, like harvest crops and fast quicker than human labor.
Crop and Soil observation: - corporation’s area unit developing laptop vision and deep learning algorithms to method knowledge compiled by drones and / or software-based technology to watch crop and soil health.Predictive Analytics: - Machine learning models area unit being developed to find out and predict numerous environmental impacts on crop yields like global climate change.Blue watercourse Technology - Weed management:The ability to regulate weeds may be a high priority for farmers associate degreed an in progress challenge as weed killer resistance becomes a lot of common.
per a quest study conducted by the Weed Science Society of America on the impact of uncontrolled weeds on corn and soybean crops, annual losses to farmers area unit calculable at $ forty three billion.
Companies’ area unit exploitation automation and artificial intelligence to assist farmers realize a lot of economical ways in which to safeguard their crops from weeds.
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In recent years, the top, Artificial intelligence companies in Bangalore such as Naspers, KDC and IBM have been expanding their R labs in India, China, Japan and Europe.
Companies like IBM and Yana are rapidly expanding into India and are providing a wide range of artificial intelligent solutions across a wide range of industries including financial services, transportation, consumer protection, energy, government and manufacturing to name a few.
The best companies in the world such as IBM, Cisco and others are also opening offices in the Asian region to further increase their presence in India and Asia.
As the technology becomes more developed and is made available to more consumers, then demand for this software will increase exponentially.
Companies that specialize in artificial intelligence research and development now have a global customer base.
Many top colleges and universities in India are also churning out software engineers, computer science professionals, and robotic engineers who are eager to find a job in the United States or Canada.
Not all heroes wear capes, well, as far as I know, Artificial Intelligence can't!
AI has the power to tackle some of the world's social problems too (the real heroes are the masterminds who thought of AI in the first place).
For example: helping the blind by directing them, diagnosing cancer and many many more.
People are just learning to use AI and the possibilities are vast.
Which is why interest in AI has dramatically increased in the past few years.
And Google has taken this social initiative naming it “AI for Social Good”First of all, what is AI?
