Artificial Intelligence has been around for almost 70 years, but only in recent years has it become a major disrupter for many industries due to the convergence of big data, processing power and cloud computing. This has led to the development of “deep learning”, which allows a type of computer intelligence that closely mimics human decision-making. In this paper, I take look at the evolution of Artificial Intelligence, along with two disparate industries: Retail and Real Estate. These industries have adopted AI at different speeds. Also, each industry has its own form of resistance and uses for the technology. My theory is that there are forms of technology resistance by major players in the real estate industry in combination with the long industry cycles that are causing slow adoption.
The Digital Retail Theater: Shopping's FutureCognizant
Artfully deploying advanced technologies such as virtual reality, augmented reality, 3-D modeling, and digital avatars, our envisioned digital retail theater (DRT) offers huge benefits to both retailers and consumers. The digitally enhanced shopping experience is rapidly gaining momentum among both online and physical retailers.
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The Digital Retail Theater: Shopping's FutureCognizant
Artfully deploying advanced technologies such as virtual reality, augmented reality, 3-D modeling, and digital avatars, our envisioned digital retail theater (DRT) offers huge benefits to both retailers and consumers. The digitally enhanced shopping experience is rapidly gaining momentum among both online and physical retailers.
The 5 Biggest Future Technology Trends: Accenture Reveals Their Vision Of Pos...Bernard Marr
What are the key technology trends that will disrupt the next three years? Every year, Accenture produces its technology vision report to predict the tech trends that every company should watch. Here we look at their 2019 research and their top five predictions.
The Rise of Machine Learning in Marketing [Research Report 2019]Alex Mari
The "rise of machine learning in marketing" describes the goal, process, and benefit of AI-driven marketing. In particular, it explores how marketing leverages machine learning models to automate, optimize, and augment the transformational process of data into actions and interactions with the scope of predicting behaviors, anticipating needs, and hyper-personalizing messages.
Full research report: https://www.researchgate.net/publication/332865857
9 Technology Mega Trends That Will Change The World In 2018 | PowerPoint Pres...Graphi Tales
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In their report, “Predictions 2017: Artificial Intelligence Will Drive The Insights Revolution”, Forrester Research predicts that “insights-driven businesses will steal $1.2 trillion per annum from their less-informed peers by 2020”. Statista tells us that this year “the global AI market is expected to be worth approximately 7,35 billion U.S. dollars.”
I compiled a “best of” e-book for Informa Connect Learning from interviews with 34 pioneers on the topic of AI in marketing, healthcare, finance and maritime/logistics. From Wolfgang Lehmacher, Head of Supply Chain and Transport Industries of the World Economic Forum to Forbes 30 under 30 Domeyard Hedge Fund Partner, Christina Qi, the Global No. 1 Fintech, AI,
Blockchain & No. 2 InsurTech Influencer by Onalytica, Spiros Margaris to award winning scientist and entrepreneur, ReviveMed CEO and Co-Founder, Leila Pirhaji -
learn how 34 of the top artificial intelligence experts in the world are using AI to disrupt their industries, increase profits, drive efficiencies and in many cases - save lives.
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The Amazing Ways That L’Oréal Uses Artificial Intelligence To Drive Business ...Bernard Marr
L’Oréal, the world's largest beauty brand, continues to invest in technology and artificial intelligence to enhance its operations, products, and customer experience. From its technology incubator that focuses on how to best use technology to support the beauty industry to its innovative products such as an AI-powered skin diagnostic, L’Oréal uses artificial intelligence to its advantage.
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Digital Survivors—Death of the Retail CultureAccenture
The landscape of retail players and consumers has been drastically reshaped and the end-to-end consumer value chain is expected to transform beyond recognition in just two to five years. With online commerce growing at four times the rate of the overall industry, many traditional retail giants have made significant investments—upwards of $70 billion USD—in digital channels.So, why do their market caps continue to decline?
This is a presentation delivered by Katie King at the UKInbound tourism conference, on "How can marketing professionals adapt to survive & thrive in a world of AI?"
https://www.ukinbound.org/events/tourism-marketing-in-a-digital-age-seminar/
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The 7 Biggest Technology Trends To Disrupt Banking & Financial Services In 2020Bernard Marr
New technology changes the operations and realities of organizations in all industries when it is widely adopted. It's no different with the latest innovation introduced by artificial intelligence, blockchain, and other technology. Here we look at the 7 biggest technology trends that will disrupt banking and financial services in 2020.
The Fascinating Ways PepsiCo Uses Artificial Intelligence And Machine Learnin...Bernard Marr
PepsiCo, one of the world’s biggest food and beverage companies, unlocked the value of data and now uses artificial intelligence and machine learning in its factory operations, to determine product placement and marketing opportunities, uses robots for delivery and to screen potential job candidates, and more.
With enterprises putting digital at the core of their transformation, our annual Data Science & AI Trends Report explores the key strategic shifts enterprises will make to stay intelligent and agile going into 2019. The year was marked by a series of technological advances, including advances in AI, deep learning, machine learning, hybrid cloud architecture, edge computing (with data moving away to edge data centres), robotic process automation, a spurt of virtual assistants, advancements in autonomous tech and IoT.
The Rise of Machine Learning in Marketing [Research Report 2019]Alex Mari
The "rise of machine learning in marketing" describes the goal, process, and benefit of AI-driven marketing. In particular, it explores how marketing leverages machine learning models to automate, optimize, and augment the transformational process of data into actions and interactions with the scope of predicting behaviors, anticipating needs, and hyper-personalizing messages.
Full research report: https://www.researchgate.net/publication/332865857
9 Technology Mega Trends That Will Change The World In 2018 | PowerPoint Pres...Graphi Tales
Some tech trends fizzle out and die a quiet death, while others are so significant that they transform our world and how we live in it. Here are the top nine tech mega-trends that I believe will define 2018 and beyond.
Beyond the Buzz: How Sectors as Diverse as Logistics, Finance, Healthcare & M...Leah Kinthaert
In their report, “Predictions 2017: Artificial Intelligence Will Drive The Insights Revolution”, Forrester Research predicts that “insights-driven businesses will steal $1.2 trillion per annum from their less-informed peers by 2020”. Statista tells us that this year “the global AI market is expected to be worth approximately 7,35 billion U.S. dollars.”
