Tag: AI

Disclaimer: This is an opinion piece. The views expressed in this article are mine and does not represent my employer.

Smart, sentient machines! The latest (well, not really) hype! Look back a week or two, and think about the number of days you went without hearing about how AI is going to change your career, health, medicine, food, travel or whatever. Television, newspapers, and blogs remain constantly flooded with announcements about the imminent disruption <insert field here> that is going to witness due to using AI.

Let me show you some, ahem, examples.

We have here (in the order of increasing horror):

• AI-powered Air Conditioners

• AI-powered Washing Machines

Source – Gizmodo

• AI-powered Suitcases

Source – Indiegogo

• AI-powered Phones

• AI-powered Toilet

Source – The Verge

• AI-powered Underwear!

Okay, I made that last one up. But for a second there, you guys did believe me, right? RIGHT?

That is the sad state of affairs. We are all techies here, and might think “wait, WHAT?”. But the vast majority of the not so technical audience out there sees AI as magic. They see it as something beyond their cognitive ability to process and accept any BS branded as “AI-powered” without questions. Thus, we have this article!

Source – Mashable

So what is the truth with AI? If you dig deep enough, or if you peel off enough layers(pun intended), what is happening?

Before we move on to taking the buzz off of buzzwords, let’s look at some core concepts.

Related Read: Top Artificial Intelligence Trends to Watch Out for In 2019

What is AI?

From wiki, Artificial intelligence is intelligence demonstrated by machines. It is the study of “intelligent agents”: any device that perceives its environment and takes actions that maximize its chance of successfully achieving its goals.

But Really, What Is Artificial Intelligence?

IM[not so H]O, AI is just a buzzword. Really, it is just meaningless jargon. Okay, maybe not meaningless, but it’s still jargon. Don’t believe me? Let me give you some examples:

• Computers playing checkers and beating the best human players was considered AI. Until it was not when it was accomplished around 1994 by Chinook, the checkers-playing computer program.
• Computers playing chess and beating the best human players was considered AI. Until it was not when it was accomplished around 1997 when IBM’s Deep Blue defeated the then world champion, Garry Kasparov.
• Cruise control was considered AI. Until it was not when it started being available in production cars in 1990+(partial) and 2010+(full speed range).
• Automatic parking was considered AI. Until it was not when it started being available in production cars somewhere around 2006.
• Human speech recognition was considered AI. Until it was not when it started being available as Google Assistant, Cortana, Siri, etc. Now we have a real-time speech translation!

Obligatory XKCD.

I could go on, there are quite a few examples of this phenomenon, formally known as(yes, it is so well known that it has a name) the AI effect [wiki].

So a much better definition of AI was put forth by Douglas Hofstadter.

“AI is whatever hasn’t been done yet.”   

 – Douglas Hofstadter

Just Computation

“Every time we figure out a piece of it, it stops being magical; we say, ‘Oh, that’s just a computation’.”

– Rodney Brooks

So, if it’s all just computation, why was it not, well, “computed” earlier?

Yes, computation, or rather, the capacity for computation is the key. A lot of problems were characterized as AI because, at the time, algorithms for solving that were not known yet, or because the resources to compute those were not available yet.

• Availability of Computation Power

Eg. Chess/other games, etc.

Moore’s law and the explosion in storage availability have played a major role in turning the tables. [It is important to note that the tables have not turned completely. Yet. There is so much more ground to cover.]

• Availability of Unbiased Data

Eg. Natural language processing (NLP).

Okay, now you may be thinking “Enough data was not available for speech recognition? This guy is full of BS”, but hear me out. With the explosion of social networks, so much content is created and made freely available that finding huge swaths of unbiased(this is the key here) voice/video of natural speech is available, which in turn has helped the advances in NLP.

• Availability of Infrastructure

I guess I don’t have to mention the improvement in internet speed that happened over the decade. This has accelerated content creation, real-time processing, etc.

So, What is All the Current Hype About?

The hype is not current. There has been huge interest around AI from the time it was first proposed around the 1950s. The sheer number of films about it tells us about how much.

But the current wave of hype and buzz surrounding AI comes from the recent advances made in, drumroll please, Machine Learning.

What is Machine Learning?

Machine learning is

• giving computers the ability to learn
• to find patterns in data
• from experience
• without explicit programming.

ML is essentially about classifying and predicting stuff.

The typical operation is something like:

1. Take some data
2. Learn patterns in the data
3. When presented with new data, classify it for the best guess of what it probably is, based on the “learning” that happened in [2].

Related Read: Machine Learning- Deciphering the most Disruptive Innovation

Meh! So what is the big deal?

Once trained for one purpose, the same ML system can be reused(with additional training) to learn new concepts. This can be done without rewriting the code. Now that is a big deal.

Let’s look at a simple example: Classifying emails.

Traditional programming:

if the email contains "it's never a job, its always a career"

then send to trash;

if the email contains ...

then ...

if the email contains ...

then ...

ML programs:

try to classify some emails;

change self to reduce errors;

repeat;

That was a two-minute primer on Machine Learning. So next time someone starts talking about Artificial I, I hope you feel the pang and say “Excuse me, I think you mean Machine Learning, not AI”.

Source – HubSpot

What To Watch Out For In 2019 On ERP Market Trends

It’s true that we can never bid adieu to last year’s trend-setting technologies like blockchain, AI, IoT, and multi-cloud. But, neither can we not talk about the progress where technology is likely to echo around the ERP space.

According to a study by MarketWatch, “The ERP software market is expected to rise globally to $47B by 2022”. Let us find out what are the possible market trends in ERP for 2019.

Drastic Rise Of The IoT Market

According to Statista’s latest research, “the global IoT market will rise exponentially from $2.9 trillion in 2014 to over $7 trillion in 2020”.  This leads to a situation where  ERP systems will need a new level of intelligence and automation to make platforms collect data and insights.

Earlier, only a small percentage of data were created and processed outside a traditional data center. But in the future, there will be a situation where nearly all data will be generated from outside of the data center.

IoT is expected to drive the design and deployment of many operational analytics solutions. Industries such as retail, banking, and telecommunications will also adopt operational analytics to enhance customer experience and quality.

Related Reading: Get answers to where and why should you invest in IoT.

Accelerating Transition To Cloud Computing

According to Statista Reports, “the global market revenue of public cloud services will surpass 278.3 U.S. Dollars in 2021”.

