For decades, consumers have relied on friends and family, product reviews and tastemakers when making purchasing decisions. A loved one could recommend a particular brand of tools that’s worked well over the years. A consumer watchdog publication could inform and educate on which car models offer the most reliability. A fashion magazine could highlight the latest trends that speak to any style. But while each of these different influencers remains relevant to today’s buyers, shoppers seeking out buying advice are increasingly being guided by artificial intelligence.

Through sophisticated AI, retailers are diving deeper into personalization by building solutions that suggest the best products for a user to purchase bolstered by data-driven insights.

Thanks to powerful AI-driven supply chain management, retailers can easily track what’s in store, what’s being shipped and what’s in the warehouse; ensuring customers can get what they want when they want it. But to create a more personalized shopping experience, retailers are also putting together better product collections, embracing trends like “showrooming” and crafting entirely new ways of shopping.

Here’s a look at how AI-driven personalization is transforming brick-and-mortar retailing:

1. b8ta

Retailers long maligned the trend of “showrooming” — that is, trying out a product in-store only to make an eventual purchase online. AI-driven supply chain management has allowed omnichannel retailing to alleviate some of these fears, but new retailers like b8ta have embraced this trend even further by building new stores around the showrooming concept. Offering retail-as-a-service, b8ta is an open-concept store that offers companies a flexible way of selling through brick-and-mortar locations. Companies can showcase products in b8ta stores from online brands that desire a physical presence.

For consumers who wish to purchase something online but also want to see it in person, b8ta changes the game. And for online retailers with a wide range of SKUs or a limited desire to expand into physical retail, b8ta offers the best of both worlds by showcasing products for limited amounts of time. Combined with AI-gathered data for personalized product targeting, a manufacturer could take advantage of b8ta by offering a small sample of their most popular products that customers wish they could try out in real life.

2. Amazon 4-Star

If you’re buying a kitchen gadget, how do you know it’s the best kitchen gadget? Well, if you’re Amazon, you know it’s the best because it’s got a wealth of customer purchasing data behind it. This includes star ratings, which lets users rank products after they’ve been purchased.

That’s the core concept behind Amazon’s newest retail store in New York City: Amazon 4-star. Carrying a curated selection of products that have all received large amounts of four-star ratings, Amazon uses its sophisticated product recommendation engines to bring its bestselling, most popular items into physical stores.

By offering a hand-picked selection of products that are beloved, trending or hidden gems, the service allows customers to shop from a collection of highly personalized recommendations in a brick-and-mortar setting.

Considering 35 percent of Amazon’s revenue comes from its AI-enhanced product recommendations, it’s a profitable shortcut to give customers what they already want.

Selling only the top-rated products might also be the right approach for adjusting an existing retail strategy. In early 2018, home furnishing retailer Crate & Barrel shuttered all physical locations of its children’s furniture chain The Land of Nod and began offering a smaller, curated collection of the same products under its in-store label, Crate & Kids. For Crate & Barrel, it became clear that offering a more personalized selection of products to its customers was more valuable than propping up an underperforming retailer that featured wider selections.

3. AlgoFace

Buying new makeup can be a long and messy process. Dropping by Sephora or the makeup counter at Macy’s means waiting for an associate to help you apply lipstick or eyeshadow to find the perfect color — from a tube that’s already been used by somebody else.

AlgoFace is making this process simpler (and far more sanitary) through its virtual-makeup SDK, which is available for makeup retailers to build into their apps. Shoppers can virtually apply an endless array of makeup shades to a live video of their face. Their AI-driven augmented reality interface makes it look like users are actually, physically wearing the makeup they’re thinking about buying.

The result isn’t just a highly personalized experience that lets users try out makeup combinations with no mess: It’s an incredible way to cut down on costs by saving on makeup samples. As for customer experience, this means being able to try out different looks in a mobile app or at a physical location.

 

Article originally published on Medium and reposted with permission from Humans for AI.

Image credit: Simply Mac Computers

While artificial intelligence may bring to mind sci-fi notions of robotic butlers and automated factory workers, the truth is in many ways far more interesting. The rapid growth of machine learning has provided major tech companies with more ways to predict the behaviors of their customers while at the same time providing those customers with products and services that accurately match their particular needs. Here are some useful ways tech companies are incorporating AI into their tech.