I compiled a “best of” e-book for Informa Connect Learning from interviews with 34 pioneers on the topic of AI in marketing, healthcare, finance and maritime/logistics. From Wolfgang Lehmacher, Head of Supply Chain and Transport Industries of the World Economic Forum to Forbes 30 under 30 Domeyard Hedge Fund Partner, Christina Qi, the Global No. 1 Fintech, AI,
Blockchain & No. 2 InsurTech Influencer by Onalytica, Spiros Margaris to award winning scientist and entrepreneur, ReviveMed CEO and Co-Founder, Leila Pirhaji -
learn how 34 of the top artificial intelligence experts in the world are using AI to disrupt their industries, increase profits, drive efficiencies and in many cases - save lives.
5 Major Robotics Trends To Watch For in 2019Bernard Marr
We are increasingly seeing robots becoming part of our everyday lives. Robots are no longer confined to factories but are now entering our homes and offices. Here I look at the five most significant robotics trends everyone should watch out for in 2019.
The Amazing Ways That L’Oréal Uses Artificial Intelligence To Drive Business ...Bernard Marr
L’Oréal, the world's largest beauty brand, continues to invest in technology and artificial intelligence to enhance its operations, products, and customer experience. From its technology incubator that focuses on how to best use technology to support the beauty industry to its innovative products such as an AI-powered skin diagnostic, L’Oréal uses artificial intelligence to its advantage.
How To develop An Artificial Intelligence Strategy: 9 Things Every Business M...Bernard Marr
An artificial intelligence (AI) strategy has become a vital tool every organisation needs. Based on my experience helping companies develop their AI strategies, I share my nine things every AI strategy must include.
Technology tech trends 2022 and beyond Brian Pichman
It's that time of year again, where we get to look ahead and finally have some good news. Tech enthusiast Brian Pichman of the Evolve Project will showcase the latest technology trends and how that impact our learning spaces and spaces at home. It is guaranteed to make you forget about all of 2020 and 2021....well maybe that's a new technology about to be released, the MIB memory eraser. Join this exciting webinar and leave with some high hopes of new technology to explore!
Digital Survivors—Death of the Retail CultureAccenture
The landscape of retail players and consumers has been drastically reshaped and the end-to-end consumer value chain is expected to transform beyond recognition in just two to five years. With online commerce growing at four times the rate of the overall industry, many traditional retail giants have made significant investments—upwards of $70 billion USD—in digital channels.So, why do their market caps continue to decline?
This is a presentation delivered by Katie King at the UKInbound tourism conference, on "How can marketing professionals adapt to survive & thrive in a world of AI?"
https://www.ukinbound.org/events/tourism-marketing-in-a-digital-age-seminar/
Internet of Things: From Strategy to Action: Driving IoT to Industrial ScaleCognizant
Full IoT value cannot be realized by connecting a few devices. Organizations need to get beyond instrumentation, and focus on the impact these technologies can have on their business strategies, which will require leadership, vision and partnership.
The 7 Biggest Technology Trends To Disrupt Banking & Financial Services In 2020Bernard Marr
New technology changes the operations and realities of organizations in all industries when it is widely adopted. It's no different with the latest innovation introduced by artificial intelligence, blockchain, and other technology. Here we look at the 7 biggest technology trends that will disrupt banking and financial services in 2020.
The Fascinating Ways PepsiCo Uses Artificial Intelligence And Machine Learnin...Bernard Marr
PepsiCo, one of the world’s biggest food and beverage companies, unlocked the value of data and now uses artificial intelligence and machine learning in its factory operations, to determine product placement and marketing opportunities, uses robots for delivery and to screen potential job candidates, and more.
The Fascinating Ways PepsiCo Uses Artificial Intelligence And Machine Learnin...
Similar to Retail To Real Estate: Why has the real estate industry been slow to adopt AI-assisted information processing in its organizational decision making?
With enterprises putting digital at the core of their transformation, our annual Data Science & AI Trends Report explores the key strategic shifts enterprises will make to stay intelligent and agile going into 2019. The year was marked by a series of technological advances, including advances in AI, deep learning, machine learning, hybrid cloud architecture, edge computing (with data moving away to edge data centres), robotic process automation, a spurt of virtual assistants, advancements in autonomous tech and IoT.
AI in Mobile Apps empowers the evolution of mobile apps by making them intelligent pieces of software that can predict user behavior and make decisions. AI allows mobile apps to learn from data generated by the user. Mobile developers are adapting quickly to changing innovations. read more
AI and Marketing: Robot-proofing Your JobCall Sumo
Artificial Intelligence (AI) provides marketers with deep knowledge of consumer, clients and delivers the right message to the right person at the right time. Here are more depth information how AC affects on Marketing.
Artificial intelligence in the apparel industryThreadSol
Artificial intelligence is set to be one of the biggest business disrupter in the coming decades. But, apparel industry needs to do more to harness this power to achieve profit-driven business.
AI & Analytics Predictions of 2022. InfographicInData Labs
What does 2022 hold for artificial intelligence? Will the AI revolution continue to gain momentum?
This report will provide a look into the future of AI technologies, including:
- Strategic AI predictions and trends for 2022 and beyond
- The current and projected state of the AI market and its value
- Business functions that already benefit from AI implementation
- Industries where AI is making the greatest disruption
- The business value generated by Artificial Intelligence
- Costs of AI implementation and main challenges
Artificial Intelligence can Offer People Great Relief from Performing Mundane...JPLoft Solutions
AI refers to the recreation of human-like intelligence in machines created to function like humans and mimic their actions. Artificial Intelligence solutions can be applied to any device that exhibits traits similar to the human brain, such as the capacity to learn and analytical thinking.
10 trends of artificial intelligence (ai) in 2019Digiture
Many of us are dazzling about AI in 2019 and its upcoming features in 2020. Some of us might be wondering about “Singularity.” Above all, some are still thinking AI is just a puff and no action. All valid questions to ponder.
Artificial Intelligence Best Practices: How AI Models Can Transform Legal and...Anna Kragie
The legal and corporate worlds are buying into the power of AI and machine learning. Now, many industries are becoming increasingly receptive to how to use better data classification methods and AI models to generate better business practices. A decade ago, the legal and corporate worlds needed more convincing about the power of AI and machine learning. Now, many industries — legal included — are becoming increasingly receptive to how to use better data classification methods and AI models to generate better business practices.