The benefits of this would be greater data security, minimal dependency on hardware, speedy results, and high customer satisfaction. As per the research report by IDC, spending on cloud computing is anticipated to rise at a rate of six times the rate of the current IT spending through 2020 which upsurges at 4.5 times the IT spending rate since 2019.

Cloud concepts, Content Delivery Network (CDN), DevOps, Big Data and Artificial Intelligence, are going to be the key players in the future of Cloud Computing.

Contribution Of AI And Emerging Disruptive Technologies

The three main trends behind the huge adoption of ERP services are the integration of artificial intelligence (AI), deployment in the cloud, and improved IoT technology.

Big data analytics and the various kinds of AI, including predictive analytics, machine learning, and deep learning, form the catalysts for industries to improve customer experience.

The third wave of technology evolution is based on systems of intelligence (Cloud, IoT, AI, VR, AR). For instance, Chatbots and messaging apps are examples for a rapid expansion in the implementation and adoption of AI.

By implementing advanced solutions such as AI-based chat-bots, IoT sensors and more, businesses will streamline and thereby accelerate their functions. This can tackle productivity issues and also it is an opportunity for businesses to realize the value and utility of new disruptive technologies.

Related Reading: Watch out for the top AI trends in 2019.

ERP and SaaS – Differences In Overheads

The traditional applications based on ERP were stored on servers. This meant overheads as a result of increased hardware costs as well as costs associated with backup, recovery, and maintenance. The difference between traditional and SaaS applications is that SaaS applications are stored on cloud-based servers.

The benefits of SaaS are that these applications do not demand high maintenance costs, or rather are they expensive. The additional overhead costs that are reduced when it comes to SaaS are that they differ in terms of per-seat licensing costs as well as the total cost of ownership etc.

So, since Saas is a cloud-based model, SaaS-based applications are neither costly, neither are they difficult to maintain.

ERP transition has taken place rapidly. The new SaaS model for ERP is very flexible and useful.

Inclusion Of Social Media Channels

ERP systems in 2019 will need to be able to include direct marketing and data links across multiple social media channels to make their presence felt in the market.

HR managers frequently use social media to search for and hire new employees and also as a background check and even as performance management indicators. These changing trends in business operations are reflected in any competitive ERP platform.

The modules that address are becoming social-media savvy in 2019. This is mainly due to the high use of customer base that accounts for 2.77 billion customers (according to eMarketer research).

The other engaging trends in ERP adoption are as follows:

• Focus on Business Intelligence

Organizations are trying to make forecasts with ERP software for business intelligence.

• Good Integration architecture

An increasing need for ERP software system has resulted in the act of ERP consultants being shifted towards a better integration architecture for ERP software.

• Two-Tier ERP

Two-tiered ERP is very useful for enterprises since they run in different processes at different places. These tend to match the needs of all locations with a better cost structure. It best suits when the enterprise is large.

• The Personalization Advantages

Today’s ERP systems are built for personalization. Some systems offer tools to help make it easy and fast in customizing the application to their needs.

• Large Organizations Acquiring Small Startups

Large organizations try acquiring smaller startups in that regards. This increases ERP implementation.

• Partnering With Firms That Break The Traditional Rules

With the onset of the cloud, the traditional role of technology partners will no longer be enough. Finding an ERP partner that utilizes the latest technology and analyzing how they deliver service with your needs is required for a successful business.

• More focus on profit from ERP

As ERP becomes more and more successful in the market, firms blindly implement them now. They are sensitive to the return of investment.

These above trends in ERP to be witnessed in 2019 are beneficial for an organization as well as provide to business growth. ERP software is used in various fields for work and that is the reason why the demand for an  ERP software system is increasing every day.

Related Reading: Check out these tips to get your business the best out of your ERP system.

Watch out for more market trends and highlights showcased for 2019 in our latest blogs!!

Also, empower your business with trending technologies. Contact our tech-experts today!

According to The Wall Street Journal, consumer spending is the primary driver of economic growth in the U.S. Manufacturers, suppliers and logistics companies are the industries that benefit from retail profits. Retailers now prefer artificial intelligence to protect profits. This improves customer service as well!

Next-Gen Solutions To Solve Retail Profit Shrinkage – Why Would You Choose AritificiaI Intelligence?

In the year 2018, the global AI market was expected to be worth 7,35 billion U.S. dollars. Also, the global AI market is expected to grow from 150 percent from 2016 numbers, reaching a forecast size of 4.8 billion U.S. dollars. These statistics show that AI is a new factor of production that can help skyrocket profitability for retailers!

Related Reading: Check out the latest trends in AI. Find 7 reasons why AI is expected to play out in 2019.

Why would you choose AI to protect retail profits?

By 2035, AI technologies will have the potential to boost productivity by 40% or even more! This means AI will increase economic growth at an average of 1.7% across 16 industries by this period.

These numbers show a straight 59% increase in retail profits alone! For this, advanced analytics are used to design and develop models. These models are then used to fetch possible outcomes from a wide spectrum of data given to a computer to analyze. From these outcomes, future decisions and actions are fed to the system which learns it. The system can now perform without human intervention! It can make decisions in real-time.

Machine learning, deep learning, and natural language processing are a few examples of AI. Marketing, pricing, logistics, risk management, store management, fraud detection are some inevitable areas where the largest retailers have used AI for decades now!!

AI – How it uses advanced analytics to solve a wide spectrum of retail problems

Manufacturers, Logistics companies, and suppliers are the major industries that support retail sales. Consumer spending depends on fluctuation in these sectors. This drives the economic growth in the U.S! Since these sectors benefit from strong retail profits, “retailers are turning to artificial intelligence to help protect profits” says a report from Forbes!

AI replaces redundant and individual-driven analysis. This is a more convenient method and ensures consistency across the retail chain. Thus AI can replace 1000 people performing the same tasks by answering spontaneously with just the same analysis!

AI can also enhance customer experience and drive sales. Online retailers use chatbots and product suggestions, while stores can enjoy real-time, targeted marketing messages. Retailers have the need to generate chunks of data on a daily basis. With predictive analytics, this data can predict trends and thus reduce the chance of failures by determining necessary changes to improve profitability. Thus the employees can have proper information faster and deliver more consistent results!

