One of the most important things about our culture at is that we value diversity of thought and backgrounds because we believe it gives us a competitive and creative advantage.

The real strength of a team comes from its diversity in creativity. All people are creative and imaginative in their own ways— embrace and foster your team members’ individual creative thinking to help deliver great experiences and customer satisfaction.

Jason Kummerl, CTO

To that end I will be attending VerveCon 2019 a conference for Women Leaders in Tech in Santa Clara, CA next week Tuesday, May 7th.

VerveCon aims to empower women in technology and build a community that helps them in their career path and prepares them to be an impact maker, to solve the real problems, to prepare them to take tough decisions.

I will be giving a talk on the State of Enterprise AI and participating in a Career panel titled Is Mentoring the Be-all and End-all for Career Growth?

Hope to see you there!


P.S. You can register here and use code VC-Nikki for a $200 discount

Amjad Hussain, CEO and Founder of, shares his insights on the relationship between data, artificial intelligence and how the two can combine to offer a new form of value in the modern economy.

“Observable, Accessible, and Interesting” are the attributes one must add to a Data Universe according to our founder, Amjad Hussain, CEO of If this can be accomplished, you are well on your way to helping Data become the New Oil.

A new way of architecting the data, brain and workflow layers are the keys to maximizing the utility of the Data Universe and achieving competitive advantage. Companies that adopt this new way of thinking will undoubtedly establish a lead in the market and realize the goal of leveraging Data as the New Oil.

Insights Success Magazine has once again included in it’s editorial list of companies to watch. We are working hard on one of the most innovative AI platforms out there and appreciate the shout out!

Read more about what we are working on, what drives us, and what’s to come in 2019 in the full article: Where Artificial Intelligence Meets Enterprise Decision- Making

Amazon’s Alexa platform may be helping users get accustomed to voice-driven interactions, but its underlying purpose isn’t just to help get weather reports or control smart-home devices. As a storefront, first and foremost, Amazon’s original intention with Alexa places a virtual assistant at your fingertips or in your home to help you shop.

Through AI tools like natural language processing, Alexa has led the retail industry in its rise towards conversational commerce. As if a customer was interacting with a clerk in a retail store, conversational commerce makes it possible for users to engage with software to research, purchase, or get customer assistance with products and services across a wide range of industries.

With Alexa, for example, users can ask any Alexa-enabled device to add an item to an Amazon shopping cart, set a purchasing reminder when a product is running low, or carry out a complete purchase without having to access a shopping cart. The result is a seamless conversational experience that enables consumers to carry out transactions as quickly as it takes to speak a sentence.

On other chat-based platforms, conversational commerce makes it easy to engage with brands without the need for human intervention. AI-based chatbot technology gives users a recognizable chat-based interface to ask product questions or purchase items. Chatbots also don’t always require their own separate app download, offering interactions over popular platforms like Apple’s iMessage, Facebook Messenger, and Google Home.

For many common user requests, it’s possible for chatbots to offer better user experiences with more efficiency than a phone call or email to customer support. A product return, for example, could be automatically coordinated through a chatbot instead of having to go through the lengthy process of speaking to a representative for return authorization.

One of the clearest models of the future of conversational commerce is Jetblack, the product of Walmart’s Store №8 tech incubator for the future of retail operations. Jetblack is an entirely chat-driven store currently serving Manhattan, where users can make shopping requests, get customized recommendations, and process returns.

While an exclusively chat- or voice-based shopping experience for all scenarios may never completely replace the in-person experience, conversational commerce will continue to grow as an added method of convenient and efficient communication. As users continue to become more accustomed to engaging with chatbots and voice-driven interfaces, expect more innovations in the space as brands continue to develop their unique conversation-based solutions.

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

The marriage of artificial intelligence (AI) and e-commerce is growing stronger than ever before — and it’s changing the way users find and purchase consumer goods across nearly every industry. Largely pioneered by Amazon’s Real-time Product Recommendations, sophisticated AI is used to measure and track a user’s purchasing habits to determine other products they might be interested in buying. These days, retail’s use of data is giving consumers more of what they want, when they want it.