20 Useful Applications of AI Machine Learning in Your Business ProcessesKashish Trivedi
A 2017 study from Pew Research found that more than 70% of the U.S. is scared that robots are going to take over our lives. And, while we can’t perfectly predict the emergence of a Skynet singularity, we can say with some certainty that technology is set to take over the repetitive, dehumanizing elements of our jobs instead of putting us out of work. Artificial intelligence (AI) is a strategic priority for 84% of businesses, and in some cases has been used to improve sales team efficiency by over 50%. Even I’ve used AI in the past to generate hundreds of relevant hashtags for social media posts at the click of a button. It was once the stuff of utopian science fiction and huge enterprises, but now practically anyone can take advantage. For this post, we will dive into 20 different applications of AI in the real world.
20 Useful Applications of AI Machine Learning in Your Business ProcessesKashish Trivedi
The fear of robots taking over our lives has been a prevalent concern, with over 70% of the U.S. population expressing apprehension, as highlighted by a 2017 Pew Research study. However, while the emergence of a Skynet-like scenario remains uncertain, it's evident that technology, particularly artificial intelligence (AI), is poised to revolutionize various aspects of our daily tasks, freeing us from repetitive and dehumanizing job elements rather than rendering us obsolete. With AI being a strategic priority for 84% of businesses, its implementation has shown remarkable efficiency enhancements, such as boosting sales team productivity by over 50%. The accessibility of AI tools has expanded significantly, enabling practically anyone to leverage its benefits. In this discourse, we'll explore 20 diverse real-world applications of AI, ranging from healthcare and finance to entertainment and government, illustrating its pervasive impact on modern society.
The overall impact of artificial intelligencekoteshwarreddy7
Artificial intelligence (AI) can have a transformative impact on international trade. Specific applications in areas such as data analytics and translation services are already lowering barriers to trade. At the same time, there are challenges in Artificial Intelligence App Development that international trade rules could address, such as improving global access to data to train AI systems.
Retail Technologies and Retail Trends That will Define The FutureRosalie Lauren
Technology will transform retail resulting in the growth of brick and mortar retail. Check Retail Technologies trends that will help retailers survive.
Artificial Intelligence is already in a dynamically evolving phase by revolutionizing industries one by one. Advent increase in technology affects the business strategies and operations.Artificial Intelligence is already in a dynamically evolving phase by revolutionizing industries one by one. Advent increase in technology affects the business strategies and operations.
From assistants everywhere to customer lifetime value to restoring trust, these are the technology, behaviour, and business trends that are exciting the rehab team this year.
Similar to Retail To Real Estate: Why has the real estate industry been slow to adopt AI-assisted information processing in its organizational decision making? (20)
Tata Group Dials Taiwan for Its Chipmaking Ambition in Gujarat’s DholeraAvirahi City Dholera
The Tata Group, a titan of Indian industry, is making waves with its advanced talks with Taiwanese chipmakers Powerchip Semiconductor Manufacturing Corporation (PSMC) and UMC Group. The goal? Establishing a cutting-edge semiconductor fabrication unit (fab) in Dholera, Gujarat. This isn’t just any project; it’s a potential game changer for India’s chipmaking aspirations and a boon for investors seeking promising residential projects in dholera sir.
Visit : https://www.avirahi.com/blog/tata-group-dials-taiwan-for-its-chipmaking-ambition-in-gujarats-dholera/
3.0 Project 2_ Developing My Brand Identity Kit.pptxtanyjahb
A personal brand exploration presentation summarizes an individual's unique qualities and goals, covering strengths, values, passions, and target audience. It helps individuals understand what makes them stand out, their desired image, and how they aim to achieve it.
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As an Army veteran dedicated to lifelong learning, I bring a disciplined, strategic mindset to my pursuits. I am constantly expanding my knowledge to innovate and lead effectively. My journey is driven by a commitment to excellence, and to make a meaningful impact in the world.
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LA HUG - Video Testimonials with Chynna Morgan - June 2024Lital Barkan
Have you ever heard that user-generated content or video testimonials can take your brand to the next level? We will explore how you can effectively use video testimonials to leverage and boost your sales, content strategy, and increase your CRM data.🤯
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What is Enterprise Excellence?
Enterprise Excellence is a holistic approach that's aimed at achieving world-class performance across all aspects of the organization.
What might I learn?
A way to engage all in creating Inclusive Excellence. Lessons from the US military and their parallels to the story of Harry Potter. How belt systems and CI teams can destroy inclusive practices. How leadership language invites people to the party. There are three things leaders can do to engage everyone every day: maximizing psychological safety to create environments where folks learn, contribute, and challenge the status quo.
Who might benefit? Anyone and everyone leading folks from the shop floor to top floor.
Dr. William Harvey is a seasoned Operations Leader with extensive experience in chemical processing, manufacturing, and operations management. At Michelman, he currently oversees multiple sites, leading teams in strategic planning and coaching/practicing continuous improvement. William is set to start his eighth year of teaching at the University of Cincinnati where he teaches marketing, finance, and management. William holds various certifications in change management, quality, leadership, operational excellence, team building, and DiSC, among others.
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The world of search engine optimization (SEO) is buzzing with discussions after Google confirmed that around 2,500 leaked internal documents related to its Search feature are indeed authentic. The revelation has sparked significant concerns within the SEO community. The leaked documents were initially reported by SEO experts Rand Fishkin and Mike King, igniting widespread analysis and discourse. For More Info:- https://news.arihantwebtech.com/search-disrupted-googles-leaked-documents-rock-the-seo-world/
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Memorandum Of Association Constitution of Company.pptseri bangash
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A Memorandum of Association (MOA) is a legal document that outlines the fundamental principles and objectives upon which a company operates. It serves as the company's charter or constitution and defines the scope of its activities. Here's a detailed note on the MOA:
Contents of Memorandum of Association:
Name Clause: This clause states the name of the company, which should end with words like "Limited" or "Ltd." for a public limited company and "Private Limited" or "Pvt. Ltd." for a private limited company.
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Registered Office Clause: It specifies the location where the company's registered office is situated. This office is where all official communications and notices are sent.
Objective Clause: This clause delineates the main objectives for which the company is formed. It's important to define these objectives clearly, as the company cannot undertake activities beyond those mentioned in this clause.