Related Reading: AI and Robotics carry the power to enhance customer experience. Here’s a CTO Guide to it.

Solving Retail Problems With AI – Steps to Overcome Challenges And Improve Efficiency To Boost Sales

All retail companies (physical and online), face four fundamental challenges. These can be solved with predictive analytics and an effective data production plan. They include:

• Siloed and Static Customer Views

Retailers can adopt a complete, real-time strategy by combining traditional data sources with the non-traditional like social media or other external data sources to create valuable insight, resulting in robust fraud detection systems, more effective marketing campaigns, more accurate and targeted churn prediction, and better customer service. This helps them encounter the problems faced by siloed data, where transaction data are separated from web pages, which is again separate from CRM data.

• Time Consuming Vendor and Supply Chain Management

Retailers can adopt real-time analytics and unstructured data sets to combine structured and unstructured data to create more accurate forecasts or automatic reordering, resulting in optimized pricing strategies and more efficient inventory management.

• Analysis Based on Historical Data

Retailers can use prediction and machine learning in real time to create predictions based on current behaviors and trends. This helps them predict the client’s next move. Thus AI helps to adapt automatically to customer behaviors.

• Single-Time Data Projects

It is high time retailers turned towards automated and scalable data workflows. This helps them improve their overall efficiency. This is made possible with predictive analytics using AI.

Related Reading: Enrich customer experience at your retail store. Read along to reveal five secret to win your retail customers.

How AI can Generate Additional Revenue

IDC analysts predict that by 2019, 40 percent of retailers will have developed a customer experience architecture supported by an AI layer! In a nutshell, the major ways in which AI can generate additional revenue and help avoid additional overheads and losses are the following:

• AI can replace redundant and individual-driven analysis for a retailer. This process is far more efficient and it ensures consistency across the retailer’s stores.
• Additionally, employee theft and paperwork errors contribute a high figure of shrink to retail profits. For instance, the National Retail Federation conducted a survey and it turned out that the reason for more than 50% of retail shrink, ie, (the difference between the real ‘on-hand’ inventory and the inventory level recorded in the computer system) is a result of employee theft and manual errors! AI models yield better and efficient results.
• Also, retailers can use AI to predict solutions benefits and functionalities prior to buying it. This way, AI can help reduce risks in retail profit shrinking.
• Choosing a consultant that can address the needs of your company can be another major benefit to reap out of AI to reduce retail profit risks. The following concerns can be addressed with the consultant:

1. How to address constraints like budget, time and personnel? Ask your consultant to provide explanations for the outcomes.
2. Consider the consultant’s skill sets from their previous projects and work experience before you decide to hand over the responsibilities and contract

Related Reading: Does AI have the potential to drive business value across industries? Read through to find how AI is revolutionizing various industries.

AI adopts next-generation solutions that use predictive analytics to capitalize on their data and knowing that 80% of this data is untapped and unstructured is the winning solution! Want to know more reasons why you can undoubtedly bet your company on AI?

Stay tuned to our latest articles and blogs to learn how AI has managed to perform a quantum shift in computing and in generating revenue to successful retail companies!!

Most of us, technology geeks or not, are eager to stay first in line to catch up with the latest game-changing technology trends. Here we are to know which technologies will thrive in 2019!

The Potential Technology Trends You Need To Explore In 2025

Have you ever looked up at the sky and clapped your eyelids on a bat? This is commonplace. But what if it was a drone. Or would it be a flying fleet? Since we don’t belong to the Jetsons family, the latter is not expected but we are close to it! 2019 is definitely a transformative year for technological innovation!

According to Gartner, the Top 10 Strategic Technology Trends for 2019 are Block chain, Artificial Intelligence, Empowered Edge, Privacy and Digital Ethics, Quantum Computing, Immersive Experiences, Augmented Analytics, Autonomous Things, and Digital Twins!

This is just the tip of the iceberg. Following are the emerging technology trends and catalyzing technical innovation that we can expect to see more of in 2019!!

Related Reading: Find how digital innovation is transforming today’s business world.

1. Blockchain Technology – The ‘New Internet’

Some call Blockchain technology the ‘New Internet’. The blockchain is the brainchild of a person or group of people known by the pseudonym, Satoshi Nakamoto. It permits digital information to be distributed but not duplicated.

It was first devised for the digital currency, Bitcoin.  It is also called the “digital gold”. To this day, the total value of the currency is nearly $112 billion US!

“Blockchain solves the manipulation problem”, says Vitalik Buterin, inventor of Ethereum.

2. Artificial Intelligence (AI)

Apart from AI-powered chatbots, 2019 will witness chip manufacturers such as Intel, NVIDIA, AMD, ARM, and Qualcomm shipping specialized chips that speed up the execution of AI-enabled applications.

2019 will also be the year for hyperscale infrastructure companies like Amazon, Microsoft, Google, and Facebook.

Related Reading: Check out the top AI trends of 2019.

3. Cloud-independent edge computing

The study from IDC illustrates that 45 percent of the entire data created by IoT devices will be stored, processed, analyzed and acted upon close to or at the edge of a network by 2020! Edge computing is a mesh network of data centers that process and store data locally before being sent to a centralized storage center or cloud.

4. Privacy and Digital Ethics

Facebook, recently witnessed the biggest security breach in which 50 million accounts were compromised. Facebook, later clarified that data of 30 million accounts were stolen.

People are becoming more nervous about how organizations and third-parties are using their personal data.

5. Quantum Computing

The world is behind building the first fully-functional quantum computer. Also called the supercomputer, this is expected to be a cloud service rather than an on-prem service. IBM is already offering cloud-based quantum computing services. For instance, the automotive, financial, insurance, pharmaceuticals, military, and research industries have the most to gain from the advancements in Quantum Computing.

6. Immersive Experiences

Conversational platforms are changing the way in which people communicate with the digital world. Virtual reality (VR), augmented reality (AR) and mixed reality (MR) are changing their approaches to know more about people’s perception.

7. Augmented Analytics

Augmented analytics relies on augmented intelligence. This uses machine learning (ML) to transform how analytics content can be developed, consumed and shared.

“Through 2020, the number of data scientists will grow five times faster than the number of experts”, says David Cearley!

8. Autonomous Things

Autonomous things, such as robots, drones, and autonomous fleet, use Artificial Intelligence techniques to automate their functions that were previously performed by humans.