What’s more, companies are increasingly finding ways to cut out the middleman in order to offer their own line of direct-to-consumer goods. Amazon itself already has already amassed more than 76 private-label brands, taking its AI-driven insights into the real world by guiding customers to purchase its own in-house product lines. For products purchased on a regular basis, such as cleaning supplies or toiletries, Amazon boosts its own customer relationship even further through its Subscribe & Save program, offering discounts to users who commit to purchasing on a recurring basis.

These initiatives all add up to a retail bet that’s placed firmly on personalization through direct-to-consumer subscription services. An early wave of this trend was seen with online-only retailers like mattress company Casper. These types of retailers eliminated physical stores altogether in favor of a digital product selection available for in-home delivery.

The next evolution brought forth brands like online beauty sampler Birchbox, which gives users the chance to subscribe to a rotating box of cosmetic products to match a user’s predetermined tastes. Even large, traditional retailers have decided to jump on the bandwagon: One example is babyGAP‘s decision to offer subscription options to its legions of parent shoppers.

But now, armed with insights gleaned from AI, companies are further refining their direct-to-consumer subscription models to offer products meant to appeal directly to a consumer’s interests. Meal kit subscription provider HelloFresh uses machine learning to determine which foods its subscribers prefer, creating a feedback loop that tailors its menu to better recommend meals its customers will enjoy.

And at Yoox, a private label online clothing retailer, the entire business model is predicated on AI. The company combines fashion trends from social media with on-site sales data to curate its very lineup of clothing.

What’s in store for tomorrow’s retailers? It seems the combination of AI, hyper-targeted advertising and the subscription model means that soon enough, retailers will know their customers better than they know themselves.

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

Data & Society, a New York City–based research institute focused on social and cultural issues arising from big data and automated technologies, recently released a new report on the future effect artificial intelligence (AI) poses to the retail industry. “AI in Context: The Labor of Integrating New Technologies” analyzes how AI — despite fears about its potential to replace human labor — is setting the stage for workplaces that will continue to rely on human beings to carry out different tasks.

Amazon’s cashier-less retail store, Amazon Go, sparked several fears about a retail future bereft of human labor. Relying on a skeleton crew of human staffers to restock shelves or bake food, Amazon’s automated store seemingly figured out how to seamlessly create a physical retail experience that doesn’t depend on cashiers or other frontline workers.

But Amazon wasn’t the first company to begin the process of automating retail labor — it was the now-ubiquitous self-checkout machine used by grocers and convenience stores around the globe. After the self-checkout expanded in use throughout the 1990s, many speculated that it would render cashiers and related retail laborers obsolete (similar to the speculations about Amazon Go).

Ultimately, those fears proved to be misguided. The adoption and usage of self-checkouts has fluctuated over the past few decades, as users grew frustrated with unintuitive interfaces and cumbersome checkout procedures.

In turn, the skills and responsibilities of a cashier have adapted. Rather than simply ringing up a purchase, cashiers must now fill customer service roles by troubleshooting self-checkout issues caused by the very machines meant to make the checkout process more efficient. While self-checkout machines make it easier for shoppers to check out on their own, users who run into difficulty ultimately need a human cashier to resolve the issue.

Another promise of self-checkout systems was to reallocate cashier labor to other tasks throughout a store. Instead, those workers were often left to oversee the self-checkout operation or entice users to use self-checkout machines rather than the checkout lanes operated by human beings. Rather than replacing human jobs, self-checkout machines ultimately reconfigured the types of work that retail workers were responsible for carrying out.

Automated technologies like self-checkouts may be highly efficient pieces of machinery, but human beings are still required to interact with the machines on a daily basis. Organizations developing the AI solutions of tomorrow may seem like they’re building applications meant to replace human labor. However, instead, that labor is being adapted into new skills and responsibilities that complement the work carried out by a machine. 

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 internet of things is smartly predicting everything from failure to predicted customer satisfaction. This means customers are able to have their needs met before they even know they need it.

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.