The Artificial Intelligence (AI) revolution has arrived. Despite its infancy, AI has already launched self-driving cars, early detection of cancer cells, smart identification of retail store locations, and voice-activated home systems that provide auto-set alarms and thermostats.
This technology may seem awful to many real estate agents and brokers, but a deeper understanding of the potential applications for AI and machine learning may bring a new appreciation for the opportunities ahead.
AI Transforming Real Estate:
Improve the Home Search for Clients:
Since listings became available online, homebuyers have been able to search for homes by selecting features such as location, price, square footage and the number of bedrooms. But reducing property search to these parameters can also treat home hunters with hundreds of homes, or worse, filter out appropriate properties that do not meet the search criteria.
Machine learning can make this process extremely frustrating by analyzing a person’s search patterns and creating a more accurate picture of what they really want. For example, Zillo combines search data from a potential home buyer with similar buyers and generates a list of actively searched properties while connecting with other properties that are close to their needs.
Identify Strong Client Leads for Agents
AI technology also provides a powerful tool that helps agents to expose their ideal clients. For example, Zillow's site can instantly identify hundreds of data points that separate a serious buyer or seller from “daytime” or “window shopping” homes.
Some systems use natural language processing (NLP) to distinguish natural values or touchpoints from low-value touchpoints as a means of identifying contacts that engage the agent most.
This tool of accurate identification helps special agents, such as a hyper-local expert, to tailor the field of potential clients to their niche or the vision of the business.
Programs such as Machine Learning Zillow’s premium broker Flex allow a large percentage of clients looking for agents to produce and generate pre-qualified leads, which agents will not pay until a closing agreement is reached.
In the future, an agent can call a robot to set up client appointments over the phone in any language using the brokerage’s CRM or cross paths in the open house with a bilingual robot that works as a translator for Mandarin-speaking visitors.
Remove the Bias from Agent Recruiting:
By providing an in-depth analysis of the AI and Machine Learning market and giving an edge to brokers in the hiring process by assessing where the current demand is strong, low and growing. As a result, brokers and team leaders can move confidently into those areas with new hires.
Computers also offer the benefit of eliminating emotional bias from the agent interview process, thereby helping brokers hire the right agents to help them succeed in their niche.
According to Rudina Cesari, Founder and Managing Partner of Glasswing Ventures, a Boston, MA, next-gen AI venture capital firm, the algorithms outline how humans can overcome the hiring of meta-analysis.
Of course, personality and cultural competence are variables that require human judgment, but unbiased comprehensive analysis can eliminate the amount of work that needs to be done when considering the agent’s performance history.
Machine Learning Enabling Agents
As long as real estate continues to be a data-intensive business, brokerages must adopt the latest technology if they want to overcome competition with speed leads and contract-to-close transactions.
Understanding players utilize machine learning by generating more quality leads with precision, streamlining the transaction process and intelligently hiring.
Murtaza Haider, associate professor at McGill University in Toronto, CA and author of The Financial Post, real estate expert Stephen Moranis, says, “Real estate is changing the way AI [AI’s] sector works in its traditional brick-and-mortar roots. “
For many agents and brokers, the idea of this kind of technology still paints a vague personality-less picture of the future, but experts say the net result may actually be quite the opposite. By helping people quickly analyze the huge amounts of search data that exist, smart tech agents are able to focus on the aspects of their jobs that they think are most profitable — the relative, intuitive, and creative roles in real estate that are beyond the capabilities of any computer.
After all, no matter how sophisticated the AI is, clients are unlikely to be able to master the key qualities that clients seek in agents, show empathy, build relationships, negotiate art, tell the story and adapt to new situations.
For brokers who fear that they will outperform their larger rivals, Chen recalls, “Developing and implementing machine learning applications requires considerable resources, even for companies with established data science disciplines. Our goal is to make this technology available to as many brokers and teams as possible because the more successful they are, the more successful we will be. “
How does AI help the commerce industry?Traditionally, retail businesses have been satisfied with making an e-commerce website for their brick-and-mortar stores, but now it is not enough.