9. Digital Twins

A digital twin is a digital representation of real-world items that are interlinked. Cearley states that there can be digital twins of people, processes, and things!

A DTO is an aspect of the Digital Twin evolution that is a dynamic software model that relies on operational or other data. DTOs help drive efficiencies in business processes.

Apart from these, there are other key technology trends that organizations need to explore in 2019. These include:

10. Cybersecurity and Risk Management

According to the estimates from the firm Gemalto, the data breaches were 4.5 billion in the first half of 2018! The University of Maryland study found that hackers attack computers every 39 seconds.

In 2019 we will be facing a more sophisticated array of physical security and cybersecurity challenges.

Cybersecurity is thus the digital glue that has held IoT, Smart Cities, and the world of converged machines, sensors, applications, and algorithms operational throughout!

11. Smart Spaces

A smart space is a physical or digital environment in which humans and technology-enabled systems interact in an increasingly open, connected, coordinated and intelligent ecosystems, according to Gartner! The world of technology is to enter accelerated delivery of smart spaces in 2019.

 12. Self-powered data centers

Data centers grow every minute with the implementation of virtual servers and storage, energy-efficient buildings. In 2019, the data centers are expected to run on its own self-contained power plants!

13. IoT integration

2019 will witness more IoT implementation. An International Forrester IT survey that said among a recent group study, 82% of respondents were unable to identify all of the devices connected to their networks. Of this lot, 54% were nervous about device security, and 55% were concerned about integration!

Related Reading: Find the role of Data Analytics in Internet of Things (IoT)

14. More self-service IT kiosks for business users

2019 will be a year of IT innovation designed to build better communication between IT and end users. The self-service IT kiosks to be set up would enable users to log on and choose what they want for the apps that they build.

15. The Internet of Things and Smart Cities

50 billion equipment, including smartphones, and others are expected by the IoT to be wirelessly connected via a network of sensors to the internet by 2020!

The term “Smart City” means creating a public/private infrastructure to conduct activities that protect and secure citizens. It integrates communications (5-G), transportation, energy, water resources, waste collections, smart-building technologies, and security technologies and services!

To upgrade your business with the latest technology trends on the table, contact the experts at Fingent today! Also, read through our latest blogs to learn more about accelerated technological development!!

The Experts Speak: The Adoption of AI and ML in Software Development

Artificial Intelligence (AI) and Machine Learning (ML) is transforming nearly every industry. In our previous blogs, we discussed how it is transforming finance, customer service, supply chain & logistics, and other industries. In this blog, we will talk about how AI and ML are radicalizing the software industry. We will look at the benefits of the adoption of AI and ML in software development and what industry experts have to say about it.

The Fundamental Shift in Software Development

At its very core, software development involves writing reams of rule-based code. Traditionally, developers had to specify every detail to let the system know what to do, and then customize the features of each piece of technology. With the adoption of Artificial Intelligence and Machine Learning, this process becomes much easier.

Author, scientist and Google research engineer Pete Warden puts it well:

“The pattern is that there’s an existing software project doing data processing using explicit programming logic, and the team charged with maintaining it find they can replace it with a deep-learning-based solution … What I see is that almost any data processing system with non-trivial logic can be improved significantly by applying modern machine learning. This might sound less than dramatic when put in those terms, but it’s a radical change in how we build software. Instead of writing and maintaining intricate, layered tangles of logic, the developer has to become a teacher, a curator of training data and an analyst of results.”

Practically, this means a revolutionary change in the very essence of software development.

AI and ML in action

“Modern IT environments are incredibly (and increasingly) complex and ever-changing, leading to large amounts of time and resources devoted to monitoring, troubleshooting, and course correcting,” says Phil Tee, Cofounder, and CEO of Moogsoft Inc. “It’s a reactive position for most companies, but when teams use AIOps technology they can leverage change-tolerant algorithms and access indexed information. This allows them to spend more time focused on proactive, meaningful work rather than fixing the same problems repeatedly or spending time managing rules and filters.”

Artificial Intelligence and Machine Learning can transform the entire Software Development Life Cycle (SDLC). Three ways in which it does this are:

• Synthesis of large volumes of data to predict the success or failure and business value of a project.
• Predicts accurate project delivery timelines, delivers project status updates and creates project schedules.
• Automatic diagnosis and rectification of problems in the project.

Let us consider the details of how this is achieved.

1. Turn Idea into Code Quickly and Effectively

The process from the inception of an idea to its actual execution into workable code is time-consuming and complex. Traditionally, developers must go through a long process of trial and error to get the basic code in place. Obtaining funding approvals for the project is complicated as well and requires getting the project to a prototype level even before requesting for funds. All this can be made easy with AI and ML. In the future, the system itself could learn to process ideas from natural language and suggest machine-executable code without human intervention.  AI and ML are making this possible even now by teaching systems to suggest code completion. This way systems will slowly learn to generate code through predefined modules.

Considering the viability of a project also becomes easier and faster with AI and ML. Machine learning can help developers identify and prioritize the effects of the project based on business risk. This way, time and effort on unnecessary regression testing and rectification can be eliminated. A sound decision on whether the project is feasible or not can thus be made in the earlier stages.

Related Reading: How to accelerate your business growth with Robotic Process Automation

2. Effective Project Management

Through pattern detection, AI and ML can be trained to use details of past projects to provide accurate estimates of the current project. Historical project details like bugs, test phases, actuals, and estimated values can be fed into the system and used to fine-tune the level of accuracy. Through this, the system will learn to predict accurate delivery schedules and create work schedules for individual members of the team. Risk Management, as well as Resource Management, can be better executed this way.

3. Automation of Testing and Error Detection

Pattern Detection is one of the most valued benefits of machine learning. This can be used effectively to automate the testing and debugging process in software development. One of the challenges of software testing is to come up with a list of most likely cases and scenarios that could affect the program’s performance. Through pattern detection, systems can look at past logs and generate a test case list automatically. They can also identify and classify error types and in time learn to automatically fix these errors.

Joe Colantonio, an expert on software automation and performance testing discusses what is possible with AI and ML.  “Wouldn’t it be great if you could answer the classic testing question, “If I’ve made a change in this piece of code, what’s the minimum number of tests I should be able to run in order to figure out whether or not this change is good or bad?” he says. “Many companies are using AI tools that do just that. Using ML, they can tell you with precision what the smallest number of tests is to test the piece of changed code. The tools can also analyze your current test coverage and flag areas that have little coverage, or point out areas in your application that are at risk.”