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Liability Clause: It outlines the extent of liability of the company's members. In the case of companies limited by shares, the liability of members is limited to the amount unpaid on their shares. For companies limited by guarantee, members' liability is limited to the amount they undertake to contribute if the company is wound up.
https://seribangash.com/promotors-is-person-conceived-formation-company/
Capital Clause: This clause specifies the authorized capital of the company, i.e., the maximum amount of share capital the company is authorized to issue. It also mentions the division of this capital into shares and their respective nominal value.
Association Clause: It simply states that the subscribers wish to form a company and agree to become members of it, in accordance with the terms of the MOA.
Importance of Memorandum of Association:
Legal Requirement: The MOA is a legal requirement for the formation of a company. It must be filed with the Registrar of Companies during the incorporation process.
Constitutional Document: It serves as the company's constitutional document, defining its scope, powers, and limitations.
Protection of Members: It protects the interests of the company's members by clearly defining the objectives and limiting their liability.
External Communication: It provides clarity to external parties, such as investors, creditors, and regulatory authorities, regarding the company's objectives and powers.
https://seribangash.com/difference-public-and-private-company-law/
Binding Authority: The company and its members are bound by the provisions of the MOA. Any action taken beyond its scope may be considered ultra vires (beyond the powers) of the company and therefore void.
Amendment of MOA:
While the MOA lays down the company's fundamental principles, it is not entirely immutable. It can be amended, but only under specific circumstances and in compliance with legal procedures. Amendments typically require shareholder
Unveiling the Secrets How Does Generative AI Work.pdfSam H
At its core, generative artificial intelligence relies on the concept of generative models, which serve as engines that churn out entirely new data resembling their training data. It is like a sculptor who has studied so many forms found in nature and then uses this knowledge to create sculptures from his imagination that have never been seen before anywhere else. If taken to cyberspace, gans work almost the same way.
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Retail To Real Estate: Why has the real estate industry been slow to adopt AI-assisted information processing in its organizational decision making?
1. RETAIL TO REAL ESTATE:
Why has the real estate industry been slow to adopt AI-
assisted information processing in its organizational
decision making?
Final Paper
Behavioral Approaches to Strategy
MAN7778
at the
University of Florida
Bryan Dentici
December 12th, 2019
2. Abstract
Artificial Intelligence has been around for almost 70 years, but only in recent years has it become
a major disrupter for many industries due to the convergence of big data, processing power and
cloud computing. This has led to the development of “deep learning”, which allows a type of
computer intelligence that closely mimics human decision-making. In this paper, I take look at
the evolution of Artificial Intelligence, along with two disparate industries: Retail and Real
Estate. These industries have adopted AI at different speeds. Also, each industry has its own
form of resistance and uses for the technology. My theory is that there are forms of technology
resistance by major players in the real estate industry in combination with the long industry
cycles that are causing slow adoption. The research question I will focus on is, “Why has the
real estate industry been slow to adopt AI-assisted information processing in its organizational
decision making?”
Introduction
Artificial Intelligence (AI) is being utilized by organizations in a wide range of industries to
supplement human decision-making. AI has been explored as far back as the 1950’s when
mathematicians such as Alan Turing asked the question, “Why can’t machines solve problems
and make decisions like humans? (Harvard 2018)” In 1956, Herbert Simon, Allen Newell and
John Shaw created the first Artificial Intelligence program that was designed to mimic human
problem-solving skills (Computer History 2019). Additional research over the years has helped
AI to grow and as computers became more accessible, AI technology has been able to help more
and more businesses. Now, it permeates our daily life in the form of algorithms in social
networks, mapping applications, voice recognition and data organizing software. Within
organizations, the application of AI and more advanced machine learning capabilities has been
3. able to add tremendous value. Humans have a capacity limit on the volume of data they can
store and process due to “bounded rationality” (Simon 1956). Because of this, AI has been able
to far surpass human abilities to process information in both accuracy and speed. While humans
have used this AI technology to assist them in the past, AI is now equipped with advanced
algorithms and machine learning that can replace humans in some industries. Unfortunately,
humans commit errors and can be inefficient. Artificial Intelligence can replicate human
operation functions with much more efficiency, which leads to more profits for organizations. In
a study done by Forrester in 2016, they concluded that AI, machine learning, and automation will
replace 7 percent of US jobs by 2025 (Forrester 2016).
Those who work in the retail and real estate industries have very different responsibilities and
tasks. The real estate industry has been much slower adopting AI, whereas the retail industry has
been dynamically transformed by it since e-commerce started growing in the 2000’s.
AI in Retail
The retail industry has completely changed since the year 2000 and the pace of AI innovations
has increased exponentially. One of the casualties of the lightning speed of AI innovation is the
retail salesperson. The retail “salesperson” used to be vital to retailers as they would help
customers find the right product that fitted their needs or preferences. It was about giving great
customer service. Now, algorithms built into e-commerce platforms can offer many more
choices and they can do it much quicker than humans ever could. According to CNN, the retail
sector has lost nearly 200,000 jobs since the beginning of 2017 (CNN 2019). The retail
organizations who adapt to the growth of technology will be able to survive as the industry
continues to evolve. In a 2017 article from the Work in Progress journal, it was stated that
Target now views selling as “routinized” and transactions are judged on the speed of processing
4. rather than the quality of service. Because of the retail industry losing so many jobs due to e-
commerce, CBRE estimated that the demand for warehouse and distribution jobs from 2018 to
2019 was 452,000 (CBRE 2018). Although, what happens when warehouses become
increasingly automated with AI robots? A company in Tokyo called Uniqlo cut 90 percent of its
warehouse staff and replaced them with robots who can inspect clothes 24 hours a day (Quartz
2018). Walmart has also invested in bots to help with distribution. A grocery distribution center
will open in 2020 in Shafter, California that will have bots shuttle perishable goods around the
warehouse without damaging them (Fast Company 2018).
Retailers worldwide are integrating AI into logistics and supply chains. According to a survey
by Statista, 49 percent of respondents expect supply chain AI to reduce costs (Statista 2019). AI
inventory management is also expected to reduce costs for retailers.
In The Future of Retailing, the authors had five categories where technology would be used.