A Smarter Personal Assistant

When Siri was introduced in 2011, it was a revelation in the tech world. While mobile phones had long been a primary means for people to interact in their personal and professional lives, Siri was created as a means to unify the internet of things via a smart and responsive virtual assistant who would respond to the needs of the users.

In the years that would follow, Microsoft and Samsung would introduce their own spins on the concept through the implementation of Cortana and Bixby. But technology has to been growing to meet the demands of the consumers, and these companies are looking towards the future by creating virtual assistants that are more personalized and natural.

Humans are naturally social creatures, and the more lifelike an assistant is, the more likely humans are to take their advice and incorporate them into their daily lives. In a demonstration, Google showed what this integrated assistance might look like when their Duplex assistant scheduled an appointment via phone using a remarkably human voice. Engineers are working hard to create assistants that don’t just mimic human language, but that also imitate the tics and eccentricities in language.

The Future of A.I. Virtual Assistants

Recent studies suggest a bold future for this brand of integrated assistant services. Analysts predict that within five years, over half of customers will be deciding on the services and products they want to purchase based off of the recommendations of artificial intelligence, and most of these artificial intelligence services will be integrated into our daily lives without a screen.

A.I. could become a natural and seamless part of our daily experience, perhaps even as common as owning a mobile phone. In terms of how businesses are run, analysts look a decade into the future and envision virtual assistants that drive the productivity of employees 24 hours a day. Where fiction writers once envisioned a future where artificial intelligence replaces humans in the labor force, the new model predicts a future where the two are synthesized together in a sort of symbiosis.

Google Trying to Lead the Charge

Google has become a pervasive presence in modern life, and there’s little doubt that they’re looking to get in on the ground floor of the A.I. boom. A recent report has coined 2018 as the “Year of Artificial Intelligence” for Google, and that’s mostly taking place at Google AI, a platform designed to make Google services cleaner and more accountable. This can be seen in the form of both Google Home and Google Assistant, and as usage of these services grow, and more data is collected, Google’s artificial intelligence is only expanding in its capabilities. At the heart of this understanding is DeepMind, a neural network bought by Google which shows the true capacity for machine learning and contributes to many of Google’s developments in artificial intelligence.

Therein lies the strength of artificial intelligence. Increased data leads to exponential intelligence, and as adoption increases, so do capabilities. Customers throughout the world seem to have developed a taste for artificial intelligence, and it’s unlikely these trends will be slowing anytime soon.

Artificial Intelligence, or AI, has changed the landscape of many areas of our lives, such a medical diagnosing, education, and manufacturing. Technology experts explain that AI is when a trained computer is given data, and then makes decisions based upon that information. This process will change many jobs that used to be only performed by humans.

AI is changing how consumers get real estate loans. Often, a mortgage lender will offer a variety of different types of loans (FHA Home Loan, VA home loans, first-time buyer specific loans, etc) to those going through the mortgage process. With that information, the potential homeowner could decide which loan would match their particular needs. The borrower would apply for the loan, fill out forms, and bring in supporting documents. The lender would verify the information and try to catch any issues that might present a problem with the loan.

AI could be fed the borrower’s information. The borrower has to declare income and debt. They must also bring in paycheck stubs, and tax returns. This data could be absorbed and studied by AI, and if the AI found anything out of the ordinary, it could flag the issue. The mortgage lenders would be alerted, and they could find out if there were a reasonable explanation for the discrepancy. The parameters would already be set just as they are in today’s mortgage lending world. For example, if a person has too much debt, the loan process is halted. Imagine the time it takes a lender to scour that information. A computer could do the same job efficiently.

The future of AI technology in the mortgage field might have the potential borrower enter their own numbers and upload the supporting papers for AI to reference. This could save money on loan processing fees and make the loan more affordable to the homebuyer.

The AI computers may soon learn how to predict the dependability of the potential borrower. This would reduce the risks that lenders take and may bring down interest rates for low-risk clients. It would obviously save the lending institution money if the system could predict high-risk clients.