Revolutionizing IT

Apart from making a big difference in the software development process, Artificial Intelligence and Machine Learning will also change the way applications are made. With the power of AI and ML, developers will be able to design apps, which will be able to listen, think, speak, reason and make decisions. Vision Recognition technologies, Optical character recognition, and many more AI-powered capabilities will help developers create faster, smarter and better apps in the future. At Fingent, we endeavor to put this into action every day. There is no area that is immune to the changes that AI and ML can bring and we are determined to stay on top of it.

Related Reading: Top Artificial Intelligence Trends to Watch Out for In 2019

Artificial Intelligence (AI) is the rage now, but like all things tech, it is in a continuous state of evolution. Here is how Artificial Intelligence is expected to play out in 2019.

1. Complex AI-enabled chips in the Offing

The tremendous power of Artificial Intelligence, manifesting in the ability to undertake advanced mathematical calculations, number crunching, facial recognition, object detection, and other complex tasks, come with a hardware cost. Even the fastest and most advanced CPU is inadequate to improve the speed of training an AI model. Seamless execution of AI models requires additional hardware, in the form of specialized processors to complement the CPU.

Leading chip manufacturers such as AMD, Intel, NVIDIA, Qualcomm, and others, however, are working on removing the limitation, and are on the cusp of rolling out specialized chips that speed up the execution of AI-enabled applications. Hyperscale infrastructure companies such as Google, Amazon, Microsoft, and Facebook are also increasing investments in custom chip development. These new chips would be based on field programmable gate arrays (FPGA) and application specific integrated circuits (ASIC) and optimized for specific use cases and scenarios.

Needless to say, the new chips in the offing would make high-performance computing tasks such as query processing and predictive analytics very fast and seamless. Such chips would find application in a host of industries such as healthcare, automobile, and more.

Some of the early bird initiatives, such as Project Nitro from Amazon, Cloud TPUs from Google, Project Brainwave from Microsoft, Intel Myriad X VPU is a portent of the things to come in 2019.

2. Rise of ONNX to Facilitate Interoperability among Neural Networks

Developing workable AI based neural networks depends largely on selecting the right framework. While plenty of choices exist as to frameworks, developers are hamstrung by the lack of interoperability among such frameworks. This holds true for all the popular frameworks in vogue, including TensorFlow, Caffe2, Apache MXNet, PyTorch, Microsoft Cognitive Toolkit, and others.

Industry biggies such as AWS, Facebook and Microsoft are however are working on it, and have collaborated to build Open Neural Network Exchange (ONNX), which makes it possible to reuse trained neural network models across multiple frameworks.

ONNX is all set to become an essential technology for the industry in 2019, adopted by the stakeholders in a big way. Windows 10 ships already with ONNX runtime and Intel’s OpenVINO toolkit already supports ONNX, indicating the trend.

3. Automated Machine Learning to Gain Prominence

Machine Learning holds unbound promise but developing models is hard work, and the highly advanced expertise required stifles possibilities.

AutoML is however all set to change things. Applied the right way, it would empower business analysts and developers to evolve machine learning models capable of addressing complex scenarios without having to go through the usually arduous and vexatious process of training ML models, or going through elaborate workflows. Business analysts could focus on the business problem on hand, rather than worry about process and workflow.
AutoML offers the same level of flexibility that cognitive APIs perform, but also offer high portability and ability to co-opt custom data.

DataRobot, Google Cloud AutoML, Microsoft Custom Cognitive APIs, Custom Entities for Amazon Comprehend are some of the AutoML solutions already launched. The popularity of these tools indicates widespread popularity for AutoML in 2019.

4. Automation of DevOps through AIOps

AIOps represent the convergence of AI and DevOps. Such a convergence, which is all set to go mainstream in 2019, will benefit public cloud vendors and enterprises considerably.

Modern applications and infrastructure generate considerable log data, generated by hardware, server and application software, operating systems, and other sources. Such data finds a use for indexing, searching, and analytics, and is also aggregated and correlated to find insights and patterns. The application of machine learning models to such datasets makes IT operations proactive. Business managers and other stakeholders obtain insights in real time, allowing prompt and timely action. Enterprises could, for instance, leverage the improved and real-time intelligence to perform precise and accurate root cause analysis.

Some of the AIOps based tools already in vogue include Amazon EC2 Predictive Scaling, Amazon S3 Intelligent Tiering, Moogsoft AIOps, and Azure VM resiliency.

5. The rise of Virtual Agents

Businesses have started using Artificial Intelligence powered chatbots in increasing numbers. Chatbots answer questions, qualify sales leads and assist check out for online customers, among other applications. 2019 is likely to see an upgrade from chatbots to AI-powered virtual agents capable of handling even more complex customer service tasks, with even a face and personality of their own.

As a portent of things to come, Ava, Autodesk’s virtual agent, comes with a female face and a powerful persona that resonate the company’s brand image. Needless to say, such virtual agents are much more effective than human agents.

6. Increasing Role of Artificial Intelligence in Cyber Defense

Cybercrime has been a major issue for several years now. Cybercriminals target cloud infrastructure, IoT, and other cyber assets at will. 2019 will see an increasing application of Artificial Intelligence to fight cybercrime and keep cyber networks secure.

Artificial intelligence and machine learning are already applied to pick up subtle indicators of abnormal activities, detect online enemies in real time, and nip cyber threats in the bud.

7. AI to Power Smarter Retail Recommendations

The advancements in Artificial intelligence enable businesses and marketers to develop models that would recommend products based on not just the customer’s browsing history, but also the tone and sentiment. In 2019, companies will embrace AI-based solutions to offer their customers highly personalized shopping experiences. Such experiences would expand beyond e-commerce to brick and mortar stores as well, through digital interfaces.

It is interesting times ahead for AI. Smart enterprises would do well to tag tech companies who keep themselves abreast with the latest developments in this red-hot emerging technology and develop solutions to apply it to roll out workable solutions.

