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

We would like to thank Clariden Global for hosting the “Einstein AI, Deep Learning & SuperIntelligence Summit” and inviting Nikki to speak at the post-summit seminars about AI Assistants in Business. The conversations with attendees and other speakers were high quality and it was great fun to ponder the future of these cutting-edge technologies.

If you missed the talk and would like to see the slides get in touch!

October 3, 2017, Benzinga

It’s been less than a year since the startup Algomus launched its collaborative intelligence platform Algo, and the company has taken on clients ranging from Hollywood studios to appliance manufacturers, many of which are Wal-Mart suppliers.

The 2.0 version of Algo, a platform that merges artificial intelligence with human input, is being readied for a fourth-quarter launch, said Algomus CEO Amjad Hussain.

“We just move quick,” he said.

Algomus is self-funded without venture capital money, its CEO said.

Read the Full Article Here

September 14, Talk Business and Politics

Machine learning falls under the realm of artificial intelligence (AI), and though the technology has been around for a long time, it’s becoming more relevant when married with big data, according to Amjad Hussain, CEO of Detroit-based Algomus, who provides AI assistance to retail and suppliers.

During a recent workshop in Bentonville, Hussain demonstrated how AI is used by some retail suppliers such as Sony. He said AI, when used as a business assistant, can enhance productivity in an office. Hussain said machine learning combined with human creativity creates collaborative intelligence. Mathematically, he said it’s something like 1 + 1 = 11.

“John Daly, senior vice president of worldwide production services at Sony Pictures, said the Algomus business assistant — aka Algo — makes it easy to target his underperforming stores and devise a plan to raise them.”

Read the Full Article Here

September 6, Small Business Trends

“Chatbots offer a variety of potential benefits for businesses. And Algomus is a tech startup that was one of the early adopters of AI technology, creating a chatbot that can help businesses with some of the more tedious data related tasks.

Learn more about Algomus and the company’s chatbot, Algo in this week’s Small Business Spotlight.

Read the Full Article Here

A huge thanks to everyone that came out to our first workshop event in Bentonville, AR! We had so much fun doing a Walmart Store 1 walk-thru (did you know there is a Dunkin Donuts inside!!), visiting customers, and holding our first Analytics Edge Workshop at the 21c Hotel.

The Workshop was incredibly well attended and we had some great dialogue with suppliers and others in the community about the potential of AI for business process automation and how easy access to Analytics can give anyone in an organization the opportunity to be strategic in their roles.

We also want to give a big thanks to John Daly of Sony Pictures Home Entertainment for joining us as a guest speaker, it is always inspiring to hear him talk about the transformation they have been able to achieve in such a short time!

We look forward to being back in Bentonville very soon!

BERKELEY, CA – 21 Jul, 2017 – Algomus has announced that former Sony Pictures Home Entertainment VP, Jeff Fueston, has joined forces with their executive team to lead Product and Customer Success. Jeff Fueston brings upwards of 20 years experience leading Global Customer Operations, Inventory Management, and Operations and Supply Chain Management for global industry leaders including Sony Pictures Home Entertainment, MGM Studios, and Universal Studios.

Jeff Fueston joins Algomus as Vice President of Product and Customer Success to continue their trajectory as the rising AI-powered business intelligence solution in the retail and manufacturing verticals for global industry giants such as Walmart and Sony Pictures Home Entertainment. Jeff brings a fresh perspective to the Algomus executive team: “Having been a client who implemented Algomus into our strategy while serving as VP at Sony Pictures, I know the power and value they bring to businesses that integrate their technology into their workflow. With over 20 years experience in entertainment distribution at Technicolor, Universal, MGM, and most recently at Sony, I’ve seen the landscape change dramatically over the years. Having witnessed such rapid change only reinforces my experience that Algomus helps companies drive sales and cost savings, even in declining markets. Joining the ranks of such a talented group of people counts as a career high and I look forward to helping companies benefit from the power of Algomus.”

Amjad Hussain, MIT MBA graduate and Algomus CEO, says, “Jeff Fueston’s experience is just the propellant Algomus needs to continue to solve big problems with Big Data. We are particularly thrilled to add such deep vertical expertise in the Home Entertainment space. Algomus is powered by a passionate team of designers, machine learning scientists, and engineers with tremendous industry knowledge of retail category management and discrete consumer choice behavior. With a deep passion for applied machine learning, business process automation, and enterprise mobility, it’s our mission to make sure those elements are woven into the fabric of everything we build to continue solving meaningful problems for clients worldwide.”

Algomus is an Enterprise AI company offering hosted business intelligence solutions that deliver domain-specific insights from data by leveraging the power of AI and predictive analytics.