You need to develop new emerging technologies to provide immense value to customers.
Retail businesses are implementing AI to improve various processes, customer experience and ultimately revenue.Prior to AI, there was personalization in the eCommerce industry, but of limited value.
If you are using services like Amazon or Ebay, you should definitely experience this.Artificial intelligence enables you to monitor customer interactions across multiple platforms, such as websites, mobile apps, and emails.
It’s about hitting the right chord at the right time.With the new semantic-based search option, customers are now able to search smarter and get results that are of their interest.
There may be many reasons to show such interest.
The lack of a constructive perspective may lead to a limited problem and set of solutions as AI shapes both and its expanding environment.To Know About: How Artificial Intelligence Will Change in 2050?It is important to understand the difference between agency and structure when adopting a constructive perspective.
While the abusive perspective focuses on changing the innate incentives, motivations, or accessibility of the malicious person, the risk perspective focuses on developing the skills or attention of the engineer.Behavioral change involves two levels of focus on the individual agent.
However, the constructivist view begins with the premise that the risk level does not change frequently, based on the example of avalanche even after the behavioral change of the individual agent, which may be prevented by asking for the cause of steepness rather than steepness.
Asking for specific events that turn it off.To change our way of thinking about the risks and dangers of AI, one of the main questions that need to be asked is whether there is pressure on decision-makers to see if they can change socio-economic or political structures.
Make risky or expensive decisions, regardless of how well-intentioned or competent they are.Such concern is most applicable to the security sector where a country’s missile, submarine and command, and control systems can be closely tracked by improving data and processing capabilities.
Also, AI’s well-known ability to lead to monopoly markets due to the scale of revenue and labor displacement achieved by major tech companies is linked to issues related to structural mechanisms outside of security.To Know About: How is AI Transforming Life?As shown in these examples, the proliferation of AI can be detrimental to society, even if the misuse of technology does not occur.
Artificial intelligence is surely expected to achieve the unexpected; in every possible way.
Here are some of the everyday applications, which you may have not noticed before.
Zencode was founded in 2013 as an IT outsourcing company.
We set up our first Delivery Centre at Chennai, India in 2014.
We outgrew the garage to a full fledged office within 2 years.Along the way, we also expanded our market footprint to Hong Kong and setup our AI & Blockchain practice at Bangalore, India.Today, we can help you build your IT platforms from start to finish.
From design to coding to implementation and support .
Zen is a business application that will revolutionise the way a company does things; A marketplace that brings various people together; A custom business application for your business; A mobile application that uses crowdsourcing to bring convenience to customers; or a myriad of potential new industries, ask Zencode to help you with the implementation.Email Address Sales : [email protected] HR : [email protected] us: BANGALORE III & IV Floors, NCR Complex 580/B, Sector 6, HSR layout, Bengalore-560102
Artificial Intelligence is also known as machine intelligence, where machines mimic the intelligence of the human mind and actions.
The primary purpose of artificial intelligence is to make rational decisions according to the circumstances.
The correct implementation of AI can carry more complex tasks with less time.
Artificial intelligence has received an upward trend of growth, leading to the development of human society and multiple industries, and artificial intelligence will continue to grow in promising ways for consumers and various businesses.As 2020 has not been a great year so far because of COVID-19, artificial intelligence has played a massive role in combating the pandemic induced situations.
Every ounce of technological advances and innovations helped us to fight the pandemic.Every organization is finding new ways to operate effectively and to serve their customers as social distancing measures remain in place.
These chatbots have provided the answer to almost every possible question, from evaluation to exercise without putting the human resource at risk.Machine learning and artificial intelligence have helped researchers to analyze a large volume of data to take preventive measures.
There are several ways organizations deal with the contracting process.
Few manage it with word-based drafting and redlining coupled with storing in repositories like Drop Box or SharePoint and some deploy automated contract management systems for this process that also include collaboration.https://blogs.docskiff.ai/top-5-ingredients-of-ai-based-contract-analytics-platforms/