Related Reading : Unconventional Ways Artificial Intelligence Drives Business Value

Artificial Intelligence is revolutionizing our lives. What used to conjure up images of robots taking over the world, is now a household word. Recommendation engines are reading our minds, virtual assistants are listening to our voices, and AI insights are transforming our businesses. AI is definitely here, and this blog will show you how.

Artificial Intelligence and Its Impact on Today’s World 

Artificial Intelligence in its basic sense is defined as intelligence demonstrated by machines. In application, we can say that Artificial Intelligence is the ability of a machine to assimilate information and use it to make intelligent decisions. The attributes of problem-solving, decision making and other cognitive abilities that are associated with humans becomes artificial intelligence when applied to a machine.

The lifeblood of AI is data and its pulse run by an algorithm. Algorithms assimilate data and make sense of it through analysis. The resulting insight is what drives the decision making and problem-solving capabilities of Artificial Intelligence. Learning is by far the greatest attribute of Artificial Intelligence. The ability to learn and emulate human thinking and behavior is what makes AI nearly unstoppable. Its application in business is unmatched and is predicted to offer $15.7 trillion to the global economy by 2030!

Advanced Benefits of AI 

The benefits of AI extend to much more than recommendation engines and chatbots. The ability of AI to make sense of data collected through the Internet of Things (IoT) will be a game changer in every aspect of our lives. Gartner predicts that 20.4 billion “things” will be connected by 2020. Artificial Intelligence can analyze the data collected by IoT technology and enable it in ways that we cannot even imagine.

A classic example of this is Idemandu, one of the most talked about topic in the AI world since the 2018 Consumer Electronics Show. In the words of its founder Pooya Abka, Idemandu is the first AI agent “that can understand customers’ service needs over voice, connect them to vetted service providers instantly, and learn about their personal preferences with time.”

Demonstrating what is possible with Idemandu, a Forbes article quotes this conversation:

You: “Hey Idemandu, could you ask my massage therapist to come to my place tonight preferably after 8? I’m feeling an annoying pain in my neck.”

Idemandu: “Sure, but your therapist is not available tonight. I found another very similar therapist who is available, would you like to see him at 8 pm tonight? If not, I can book your own therapist for tomorrow at 8:30 pm.”

You: “Okay, tell him to come tonight.”

Idemandu: “Okay, he’ll be there. I already briefed him about your pain.”

Imagine the possibilities with such an AI empowered assistant in every home and business. Google Duplex is another technology that is focused on helping us make hotel reservations. The Assistant will call your chosen restaurant, converse with the concierge, make a reservation for you, confirm with you if the reservation was successful or recommend another restaurant if it wasn’t!

The ability of AI and robotics to use concepts like AI-Augmented Contextual Analytics and Sentiment Analysis to better predict and direct customer experience was brought out in one of our recent blogs. You can read it here: https://www.fingent.com/uk/blog/how-robotics-and-ai-can-improve-customer-experience-ctos-guide

How AI Is Transforming Various Business Sectors

The biggest impact of AI is in business. A survey conducted at the EmTech Digital conference revealed that respondents saw AI affecting these top three business outcomes:

1. improve and/or develop new products and services
2. achieve cost efficiencies and streamline business operations
3. accelerate decision-making

We can see this impact in nearly every sector in business. Here are three sectors where the impact of AI has been seen the most:  

Healthcare 

86% of healthcare provider organizations, life science companies, and health technology vendors are using AI technology, says a 2016 report from CB Insights. These organizations are projected to spend an average of $54 million on AI projects by 2020. Few areas where AI is being used in healthcare are:

1) Data management – Medical records and other patient data can be accurately analyzed, stored and used to provide healthcare businesses with the right information at the right time. Time-intensive report analyses can be automated, diagnosis can be fast-tracked, and treatment can be better administered.

2) Virtual Consultation and Care – Healthcare apps using AI allow doctors, patients and, caregivers to communicate and coordinate effectively.  Speech recognition, machine perception, and other AI enabled technologies, help to monitor the patient’s condition and administer effective treatment.   

3) Precision Medicine and Drug Discovery – By screening complex compounds and existing medicines for specific attributes, drug candidates for pre-clinical drug discovery and development can be rapidly identified. AI can also help detect diseases and predict hereditary health issues more accurately and help design precision medicines for specific genetic make-ups.

For more applications of AI in the healthcare industry: https://www.fingent.com/uk/blog/5-ways-big-data-is-changing-the-healthcare-industry

Finance

The assimilation and analysis of financial data is where AI shows its true potential, but there is much more that AI can do in the financial sector. AI in the Finance industry reduces costs, saves time and improves accuracy and efficiency in all areas of Finance. Here are a few applications:

1. Security from Fraud – Security is the number one concern in the financial sector. AI helps in this by simulating fraud and cybercrime scenarios and coming up with preemptive security measures to combat security breaches. AI also helps in monitoring whether all security measures and regulations are being followed in the design of financial technology.
2. Wealth Management – AI engines help analyze data associated with wealth management and provide insights on how to provide optimal benefits to clients. Creating personalized and tax-optimized investment offerings for clients becomes much simpler and accurate with the help of AI. AI also helps mitigate the unpredictability of the stock market, by incorporating features like blockchains and distributed ledgers.
3. Digital Assistants – AI now assists with banking transactions and finance in nearly every household. AI assistants like Alexa, Siri and others are used to make financial transactions. Voice assisted banking is being made possible with banks like Barclays coming up with technology to enable money transfer through voice assistance software.

Read more about how predictive algorithms and AI will rule financial services:  https://www.fingent.com/uk/blog/how-predictive-algorithms-and-ai-will-rule-financial-services 

Transportation 

AI is being used widely in the transportation sector and these are a few areas where it is making an impact:

1. Automation – While driverless cars are what comes to mind when we talk about AI and automation, the role of AI in automobile manufacturing is of equal import. Tesla’s automated manufacturing systems in its factories is an excellent example of the capabilities of AI in automobile manufacturing.
2. Cloud based conveniences – With the help of AI and cloud computing, automobiles are being packed with features like suggestions for gas stations when the fuel is low, favorite restaurants on the route and shopping reminders when approaching stores.
3. Intelligent Maintenance – Features like predictive maintenance, repair scheduling, and even sensors to detect medical emergencies for drivers can be enabled with AI.