They include the following: To Facilitate Decision Making, Visual Display & Merchandise
Offer Decisions, Big Data Collection & Usage, Analytics & Probability, and Consumption &
Engagement (Grewal, Roggeveen, Nordfalt 2017). Organizations in the retail industry are now
at a point where they must be on the cutting edge of technology because consumer expectations
have changed. Technologies such as Augmented Reality on mobile phones and in-store “virtual”
fitting rooms are currently being developed to show consumers how a product would look within
the context of their home or on themselves. Companies such as PayPal have developed fraud
detection algorithms for digital transactions and since time cost is now at an all-time premium,
new “frictionless” payment systems are being developed by retailers to make the in-store
experience more efficient. Amazon already has their Amazon Go stores with cashier-less
checkout lanes where the items are automatically detected in a consumer’s virtual cart (Amazon
5. 2016). This technology has the potential to increase brick-and-mortar store visits. In 2017,
Mastercard tested an Augmented Reality iris authentication payment system (Mastercard 2017).
How long until we no longer need cashiers in brick-and-mortar retailers?
In a small survey I conducted on retail technologies, I asked the question of how new
“frictionless” payment technologies will affect overall store visits to all retailers. 51 percent of
survey respondents said they “Maybe would go shopping once or twice more per week.” In the
same survey, I asked about Augmented Reality’s effect on consumers for total clothing store
purchases. 24 percent said they would spend $20 to $50 more per month on clothing, and 18
percent said they would spend $51-$100 more per month on clothing. Again, this was a small
survey with a small sample size (n = 50), but it gave me an idea on how consumers perceived
this new technology.
AI has been used for years by companies like Amazon through algorithms that utilize predictive
analysis to suggest what consumers want or need, even before they know it themselves (Forbes
2018). Pricing strategies have advanced through machine learning algorithms from consumer
behavior. This has led to dynamic optimized pricing, which is a vital component in a company’s
profitability (Tryolabs 2019). Smart assistants use data from consumer conversations and
product use cases that mimic a human salesperson. This specific capability has deskilled
hundreds of thousands of retail employees since 2010. In this era of e-commerce, it seems like
delivery positions may be the one area that gets a boost, but not so fast. In 2016, Amazon
announced a partnership with the UK government to test parcel delivery with drones that
delivered up to 5-pound packages in under 30 minutes (EmerJ 2019).
6. Figure 1. Image from “Dice Insights” (2018).
The consumers in the retail industry are the main trigger for how fast it is evolving, There has
been a major industry disrupter in Amazon and many companies have followed them in the e-
commerce model. As consumers continue to demand more convenience and on-demand service,
businesses will continue to adopt new technologies to add value to the consumer experience.
AI in Real Estate
The real estate industry has historically been based on relationships and gut instincts. Most tasks
are handled manually by industry professionals who are resistant to change. There are
applications in the real estate industry that are beginning to adopt AI as it is becoming
increasingly evident that this technology will eventually be adopted by competitors who will
subsequently gain an advantage. Overall, the real estate industry is moving much slower than
other industries when it comes to technology adoption. The industry is still discovering the
usefulness of new AI technology. Some real estate companies are starting to implement new
technologies, while other more progressive firms are investing in the technology themselves (St.
Louis Business Journal 2019) because of the massive potential. The real estate industry has gone
7. through structural inertia (Hannon 1984) when it came to adoption of the newest technology, but
the emergence of industry disrupters has forced firms to take notice.
Artificial intelligence has been able to help tenants in the search process as AI chatbots filter
properties to fit preferences. Zillow has become a major disrupter in residential real estate since
2006 by using machine learning to give consumers the most up to date analytics. They even
have their own proprietary data-driven formula called “Zestimate” (Information Week 2016).
Zillow has continued to implement AI into its platform which helped transform it from a search
box to a virtual assistant. At Zillow’s annual AI forum this year, one of the technologies that
was presented was the use of innovative augmented reality that used “time of flight cameras” to
capture data from real-world locations through neural network 3D point clouds. This dynamic
data was then reconstructed to synthesize an incredibly accurate 3D video of the inside of a home
(Zillow 2019).
For many real estate businesses, these AI-driven technologies will take away a large source of
leverage. In fact, this may be one of the main reasons the industry has been slow to adapt. In the
U.S., transparency is at a relatively high level, but even more transparency will improve
transactions for both investors and the public. Proptech is a name for technology developed for
the real estate industry. According to JLL, $6 billion has been raised between 2018 to 2016 for
proptech startups. In countries like China and Mexico where transparency isn’t as embraced,
innovations in proptech will help standardize operations and create more globalized transactions
(JLL 2018).
Some areas of the real estate industry have adopted proptech tools more than others. Below is a
chart from JLL.
8. Figure 2. Image from JLL’s “Global Real Estate Transparency Index” (2018).
The transaction process in the real estate industry is notoriously stressful for many consumers,
but a startup called Jet Closing has digitalized the entire process with the use of machine
learning. The application will help real estate agents deliver a more “frictionless” experience for
clients (JetClosing 2019).
Even though real estate is the largest asset class in the world, it has only been recently that
industry professionals have begun to utilize the new technology available. The commercial real
estate industry is starting to use new business models, according to a new report from Altus
Group. The following are processes in which AI is being applied as of February of 2019
(Building Design + Construction Network 2019):
· 41% of firms are using automation for benchmarking and performance analysis
· 39% for scenario and sensitivity analysis
· 36% for budgeting and forecasting
· 19% are using AI and machine learning for scenario and sensitivity analysis
· 16% are using AI and machine learning for accounting and property management
9. The Development of Deep Learning
There are three main terms that are often confused but represent subsets of computer
intelligence. They are Artificial Intelligence, Machine Learning and Deep Learning. Machine
learning is a subset of AI that requires structured data to produce output. In the past, humans
were required to manually analyze data to come up with insights. This process was cumbersome
as engineers would copy data over and over, eventually putting together datasets that took a long
time. In the 21st
century, machine learning has helped company productivity by coming up with
real-time analytics, predictive analysis, competitive intelligence and cognitive insights. The
earliest machine learning techniques used for AI were hard-coded algorithms or fixed rule-based
systems, but they were not enough for high-level intelligence such as facial recognition. This is
where deep learning came in.
Deep learning is a subset of machine learning that feeds on many levels of “Artificial Neural
Networks” (ANN).
Figure 3. Image from “The Scientist” (2019).