Will AI take the place of mortgage lenders and institutions? It is hard to predict. For now, we need humans to ease many first-time home buyer’s minds, and lenders are there to answer any questions. Someday, the system may be able to take all of the information, display all of the loans available for that particular situation along with the pros and cons of each one, and then process the documents for closing.

Just a few years ago, Artificial Intelligence (AI) was just something geeks talked about. It was out there in the future, lumped in with science fiction. But, the times are changing—and fast. These days AI is being applied to pretty much every industry and is transforming the way we think about getting work done and living our daily lives. Here are 4 industries in which AI is making its presence felt:

1. Medicine and Healthcare

The medical field has been revolutionized by artificial intelligence. It’s way ahead of the curve already in actively using AI in everyday situations in order to better our lives. There are endless AI applications in treating patients and developing new medicines and cures, and in streamlining and handling patient records.

For example, because it takes so long to develop and test a new drug, medical researchers are using AI systems to help them explore the myriad of ways that new drugs can be developed and processed through the FDA system faster. So too, in the immunology and genetics fields, using AI, medical personnel can do body scans to find cancers and heart disease symptoms faster and more precisely, thus saving lives.

2. Entertainment

In 2014, when augmented reality was first starting to be talked about in technical circles, it seemed like a fad. How could AI be used to change the way that we see reality, to lay another level of reality over the one we walk through in our daily lives?

And then Pokemon came out with the Pokemon Go app and overnight the game became a global sensation. Incorporating GPS, people of all ages started using their smartphones to go out and play a game in public with others. This hyper-social form of entertainment did more than just delight though. It gave people a real taste of just what AI is capable of creating. Look to see many more uses of AI in the augmented reality and entertainment field in the next few years. Big players like Sony, Amazon, Google, Apple and Facebook—and the Hollywood studios—are counting on it.

3. Communications and Marketing

“Hey, Alexa, tell me where I can get Mexican food in my neighborhood.” One request and you get all the information you need automatically, spoken out loud to you. AI-driven communications technologies like this help people in their daily chores and are especially life-changing for the blind and disabled.

In addition, within the digital marketing field, a small business can increase its sales with current customers and have conversations with prospective customers just by adding a simple AI chatbot to their website or social media account. Re-marketing ads, enhanced with AI, also help marketers to increase their conversion rates.

4. Transportation

Twenty years ago, when the average person thought about what life would be like in the year 2020, they often imagined flying cars. Though that might not be a reality in a few years, the way that AI is changing transportation is mind-boggling.

Today, as you read this, self-driving vehicles are being tested and refined by major U.S. and foreign automakers, all powered by AI. And the trucking industry is being altered forever. What’s being referred to as “autonomous driving technology,” is starting to be used to develop the transportation industry of the future. A recent study by PricewaterhouseCoopers says that by 2025, fleet owners could achieve savings of 15% or more a year by using AI-controlled long-haul trucks.

The medical field has been revolutionized by artificial intelligence, as well as the Entertainment, Communications and Marketing, and Transportation fields. These four industries represent some of the most visible and viable AI applications to date.

So, get ready for a wild ride. Buckle up, be observant, and be open to all of the amazing changes ahead brought to us, courtesy of AI.

 

If you run a business, it is crucial that you cut your costs and increase your profits at every turn. However, this is often easier said than done. Here are five areas that businesses often overspend in to help you realize where you might be losing money that you don’t need to:

Printing

While much of the modern business world is using online tools to complete specific business processes, there is still a strong need for paper and ink. Because of all its advantages over digital assets, in addition to being legally required in certain fields, it is not showing signs of going away. Save money in this area by finding better prices for printer ink for your machines.

Cloud Apps

Cloud software is all the rage right now in business. However, don’t let that convince you to overpay for software that you can get cheaper elsewhere. Ask around to see if you can try out a trial version before investing in a subscription or service. Also see if you can replace some of your expensive apps with a free or reduced price version or look for deals on lifetime licenses for business software on sites such as AppSumo or StackSocial

Security

Security is often one of the most important things you can implement in your business. Ensuring that you and your employees are safe is of utmost importance, but not only that, but your business’ data and information. So how can you cut costs while also keeping a high level of security? The majority of pricing comes from installation and set up, which can be deeply cut if you opt for more cloud based option. You can also use automation software to monitor your network and report errors directly to you in real time.