Read more about how connected transportation will disrupt the world: https://www.fingent.com/uk/blog/how-connected-transportation-will-disrupt-the-world

Keeping up with AI 

As you can see, the implications for AI in business is tremendous. It is important that businesses capitalize on AI-based technologies to keep up with the competition. Fingent has helped businesses from every sector to implement AI and drive revenue. Drop us a message if you have any questions!

Today’s consumers are tech-savvy, demand consistency and know they can switch brands at any time. Therefore, Customer Experience (CX) is extremely important now more than ever. Customers aren’t just buying a product. They are looking to gain a good experience throughout the customer journey – before, during and after their purchase.

Imagine the pressure of not slipping up in any instance! If it wasn’t for AI and robotics, this could be a daunting affair. Thankfully though, the application of robotics and AI has streamlined the entire customer journey. As a CTO, leading the company towards this technological transformation is a great responsibility. This blog will take you through 4 ways in which robotics and AI can improve customer experience.

1. Personalization

Hyperconnected customers of this digital age highly value personalization. This personalization is expected at all touch points and marketers are employing various strategies to achieve this. In the basic sense, this includes presenting personalized recommendations using algorithms and predictive analytics. Algorithms mine transaction data, browsing patterns and purchasing behaviors to gain customer insight. This information then enables to design personalized offers and create cross-sell opportunities.

Machine Learning is going one step further with AI-Augmented Contextual Analytics. Contextual Awareness is made available through machine learning and human curation. This awareness is implemented across the entire data and analytics workflow of the company. Thus, personalization is made possible throughout the operations and can be implemented at any touch point.

Sentiment Analysis is the next big thing that companies are implementing in order to improve customer experience. Voice, text and visual engagement can be analyzed by technologies to gauge sentiment and emotion. Voice biometrics over phone calls, parsing of facial expressions during video chats, and texts through chatbots can be used to understand emotion and intent. This insight helps companies measure and deliver customer satisfaction more effectively.

Read More: Predictive Analytics: The Key to Effective Marketing and Personalization

2. Improving Internal Processes

As we have discussed, customers expect a satisfactory experience in all touch points. This includes the way the company is run, the backend and the corporate image. Efficient processes and effective decision-making filters down to a profitable company and happy customers. AI and robotics can be used to achieve this.

Mark Robinson, co-founder of the world leading SaaS solution Kimble talks about how augmented intelligence helps businesses grow. “Using augmented intelligence to make suggestions to staff, and to record their response, means that humans and the machines can work together to come up with the best solutions,” he says. “There is less need to worry that people are going to miss important actions or take wrong decisions because of the visibility of what’s going on.”

It is believed that AI has the power to increase productivity by 40% or more by 2035. By automating processes and supporting innovation, AI can improve manufacturing and business processes. One example is smart product ordering systems, which use the power of AI to streamline order fulfillment. Our recent blog brought out the opportunities in this: “From ensuring that the product is personalized and available where the customer wants it, to streamlining the order shipment and delivery process, the customer experience is enhanced by the intelligent product ordering system.”

3. Effective Pricing 

“What I ‘charge’ today has nothing to do with yesterday or tomorrow. It has to do with ‘now’!”   

– David Wayne Wilson 

This has profound significance today, where pricing drops or increases by the second. However great your marketing, your technology and other systems are, it all comes down to pricing. If a consumer gets the same benefits and quality at a lesser cost, he will opt for a cheaper option. Pricing is therefore a vital component in competitive advantage. This means that businesses must keep a close eye on competitors’ pricing behavior.

That is where Dynamic Pricing Science holds significance. With the power of Artificial Intelligence, cognitive algorithms, big data and machine learning, businesses can now effectively adjust their pricing strategies in real-time. Dynamic Pricing Science enables tailor-made pricing solutions to customers at the right time and consistent across channels. It helps understand buying patterns, identify effective correlations, compare competitor prices, match it across channels and create a customized offer – all in real time.

4. Improving Response Time 

Response time is crucial in business. This is true in leads conversion as well as customer service. The importance of response time in lead conversion was brought out by Dave Elkington, the CEO and founder of InsideSales.com. Quoting a study he was involved in he says: “The study revealed that the odds of making contact with a new lead are extremely high if you call within the first 5 minutes of submission … a rep is 100x less likely to make contact if the first call is made 30 minutes after submission. The odds of making contact drop by 3000x if the first call is made 5 hours after lead submission.” Converting a lead into a customer is the first customer touch point and it is vital to get it right.

This is important in customer service as well. The State of Multichannel Customer Service report found that:

• 68% of people stop doing business with a brand due to a poor customer service experience.
• 34% of people feel that quick resolution of their problems was the most important feature of customer service.
• 61% of people on social media expect a response from a brand in less than 24 hours.

A bad response time could break a business as the numbers show. However, AI and machine learning have helped immensely in this regard. Chatbots are proving to be a great boon, especially when it comes to swift response on first-level queries. This ensures that there is an immediate response and minimizes time spent by personnel on repetitive queries. Agents can then handle deeper conversations and conversions with the assistance of AI.

China Merchants Bank is an excellent case study on the effectiveness of real-time chatbot interaction. Interactions through these bots had reached a record of 41 million by the end of 2015, with the chatbot handling 99.5% of the questions with an accuracy of 99.8%!

Power Your Customer Service With AI

As you can see, the power of AI and robotics in customer service cannot be overemphasized. Fingent works with clients across industries all over the globe. We would be happy to help you with any questions you might have. Drop us a message and let’s get this rolling.

Artificial Intelligence (AI) is the simulation of human intelligence processes with the aid of machines. These machines primarily include computer systems and tools that carry out learning, problem-solving, reasoning and perception.

Customer service is one area where AI tools and technology can be used efficiently. As per a recent study, it is estimated that nearly 85% of the customer interactions will be handled without the presence of a human agent in next three years. There are approximately 38% of the enterprises that are using AI and the number will grow to 62% by the end of 2018. AI has the capability to accomplish the following set of tasks and activities in customer service and interactions.

Pre-emptive Action

AI embedded monitors can provide the customer service team with the ability to analyze the primary customer issues. The systems can offer real-time support to the customer for the resolution of such issues. The huge clusters of web applications can be gathered and studied to resolve the issues even before their occurrence. This empowers the business organizations to reduce the customer abandonment rates and enhance the level of customer engagement.