10. The process of deep learning is modeled after the human brain, which receives messages from
dopaminergic electro-chemical signals from billions of “neurons”. Artificial neural networks are
interconnected nodes exposed to many data points. Below is a comparison between a human
brain and the concept of an AI brain.
Figure 4. Image from Stanford CS231n (2017).
Whereas machine learning needs human intervention with pre-defined criteria, deep learning
networks learn through their own errors (reinforcement learning) as data travels through complex
non-linear layers of neural networks (Hacker Noon 2019). Also, these layers are not developed
by human engineers. In 2006, popular face recognition algorithms were analyzed. The findings
concluded that the current algorithms were ten times more accurate than the facial recognition
algorithms in 2002 and 100 times more accurate than those in 1995 (Dataversity 2019). Deep
learning is being developed to not only mimic the interpretations of a human, but to mimic the
way a human brain learns.
11. Figure 5. Image from “Xenon Stack” (2018).
There is a reason why AI has been around for so long but has only made exponential
advancement the past ten years. The director of AI at Tesla, Andrej Karpathy, stated that there
are four factors that have held back Artificial Intelligence. These were computing power, data,
algorithms, and infrastructure. The advancement of GPUs and data has led to better algorithms
and infrastructure (Medium 2017). Deep learning has had a 175 percent average growth between
2013 and 2016 (Towards Data Science 2019). Below is a graphic of the history of AI according
to the 2019 World Intellectual Property Organization’s Technology Trends report on Artificial
Intelligence.
12. Figure 6. WIPO – 2019 Technology Trends report on Artificial Intelligence.
Deep learning has had a relatively brief history. According to WIPO’s report on Artificial
Intelligence, 50 percent of all AI patents have been published in the past 5 years (Towards Data
Science 2019). The first AI patent was issued in the early 1980s, so our most recent
technological advancements are finally allowing us to see what AI can do when deep learning is
developed.
Stages of Artificial Intelligence Adoption
The retail and real estate industries are at different stages in the technology acceptance model
(Davis 1986), which was adopted from the theory of reasoned action (TRA) model (Fishbein &
Ajzen 1975) that was expanded on to explain user acceptance of information systems (Davis,
Bagozzi, and Warshaw 2989). In Fred D. Davis’s 1989 paper, Perceived Usefulness, Perceived
Ease of Use, and User Acceptance of Information Technology, he states that the most important
13. quality in perceived usefulness to survey respondents was effectiveness. For perceived ease of
use, the most important quality was for the technology to be controllable (Davis 1989). The
retail industry has seen first-hand the effectiveness of technology through the “Retail
Apocalypse” that began in 2010 (The Atlantic 2017). They saw the repercussions of falling
behind in technological adaptation and many companies are now at the Intention to Use or
Actual Usage stages in the TAM as shown in figure7.
Figure 7. Technology Acceptance model (TAM) (1989).
For professionals in the real estate industry, it appears that most of them are at the Attitudes
Towards Use stage and this is what prevents them from moving forward. Why do they not have
the motivation to adopt potentially profitable technology?
Reasons for Slow AI Adoption in Real Estate
In the real estate industry, cycles are relatively long compared to retail. According to Berkshire
Hathaway, real estate cycles have been 18 years since the early 1800’s. The most recent cycle
had begun to rise in 2008. This includes a 7 to 8-year gradual rise, followed by a 7 to 8-year
rapid rise. According to their projections, 2020 will put us in the middle of a boom. Why is this
important for industry adoption of technology? It means that the results from new technology
use are not yet observable.
14. Figure 8. National Association of Realtors (NAR) (2018).
Another reason for slow adoption is the gap between software developers and “domain
expertise”, which is had by those with a deep business understanding, along with many years in
the real estate industry (Urban Land Institute 2016). New technology needs actual “battlefield”
feedback from those in the industry. Because of these long real estate cycles, the professionals
who have a track record of success are not digital natives.
The concept of controlling information in the real estate industry is important to note. Many
business leaders consider this a source of competitive advantage, even if the proliferation of data
would be better for the industry overall. Ultimately, the business leaders in the real estate
industry must weigh the costs and benefits of sharing information. According to the Urban Land
Institute, the “big data” that is currently benefiting other industries, like retail, is not even
available to real estate professionals.
Real estate investors are also different than the venture capital investors that have financed many
tech startups over the years. Venture capital investors have many “losers” in their investments,
15. but because of this, they will also have some tech investments that succeed. Real estate investors
do not invest this way. Real estate investors believe in only putting capital into the intended
purpose: real estate.
Conclusion
The real estate industry and its leaders are very path dependent and “experiential learning”
based. The real estate industries “routines” have persisted over the years in a notoriously slow-
moving industry that has historically rewarded patience. The long business cycles in real estate
means that successful strategies that have been implemented with new AI technologies are not
yet observable. Because of this long process and the industries nature of being dependent on
expertise, exploration strategies have not been used to venture into AI technology to the extent of
the retail industry. In addition, due to the slow-moving nature of the real estate industry, the
conventional real estate firm was not designed for environmental turbulence (Siggelkow and
Rivkin 2005). The increasing complexity of our digitalized world has caused the environment to
move faster than the traditional real estate firm, creating organizational inertia.
The balance in alliance formation search strategies has mostly been across the structure
(partners) and attribute domains, but not in functional domains that may have been useful in
integrating new technology (Lavie & Rosenkopf 2006). Until only recently, real estate firms
limited themselves to investing in real estate, not technology. In the past few years, there have
been more investments in real estate technology, which shows promise of more functional
exploration. As more inter-industry alliances get formed between real estate and technology, the
more innovative the real estate industry will become.
16. The structure of modern real estate organizations will need “Gatekeepers” that have both domain
expertise and digital literacy. This could be in the form of a chief technology officer (CTO) who
is embedded in both interfirm and intrafirm networks. This CTO or “Gatekeeper” for the firm
could be instrumental for the firm developing, adopting, and integrating new technology. This
firm agent will also be the key in cultivating strategic interfirm linkages (Ahuja 2000) between
the tech and real estate industry.
Real estate professionals have needed to make forward-looking decisions based on past
indicators. The industry has long favored stability and not adaptation (Levinthal and Posen
2007). Historically, the limited amount of data available also contributed toward less adaptation.
It has only been in recent years that aggregate data was so available to everyone, but some of
those in the real estate industry still resist the idea of open and free data.