Office Space

Long gone are the days where you needed giant buildings with glass atriums to attract clients. Instead, modern consumers like a more streamlined look which is convenient because it’s a lot easier to manage and costs less. Show them that you care more about the service you provide than the office visuals by downsizing to something more modest so you can reinvest cash into your business. Coworking spaces such as WeWork also offer new options for distributed workforces or even traditional offices by providing beautifully designed spaces from hot desks to private offices. 

Air Conditioning and Heating

You would probably never spend the same kind of money heating or cooling your home as you do in the office. Still, you want to keep people comfortable. The solution is not to crank the temp down, but instead to upgrade your insulation. Your windows are one of the most significant sources of energy loss in your office. If you get more energy efficient varieties, they will easily pay for themselves over time.

When it comes to getting more growth for your company, there are two ways to do it. Firstly, you can cut down your costs. Secondly, you can increase the revenue you generate. If you stop spending on unnecessary items or reduce your spending for them, then you can save a lot of capital that can be leveraged for other things in your business now and into the future.

We’re not exactly at the point where it’s possible to call up your local real estate agent and have your pick of “smart homes” that are instantly tricked out with all of the latest technological advances. But what you can do is make some updates to your existing home to make it more efficient, safe, convenient, energy efficient, and comfortable. Many of these upgrades and devices have been started to be implemented in the business sector, but they’re slowly moving into personal homes and making our lives just a little easier all around. Here’s what you need to know about the process of converting a home you already like into one that’s a bit “smarter” thanks to an assortment of gadgets, devices, cameras, and sensors.

Be Prepared Budget-Wise Before You Get ‘Smart’

Before you start making your smart home plans, take a moment to consider how much you can invest in this process. Consider that the national average cost for the installation of a home automation system is just over $1,100, although the typical range is from nearly $400 to almost $1,200. If cost is a primary concern, you can always make your home “smarter” in stages with smaller, more affordable updates.

Many Features Can Be Accessed Remotely

One of the perks of smart home technology is the ability to control many different system functions remotely. For instance, you can monitor your home from your phone with apps like ADT Pulse to view live video from your mobile devices or virtually turn your home’s alarm on and off. Similar apps can be used to keep track of your home’s temperature or turn lights on and off. You can even get remote alerts when someone is at your door or when your child comes home from school.

You’ll Need a WiFi Connection with Sufficient Power

The primary requirement for a smart home is a wireless (WiFi) connection with enough power to reach all of the devices and systems you have set up throughout your home. In order to know what kind of WiFi setup you’ll need, make a list of what products and systems you’ll want in your home and where the required components will be placed or installed. If you add some other smart options later, make sure your WiFi is still sufficiently strong enough to transmit the necessary signals.

Don’t forget about smart appliances. Smart coffee makers, for example, are linked to your smartphone. So, all you’ll have to do is wake up and choose your preferred brew before you even get out of bed. Smart refrigerators are also generating more interest among homeowners today. No matter what you want included in your smart home, take comfort in knowing that your technology updates can be transferred to another home should you decide to move in the future.

 

As the use of AI enabled platforms continue to grow within all industries and markets, we will also see a greater level of AI platforms being adopted by retail companies. There are four factors that will influence the adoption of AI in Retail:

Think Big, Start Small

Retailers who adopted AI early are already benefitting from this innovation. Retailers that are new to using AI in their day-to-day operations will benefit from starting with the “basics.” It is important for retailers to remember it is not about solving all their problems at once, but to focus on fixing one problem at a time. People often get caught up in the task at hand or distracted with too many problems. It is very important to remember the strategy of “test and learn.” Make one adjustment towards personalization for the consumer and test it before you move on to the next.

AI Boosts Conversions, Revenue, and Customer Satisfaction

IDC Retail insights predicts by 2019 40% of retailers will have developed a CX architecture supported by AI. IDC forecasts customer satisfaction scores to rise by 20%, employee productivity to rise by 15%, and inventory turnover to rise by 25%. This is all going to be possible due to AI paired with AR and IoT data which will give retail companies the ability to hyper-personalize each customer’s experience.