Messaging Applications

The use of messaging applications is not restricted to connecting with friends, family, and colleagues. The brands are using these applications for customer interaction and the usage is set to increase further. The use of social media applications and in-house messaging applications allows real-time interaction with the customers and thus resolve their queries and issues.

One-time Training

The expenditure on hiring the customer service agent and training the member is quite high. It is also necessary to organize training sessions at regular intervals. However, with the use of AI platforms, a one-time training is sufficient which in turn would bring down the costs to a huge margin.

Non-stop Services

Customer service agents cannot be made available for a non-stop period of time. The human resources work for specific hours in a day and may remain unavailable at the time of an incident. These limitations can be resolved by the use of automated support and customer service tools which interact with the customers at any hour of the day. The queries and incidents reported by the customers are automatically recorded and a suitable response is also provided that matches the reported query.

Self-service Options

A recent customer service study revealed that over 72% customers do not prefer phone calls for the resolution of their query or issue. Self-service options for customer service are on a rise and the use of chat-bots and forums have rapidly increased. AI has enabled the easy development and usage of such options. The companies that are still not utilizing such platforms will be required to incorporate the same in the future for enhanced customer relationship management and service.

Reliability & Scalability

Customer service and interaction have a great role to play in customer engagement and relationship management. According to a survey, 42% of the customers increased their purchase after a good customer service response. On the other hand, 52% customers reduced their engagement with the organization after a poor experience. AI platforms can enhance the reliability of service with their non-stop availability and unbiased customer interaction. The AI tools can also be scaled up or down as per the requirements. These applications can simultaneously handle a wide number of customers without any impact on the speed and performance.

Cost-Savings

There are advanced customer services that can be provided by artificial intelligence. The use of automated applications can reduce the costs. Resource and training costs along with the cost of the infrastructure are eliminated with the incorporation of AI tools.

It is often assumed that Artificial Intelligence will replace the jobs currently being handled by the human resources. There are over 10 million jobs that will be replaced by AI tools and applications in next ten years. However, in the case of customer service, automated assistance can only resolve 10-35% of the customer queries. Human assistance and capabilities will be required in the rest of the cases. The business organizations must research the AI applications and platforms that can be incorporated into their customer service interactions. 

The past decade has been a game-changer for the way businesses operate in the realm of retail. The advent of e-commerce and its subsequent boom has compelled brick and mortar outlets to undertake a paradigm shift from a profits-first to a consumer-centric approach. Failure in conforming to new consumer demands fueled the retail apocalypse that toppled the brick and mortar landscape. Thus, we see retail giants like Bon-Ton Stores Inc., Sears and Macy’s filing for bankruptcy and liquidate their holdings.

Implementation of targeted mobile promotions, loyalty benefits, e-payment gateways is just some of the strategies adopted by retail outlets to maintain a competitive advantage in the face of fierce technological overhauls. With disruptive innovation gaining a strong footing now more than ever, the need to constantly reinvent and augment is more pressing than before. Here are five key disruptive technology trends that you need to sync your business model with, to offer consumers retail experience par excellence:

Related Reading: 5 Ways to Enrich Customer Experience at Your Retail Store

1. The advent of Artificial Intelligence

Robots and AI bots capable of not just learning but also executing real smartness are the new focus in tech innovations. Retail giants are already experimenting with ways to implement these AI bots in their business operations. A strong case in point would be Amazon’s no-checkout cashier-less convenience stores, Amazon Go being tested across different states in North America.

Then there are self-driving grocery stores and automated trucks making home deliveries that are still undergoing trials. Of course, that is not to say that AI dominating retail operations will become the new normal tomorrow, but it is in the offing. Businesses that are in the retail sector for the long haul will stand to gain from their preparedness to embrace this change.

2. The Internet of Things

The ability of devices to interact with humans, understand commands and execute them is passé. The Internet of Things (IoT) puts the limelight on the ability of machines to interact with one another. The slow but consistent development of IoT is shaping up a new ecosystem where our gadgets will be able to operate without human intervention. Besides, the global market size for IoT in retail is expected to grow around 94.44 billion by 2025.

The emergence of IoT will inevitably alter the dynamics of the way consumers interact with retail business and the way businesses interact with distribution networks and supply chain partners. More importantly, it will usher in a connected customer model by relying on smart-store applications like smart shelves, beacons, and customer service robots. Making room for these swift connections powered by the internet will help you build a business model that is future ready.

3. Striking the Online-Offline Balance

It is the age of digital customers where the lines between online and offline existences are forever blurring. Brick and mortar businesses need an online extension to sustain themselves. Now, the spotlight is on understanding the dynamics of virtual and augmented reality and creating a marketing strategy that caters to the customers’ dual persona – considering their social media image and real identity – to encourage continued interactions and conversions.

The result – a complete overhaul of the shopping experience by bringing in a consistent omnichannel approach built around a convenient digital backend. For instance, Oasis, the UK-based fashion retailer is closing the gap between in-store and online purchasing by merging shopping experiences across its mobile app, website, and brick-and-mortar stores.

4. Personalized Shopping Experience

Take a look at how e-commerce websites function – bringing customers exactly what they need, every time, on every device, without fail. This carefully curated shopping experience eliminates the need for buyers to browse through the inventory of online stores to find what they need. Over time, this approach toward shopping has been normalized to an extent that customers expect the same out of their retail shopping experience too. Installing smart screens, tablets etc. is one way of using technology to recreate the same sense of personalization in your retail business.

5. Banking on Data

Big data is the next big thing in terms of business operations. Multinational corporations are pumping in billions of dollars to assimilate and organize this seamless information to create the right kind of marketing strategies. While big data may be out of your reach as a standalone business entity, you can create your own pool of data and use it to offer improved retail experiences for your customers.

Fun quizzes, for instances, are a great way to gather insights into your customers’ buying preferences, which can then be used to offer personalized product recommendations. You can take it a step further by tracking these recommendations to know if they are appealing to your customers and tweak them accordingly.

Related Reading: How Big Data and Analytics are Evolving Customer Experience in Retail

[Courtesy : European Bank for Reconstruction and Development]

Meanwhile, other technologies like virtual and augmented reality will continue to grow in popularity and efficiency. As a retailer, the onus of using these disruptive innovations to offer a seamless customer experience falls on you. Pairing with the right technology partner is the first step. Get in touch with our experts today to uplift your retail experience with cutting-edge software solutions.