Future research could focus on differences in the generation gaps within the real estate industry
and the tendency for the younger generations to balance more exploration with exploiting
existing organizational abilities. As younger professionals enter the industry, it could contribute
towards more exploration of innovative solutions. There will be also more digital natives who
have real estate expertise.
It remains to be seen if the real estate industry will ever catch up to the retail industry in
technological adaptation. The nature of real estate favors patience for good returns, so this also
applies to the future of the industry. We will need to be patient in order to find out if artificial
intelligence-based technologies will indeed give the real estate industry a rewarding rate of
return or not.
17. Sources
Dovev Lavie, & Lori Rosenkopf. (2006). Balancing exploration and exploitation in alliance
formation. The Academy of Management Journal, 49(4), 797-818. doi:10.5465/AMJ.2006.22083085
Levinthal, D. A., & March, J. G. (1993). The myopia of learning. Strategic Management
Journal, 14(SPEISS), 95.
Levinthal, D. A., & Posen, H. E. (2007). Myopia of selection: Does organizational adaptation limit the
efficacy of population selection? ().ScholarlyCommons. Retrieved
from https://repository.upenn.edu/mgmt_papers/77
Siggelkow, N., & Rivkin, J. W. (2005). Speed and search: Designing organizations for turbulence and
complexity. Organization Science, 16(2), 101-122. doi:10.1287/orsc.1050.0116
Fabris, Peter. Building Design + Construction. “Property technology adoption accelerates in commercial
real estate industry”. February 12, 2019. https://www.bdcnetwork.com/property-technology-adoption-
accelerates-commercial-real-estate-industry
Raines, Tomie. Berkshire Hathaway. “How Long Does a Seller’s Market Last? Analyzing Real Estate
Cycles”. June 1, 2018. https://berkshirehathawayhs.tomieraines.com/Blog/ID/368/How-Long-Does-a-
Sellers-Market-Last-Analyzing-Real-Estate-Cycles
Stecher, Joseph. Urban Land Institute. “Why commercial Real Estate Still Lags in Adopting New
Technology”. June 24, 2016. https://urbanland.uli.org/economy-markets-trends/commercial-real-estate-
still-lags-adopting-new-technology/
Ronzio, Chris. Realtor Magazine. “3 Pillars of Successful Tech Adoption for Real Estate Teams”. April
11, 2019. https://magazine.realtor/technology/feature/article/2019/04/3-pillars-of-successful-tech-
adoption-for-real-estate-teams
World Intellectual Property Organization. “WIPO Technology Trends – Artificial Intelligence”. 2019.
https://www.wipo.int/tech_trends/en/artificial_intelligence/
Rodriguez, Laura. Towards Data Science. “Patenting AI: Let’s start with a history lesson”. October 1,
2019. https://towardsdatascience.com/patenting-ai-lets-start-with-a-history-lesson-af2cbc73a024
Wroblewski, Aaron. Zillow. “Zillow AI Forum 2019”. October 17, 2019.
https://www.zillow.com/tech/zillow-ai-forum-2019/
JLL. Global Real Estate Transparency Index, 2018. “Will proptech and flex space disrupt market
transparency?” https://www.us.jll.com/en/trends-and-insights/research/global/global-real-estate-
transparency-index/will-proptech-and-flex-space-disrupt-market-transparency
Soper, Taylor. Geek Wire. “High-tech home closing startup JetClosing raises $20M to capitalize on
‘tipping point’ in real estate”. June 8, 2018. https://www.geekwire.com/2018/high-tech-home-closing-
startup-jetclosing-raises-20m-capitalize-tipping-point-real-estate/
Fisher, Adrian. Readwrite. “Where Will Ai Take the Real Estate Market in 10 Years?”. August 6, 2019.
https://readwrite.com/2019/08/06/where-will-ai-take-the-real-estate-market-in-10-years/
18. Davis, Jessica. Information Week. “Zillow Uses Analytics, Machine Learning To Disrupt With Data”.
October 14, 2016. https://www.informationweek.com/big-data/zillow-uses-analytics-machine-learning-
to-disrupt-with-data/d/d-id/1327175
Chin, Monica. Mashable. “Can AI make house hunting easier? Zillow is going for it.” May 17, 2018.
https://mashable.com/2018/05/17/zillow-app-real-estate-ai/
Instant Offices. “AI In Real Estate: What Does The AI Building of the Future look like?” February 7,
2019. https://www.instantoffices.com/blog/featured/proptech-trends-in-real-estate/
HousingWire. “Artificial Intelligence in residential real estate: Reality or hype?” September 3, 2019.
https://www.housingwire.com/articles/50044-artificial-intelligence-in-residential-real-estate-reality-or-
hype/
Sallomi, Paul. Deloitte. “Artificial Intelligence (AI) goes mainstream” 2019.
https://www2.deloitte.com/us/en/pages/technology-media-and-telecommunications/articles/artificial-
intelligence-disruption.html
Blume Global. “How Artificial Intelligence Is Transforming the Retail Supply Chain” 2018.
https://www.blumeglobal.com/learning/artificial-intelligence-retail-supply-chain/
Mastercard. Press Release. “Mastercard Eyes the Future of Retail with Augmented Reality Shopping
Experience” October 23, 2017. https://newsroom.mastercard.com/press-releases/mastercard-eyes-the-
future-of-retail-with-augmented-reality-shopping-experience/
Kolakowski, Nick. Dice Insights. “Five Years Later, Where are the Amazon Delivery Drones?”