Mobile Devices Will Help AI Flourish

The vast majority of the population has access to mobile devices and conducts most their activities on these devices. This allows for a huge adoption in AI on this platform. The data collected from all these mobile devices will allow companies to improve their customer’s experience. One company that is already successfully implementing an AI platform is Starbucks. One thing their AI platform does is recommend specific orders for customers based on their prior purchase history. AI will play a big role influencing AI adoption in retail.

The Lack of Knowledge and Cultural Biases Will Hold Back the Adoption of AI

Two problems many companies face is the lack of knowledge and their cultural readiness for innovation within the company. These become a problem when people within the company are afraid to innovate new technology they don’t understand. Another hurdle retailers have to jump over is the cost of implementing an AI platform into their existing system.

Download the full report HERE

December 14, 2017, TechTarget

For enterprises to benefit from AI tools and techniques, experts at AI World stressed that technology needs to be grounded by a tight focus on how it can improve business goals.

There should be zero separation between an enterprise’s business objectives and its AI implementation

We’ve all seen the hype around Enterprise Big Data and AI build up over the last few years, culminating in a record year of investments, conferences and implementations in 2017. But how real is AI when it comes to building value for your business today and over the next five years?

Although we are certainly many years away from a human-like AI as we see in the movies; today, narrow or domain-specific AI technologies are already making an impact on bottom lines. Companies that have been smart about adoption and able to quietly implement AI-aided solutions into various functions such as Demand Planning and Inventory Management, Back Office Processes, Sales and Marketing are reaping the benefits.

Because AI can help companies find competitive advantages, demand is increasing at an incredible pace. New companies offering AI enabled software, and other technologies seem to pop up almost daily. Considering the amount of money and brainpower poured into AI research, it won’t be long until commercializing and monetizing data using AI as well as transforming internal processes becomes a necessity to remain competitive.

According to the recently published Teradata report State Of Artifical Intelligence For Enterprises, the majority  “see AI as being able to revolutionize their businesses, automating repetitive processes & tasks and delivering new strategic insights currently not available.”

But with most enterprise software initiatives taking on average 21 months to implement and with Big Data and AI being at the complex end of the spectrum, it is no surprise that 91% see barriers ahead with lack of IT infrastructure (40%) and lack of talent (34%) as the most significant.

So how do you quickly adopt AI successfully across different business functions, driving real and immediate ROI?

AI as a Service

AI Software As a Service (SaaS) adoption is a clear trend that is taking hold in enterprise technology stacks. Adopting SaaS solutions can help companies smooth out their revenues, leading to more resilient and flexible organizations, ultimately allowing a company to deliver better service and products to their clients. With a shortage of talent in this arena and the large data sets required to effectively train artificial intelligence algorithms and implement them into production software, the SaaS model has clear advantages versus trying to develop all capabilities in-house.

Definitive Advantages

The reasons for moving to SaaS offerings can be different for each organization. One of the primary drivers is the potential to create a technology advantage over established competitors and potential disruptors.  Others find they’re increasingly dissatisfied with the way their legacy functions and processes run, and want a better and faster way to see improvements.

Services are defined based on business results and can be expected to produce value quickly, be flexible, implemented quickly, and paid for based on value, business outcomes, or on a seat/consumption basis. This approach leaves more room for pivoting if the ROI is not there as promised, in contrast to traditional capital investment projects where teams often fall prey to the sunk cost fallacy or have a hard time measuring the ROI of their investment.

Enterprises that transition to this model will have a definitive advantage over those that don’t. Companies that don’t shift to aaS models will see their ability to compete diminished, and the same can be said about leveraging AI enabled technologies such as Robotic Process Automation and Automated Insights Generation to name a couple of tangible applications of AI in the enterprise today.

A SaaS tech stack also offers a company greater agility. Traditional industries are consolidating amid increasing mergers and acquisitions, and that means becoming more agile and lean to compete and continue to grow. Service-based models allow companies to trim infrastructure, creating flexibility to scale up or down depending on business needs.

