How Chatbots can be a Game Changer for Educational Mobile Apps?

The educational sector has undergone massive changes post the proliferation of internet services in learning.

It will not be an exaggeration to say that they have completely changed the way students of all ages study, and the overall landscape of education has evolved for good.

There is a host of online educational mobile apps for readers of every age. Schools also recommend online educational mobile app these days to reinforce and supplement in-class sessions.

Research suggests that the size of educational mobile apps is going to rise by CAGR of more than 27% by 2022, which marks it as one of the fastest-growing segments in mobile apps.

Home-grown apps like Byju have also witnessed exemplary growth in the last five years and is turning out to be the primary source of learning outside classes for all kinds of courses.

Some Factors That Govern the Impact of a Session, Online, as Well as In-Class, Are:

1. 360-degree view of the overall subject — Teachers who leave open ends while teaching often leaves students confused.

When a person learns, they develop a mind-map of the concept. When the mind map is incomplete, learning is fraught with confusion.

2. Manner of Teaching — Some teachers have a habit of giving interesting examples to teach. Some others make learning extraordinarily interactive and fun.

3. Engagement — When students engage themselves during the session, they tend to learn better.

4. Feedback — A student remembers positive as well as negative feedback. Research suggests that feedbacks help reinforce a person’s mind-map. Examinations are the traditional feedback mechanism; in the case of app- based learning, they are online assessments.

The solutions that are currently available in the market rely on coded content, embedded videos, and paid manual support to enhance the teaching experience.

This is a gap that is still unaddressed and also a massive opportunity for improvement and innovation in the sector.

Quality of content in training may be excellent, but it can never replace that component of personal approval that a learner seeks to reinforce their mind-map.

Online mobile education is just a supplement and not a replacement to in-person education due to these very reasons in the present scenario.

Chatbots are an artificial intelligence-based solution that relies on natural language processing and native language generation to address certain aspects that existing mobile apps are missing.

Chatbots act as an online representative that may answer some of your questions.

The best success story about chatbots in present times is their usage by financial organizations to address specific client requests without having to call or visit a branch.

The chatbots are also widely used in scenarios that have intensive use cases developed traditionally. The reason is that they rely heavily on historical data and the flow of conversation.

An advanced version of a chatbot is Amelia that has received a lot of acceptance across domains.

Chatbot uses the Robotic Process Automation methodology in tandem with natural language processing to provide better customer experience while also gathering useful insights for the provider.

Now, coming back to the education sector where a real-life human teacher imparts its learnings to pupils through innovative methods and further reinforces it by asking and answering questions, a chatbot might work like magic.

To Base This Claim, Let Us Compare the Gaps in Educational Apps and Chatbot Offerings

1. 360-Degree View: A trainer uploads a video of an exhaustive lecture to explain a concept. The difference comes when a student is faced with a doubt that they cannot ask anyone online.

The chatbot window pops up and asks — what can I do for you today? The AI-based tool has already recorded the current context to answer the question.

This tool has trained on this particular topic through training datasets having a size of several terabytes and has most likely developed a good understanding.

If not able to answer, it says — “I am sorry, but you may have to reach out to an expert on this.” Voila! That is how we upsell.

2. Teaching Method — During the course, the chatbot seeks student feedback. The student shares feedback, and the chatbot utilizes its intelligent system to suggest — Would you like to refer courses from another faculty? Would you like to change the language mode?

The student can have a better learning experience than it would have had earlier. If the student is not satisfied with the resolution, chatbot connects him to a manual expert again.

3. Engagement — The student is faced with doubt in the middle of the training. He types the same in the chatbot that is present to the right side of the training window.

The chatbot utilizes its expansive knowledge in this context to answer and also suggests additional training to further brush up on the concepts.

The student can clarify small doubt without having to google into more pages — a straight cut method to retain student attention and reinforce learning with zero confusions.

4. Feedback — At the end of the course, the student is asked to give a small test to check his understanding. Unlike a traditional MCQ window, the questionnaire is administered by the chatbot.