December 5, 2018. https://insights.dice.com/2018/12/05/where-amazon-delivery-drones/
Faggella, Daniel. Emerj. “Artificial Intelligence in Retail – 10 Present and Future Use Cases”
November 21, 2019. https://emerj.com/ai-sector-overviews/artificial-intelligence-retail/
Tryo Labs. “The Guide to Machine Learning in Retail: Applications and Use Cases” 2019.
https://tryolabs.com/resources/retail-innovations-machine-learning/
CHIRr. Consumer health informatics research resource. 2019. https://chirr.nlm.nih.gov/tam.php
Chandran, Prannoiy. Towards Data Science. “Disruption in Retail – AI, Machine Learning & Big Data”
July 23, 2018. https://towardsdatascience.com/disruption-in-retail-ai-machine-learning-big-data-
7e9687f69b8f
Kapoor, Ajay. Hackernoon. “Deep Learning vs. Machine Learning: A Simple Explanation” February
25, 2019. https://hackernoon.com/deep-learning-vs-machine-learning-a-simple-explanation-
47405b3eef08
Nocholson, Chris. Skymind. “Artificial Intelligence (AI) vs. Machine Learning vs. Deep Learning”
2019. https://skymind.ai/wiki/ai-vs-machine-learning-vs-deep-learning
SaS. “Machine Learning: What it is and why it matters” 2019.
https://www.sas.com/en_us/insights/analytics/machine-learning.html
Foote, Keith D. Dataversity. “A Brief History of Machine Learning” March 26, 2019.
https://www.dataversity.net/a-brief-history-of-machine-learning/
Schmelzer, Ron. Forbes. “Is Machine Learning Really AI?” November 21, 2019.
https://www.forbes.com/sites/cognitiveworld/2019/11/21/is-machine-learning-really-ai/#6053cf7d2621
19. Li, Fei-Fei and Johnson, Justin and Yeung, Serena. Stanford. “Lecture 4: Backpropagation and Neural
Networks” April 13, 2017. http://cs231n.stanford.edu/slides/2017/cs231n_2017_lecture4.pdf
Akst. Jef. The Scientist. “Machine Learning, 1951” May 1, 2019. https://www.the-
scientist.com/foundations/machine--learning--1951-65792
Maini, Vishal. Medium. “Machine Learning for Humans, Part 4: Neural Networks & Deep Learning”
August 19, 2017. https://medium.com/machine-learning-for-humans/neural-networks-deep-learning-
cdad8aeae49b
Akst, Jef. The Scientist. “A Primer: Artificial Intelligence Versus Neural Networks” May 1, 2019.
https://www.the-scientist.com/magazine-issue/artificial-intelligence-versus-neural-networks-65802
Jeffcock, Peter. Oracle. “What’s the Difference Between AI, Machine Learning, and Deep Learning?”
June 11, 2018. https://blogs.oracle.com/bigdata/difference-ai-machine-learning-deep-learning
Kaur Gill, Jagreet. Xenon Stack. “Automatic Log Analysis using Deep Learning and AI” October 21,
2018. https://www.xenonstack.com/blog/log-analytics-deep-machine-learning/
Genc, Ozgur. Towards Data Science. “Notes on Artificial Intelligence, Machine Learning and Deep
Learning for curious people” January 25, 2019. https://towardsdatascience.com/notes-on-artificial-
intelligence-ai-machine-learning-ml-and-deep-learning-dl-for-56e51a2071c2
Davenport, Thomas H and Ronanki, Rajeev. Harvard Business Review. “Artificial Intelligence for the
Real World” February 2018. https://hbr.org/2018/01/artificial-intelligence-for-the-real-world
Tenfold. Becoming Human. “How Artificial Intelligence Will Change Decision-Making For Businesses”
September 1, 2017. https://becominghuman.ai/how-artificial-intelligence-will-change-decision-making-
for-businesses-96d47cde98df
Casey, Kevin. The Enterprisers Project. “How big data and AI work together” October 14, 2019.
https://enterprisersproject.com/article/2019/10/how-big-data-and-ai-work-together
Zipori, Guy. Forbes. “The (Data) Science of The Deal: How AI Will Transform Commercial Real
Estate” January 23, 2019. https://www.forbes.com/sites/forbesrealestatecouncil/2019/01/23/the-data-
science-of-the-deal-how-ai-will-transform-commercial-real-estate/#7da616864200
Swerdlow, Fiona. Forrester. “Future Of Retail: Implementing Artificial Intelligence In 2019” May 23,
2019. https://go.forrester.com/blogs/future-of-retail-artificial-intelligence/
Kejriwal, Surabhi and Mahajan, Saurabh. Deloitte. “Infusing data analytics and AI” June 18, 2019.
https://www2.deloitte.com/us/en/insights/industry/financial-services/data-analytics-commercial-real-
estate-investors.html
Bayern, Macy. Tech Republic. “How AI can save the retail industry” September 13, 2019.
https://www.techrepublic.com/article/how-ai-can-save-the-retail-industry/
Trivedi, Swetketu. Data Driven Investor. “How AI will Change the Retail Industry in 2019” March 13,
2019. https://medium.com/datadriveninvestor/how-ai-will-change-the-retail-industry-in-2019-
c817091c6306
Sherborne, Jes. Flarrio. “Transforming Commercial Real Estate with AI” 2019.
http://flarrio.com/commercial-real-estate-ai/
Kwan, Nicole. Towards Data Science. “The Hidden Dangers in Algorithmic Decision Making”
December 1, 2018. https://towardsdatascience.com/the-hidden-dangers-in-algorithmic-decision-making-
27722d716a49
20. Bain, Marc. QZ. “Uniqlo replaced 90% of staff at its newly automated warehouse with robots” October
10, 2018. https://qz.com/1419418/uniqlo-cut-90-of-staff-at-one-warehouse-by-replacing-them-with-
robots/
Melendez, Steven. Fast Company. “Amazon and Walmart add more robots, but insist they won’t
terminate jobs” December 15, 2018. https://www.fastcompany.com/90279838/amazon-and-walmart-
add-more-robots-but-insist-they-wont-terminate-jobs
Forrester. “Robots, AI Will Replace 7% Of US Jobs By 2025” June 22, 2016.
https://go.forrester.com/press-newsroom/robots-ai-will-replace-7-of-us-jobs-by-2025/
Grewal, Dhruv and Roggevee, Anne L. and Nordfalt, Jens. “The Future of Retailing” January 12, 2017.
Journal of Retailing 93(1,2017)1–6
Lai, PC. University of Malaysia. “The Literature Review of Technology Adoption Models And Theories
For The Novelty Technology” JISTEM J.Inf.Syst. Technol. Manag. vol.14 no.1 São
Paulo Jan./Apr. 2017
Lezin, Nicole. ReCAPP. “Theories & Approaches: Theory of Reasoned Action (TRA)” 2019.
http://recapp.etr.org/recapp/index.cfm?fuseaction=pages.TheoriesDetail&PageID=517
Anyoha, Rockwell. Harvard University. “The History of Artificial Intelligence” August 28, 2017.
http://sitn.hms.harvard.edu/flash/2017/history-artificial-intelligence/