A SaaS model also enables better analytics to derive business insight and help make performance improvements. With clear and contained costs and sometimes built-in analytics capabilities, it is easier than ever to evaluate business results and ROI of investments in services vs. traditional Capex expenditures.

Getting There

Determining how to start adopting AI technologies as well as transitioning to a SaaS and multi-cloud based stack is not necessarily easy. Where to start? With a single problem, department or business need, or do you embark on an enterprise-wide effort?

It can be as simple as starting small with low-hanging fruit and then expanding from there. Is there a department that is last on the priority list for IT but could make some significant gains if given the right tools today? Is there an apparent cost, margin or process that can be identified for measurable improvement? Companies that have seen immediate success often start small and then build on that success. Technology moves too fast these days to allow for extensive planning and execution timelines.

No matter how they get there, in the long run, businesses that transition to service-based models have incomes that are more consistent over time, allowing them to make better and more agile decisions that lead to robustness, flexibility and therefore long-term sustainability.

There are many trends coming to the foreground of AI, machine learning, and business intelligence. This article will be talking briefly about some of these trends and why they are coming to light. A link to the in-depth report by Tableau can be found at the bottom of the page.

Do not Fear AI

Is AI the destructive force that will destroy all jobs and the world as we know it? The media and Hollywood have depicted AI as such, however this is not the case at all. At this point in time, machine learning and AI has become a daily tool in business intelligence. These tools are giving time back to their human Analyst counterparts. Analysts are using machine learning and AI software to better understand their company’s data in a more timely fashion.

Liberal Arts Impact on AI

In the upcoming months Liberal Arts will be playing a bigger role in the building of AI and machine learning software. Data scientists are realizing they not only need the data analyzed to be accurate but also tell a story that anyone can understand, including those without a technical background.

NLP (Natural Language Processing) Promise

NLP refers to the way we interact with the AI through the UI (user interface). Companies are beginning to want all level of employees to have access to the data provided by their AI software. The problem many of these companies face is that most of their employees do not have a technical background and no idea how to query a piece of data. This is where NLP comes into play; AI software can process queries in natural language instead of using specific codes. e.g. I want to know the Sales for Item “001”  by day at Store “2045”

Multi-Cloud Capabilities

The move to multi-cloud storage is becoming an ever-increasing desire within big companies. Companies don’t want to be limited to one storage method that may not provide the best performance for their data needs. Though multi-cloud architecture has many benefits, it also has its costs, one of which being the actual overhead cost of running this type of multi-cloud environment.

Rise of the CDO (Chief Data Officer)

With understanding data and analytics becoming a core competency more and more companies are creating a position of CDO. This position allows them to join the C-suite with the CEO, CTO and CIO. This new position gives the CDO the ability to attend the C-level meetings and actually affect change within the company. Due to the creation of the CDO position, companies are showing just how important it is to understand their data and manage it successfully.

Crowdsourcing Governance

Crowdsourcing governance is a fancy term for allowing customers to shape who has access to specific data within a company using self-service analytics. It gets the right information into the right hands while keeping that same information out of the wrong hands.

Data Insurance

Data is more valuable than ever. We have seen countless data breaches over the last few years and will most likely see many more. With customer data becoming so valuable we are going to see a rise in data insurance. This insurance will protect companies from being responsible for a breach of their customer data.

Data Engineering Roles

As data analysis software continues to grow in use and value we will see a rise in data engineering roles over the next several years. Data engineers will begin to transform from more architecture-centric roles to a more user-centric approach within their organizations.

Location of Things

“Location of things” is in connection to IoT (internet of things). We are seeing companies trying to capture location-based data from IoT devices. Gartner, predicts there will be 2.4 billion IoT devices online by 2020. The problem is that companies are trying to collect and compile all this location data within their internal data structures, while most of these structures are not capable of accepting that quantity of data. This is going to lead to great innovations for IoT data storage.

Academics Investments

With data analytics growing in all industries the demand for future data scientists will continue to grow. Due to this high demand for data engineers and data scientists we will begin to see more and more universities offering some sort of academic training in these categories over the next several years.

 

Read the full report by Tableau Here:

https://www.tableau.com/reports/business-intelligence-trends#ai