When a student provides the wrong answer, it explains the reason why this answer is wrong and the best way to approach such questions for future references.

Once the training ends, it gives a final score and uses its intelligent model to suggest more courses to strengthen the student’s learning.

Using chatbot enables the consumer to have a better experience and also allows the provider to receive better feedback on their courses.

Chatbots can also be offered to students to connect with them on a personal level and counsel them on things that are bothering them or making individual decisions.

Benefits That a Chatbot Can Offer in Educational Mobile Apps

  1. Answering questions that a child may not be able to ask in a classroom setting due to peer pressure and fear of mocking by teachers and friends.
  2. Slow learners can attend the same training multiple times and keep brushing up on doubts and confusion to get at par with others.
  3. Fast learners can seek chatbot recommendations to understand what courses they may take next instead of waiting for it in classrooms. They can also ask questions such as the topics that can enable them to grow in a specific area of interest or training module to answer particular questions.
  4. Students at the tender age can rely on the chatbot to seek answers that may not have been addressed by their parents or teachers.
  5. Students who have a habit of asking too many questions can happily tinker with the chatbot to satisfy those inquisitive pangs now and then.
  6. Customization of chatbot will enhance the comfort level and engagement of the student at every age.
  7. A chatbot can turn to be a personal counselor to children at a crucial stage that may decide how they may develop their careers.
  8. A chatbot can be a personal assistant that helps the child plan their courses to complete all topics before the d-day.
  9. A chatbot can seek student feedback through the click of a button for improvements. It can also be used to design the student profile to guide them in the best way possible.

Things You Need to Take Care for Ensuring That Chatbots Can Add Value to the Existing Offerings

  1. Training and language model should be robust and exhaustive. A poorly trained system is even worse for a student than no chat support. Reason being that it may confuse children or portray the entire app solution as flawed and inefficient.
  2. The chatbot should not slow down the overall system. Integrating a chatbot into the existing system should be seamless, so it does not lead to other performance issues in the system.
  3. Security is a concern that has to be taken care of at all times. Chatbots should be galvanized against misuse by hackers since they are directly deriving information from the core database to learn from every experience. The chatbot should be able to identify a malicious user and notify the security team.


Educational Mobile apps have only touched the tip of the iceberg in terms of value addition and contribution.

Many remote villages across India rely on online education to learn. The introduction of chatbot needs to be such that it percolates to every level of users.

With time and increased penetration, businesses are bound to uncover further innovative ways to enhance the educational experience and make a social difference that they are capable of.

The article is written by Harikrishna Kundariya on

Why Salespeople Need to Develop “Machine Intelligence”

Artificial intelligence (AI) is on quite a run, from Google’s AlphaGo, which earlier this year defeated Go world champion Lee Sedol four games to one, to Amazon’s Echo, the voice-activated digital assistant.

The trend is heating up the sales field as well, enabling entirely new ways of selling. Purchasing, for example, is moving to automated bots, with 15%–20% of total spend already sourced through e-platforms. By 2020 customers will manage 85% of their relationship with an enterprise without interacting with a human. Leading companies are experimenting with what these technologies can do for them, typically around transactional processes at early stages of the customer journey.

For example, AI applications can take over the time-consuming tasks of initiating contact with a sales lead and then qualifying, following up, and sustaining the lead. Amelia, the “cognitive agent” developed by IPsoft, can parse natural language to understand customers’ questions, handling up to 27,000 conversations simultaneously and in multiple languages. And because “she” is connected to all the relevant systems, Amelia delivers results faster than a human operator. Of course, there will be occasions when even AI is stumped, but Amelia is smart enough to recognize when to involve a human agent.

As we learned from researching our book, Sales Growth, companies that have pioneered the use of AI in sales rave about the impact, which includes an increase in leads and appointments of more than 50%, cost reductions of 40%–60%, and call time reductions of 60%–70%. Add to that the value created by having human reps spend more of their time closing deals, and the appeal of AI grows even more.

Clearly, AI is bringing big changes. But what do they mean for sales — and the people who do it? We see two big implications.

The Sales Role Is Going to Change Completely

The “death of a salesman” is an overplayed trope, but the road ahead does mean significant changes for how sales work is done. The changes are primarily focused on automating activities rather than individual jobs, but the scale of those changes is likely to profoundly disrupt what sales people do.

We analyzed McKinsey Global Institute data on the “automatability” of 2,000 different workplace activities, comparing job requirements to the current capabilities of leading-edge technology. We found that 40% of time spent on sales work activities can be automated by adapting current technologies. If the technologies that process and understand natural language reach the median level of human performance, this number will rise to 47%.

Pity the parts salesperson, an occupation where 85% of all activities have the potential to be automated with today’s technology. Gathering customer or product information to determine customer needs, processing sales or other transactions, taking product orders from customers, and preparing sales or other contracts collectively account for approximately three-quarters of a parts salesperson’s time — and all can be automated. On the other hand, most of a sales manager’s activities, which involve strategic decision making and employee supervision and coaching, cannot be automated.

Sales People Will Need to Develop “Machine Intelligence”

Much of the focus on AI and automation has been on which jobs or tasks will be replaced. That’s understandable, of course. But it’s clear, if less explored, that sales leaders and reps will continue to be crucial to the sales process even as they adapt to working with machines.

The “human touch” will need to focus more on managing exceptions, tolerating ambiguity, using judgment, shaping the strategies and questions that machines will help enable and answer, and managing an increasingly complex web of relationships with employees, vendors, partners, and customers.

Machine learning and automation tools, for example, will be able to source, qualify, and execute far more sales opportunities than reps can keep up with. Sales leaders therefore need to develop clear escalation and exception protocols to manage the trickiest or most valuable situations, making sure a sales rep keeps a robot from losing a big sale.

While machine learning will continue to evolve, for the foreseeable future senior executives must point the technology in the right direction. They’ll have to think about a number of questions: What sorts of decisions should be automated? Which kinds of automation will help deliver on strategic growth goals? What are the legal and risk implications? How will vendor and technology relationships need to be managed and integrated to create the greatest competitive advantage?

There are implications too for the hiring and managing of sales reps. An empathetic personality will still be important, but beyond their relationship skills, reps will succeed based on their ability to understand and interpret data, work effectively with AI, and move quickly on opportunities. That’s a very different sales profile from the one many companies recruit for today.

Machines are already doing many sales jobs more effectively and efficiently than their human counterparts, and boosting customer satisfaction in the process. How sales leaders respond will determine what the future of sales looks like — and how well it works.

The article is written by Thomas Baumgartner, Homayoun Hatami and Maria Valdivieso on

Artificial Human Beings: The Amazing Examples Of Robotic Humanoids And Digital Humans

As artificial intelligence continues to mature, we are seeing a corresponding growth in sophistication for humanoid robots and the applications for digital human beings in many aspects of modern-day life. To help you see the possibilities, we have pulled together some of the best examples of humanoid robots and where you might see digital humans in your everyday life today.

Humanoid Robots

Even though the earliest form of humanoid was created by Leonardo Da Vinci in 1495 (a mechanical armored suit that could sit, stand and walk), today’s humanoid robots are powered by artificial intelligence and can listen, talk, move and respond. They use sensors and actuators (motors that control movement) and have features that are modeled after human parts. Whether they are structurally similar to a male (called an Android) or a female (Gynoid), it’s a challenge to create realistic robots that replicate human capabilities. 

The first modern-day humanoid robots were created to learn how to make better prosthetics for humans, but now they are developed to do many things to entertain us, specific jobs such as a home health worker or manufacturer, and more. Artificial intelligence makes robots human-like and helps humanoids listen, understand, and respond to their environment and interactions with humans. Here are some of the most innovative humanoid robots in development today:

Atlas: When you see Atlas in action (doing backflips and jumping from one platform to another), you can see why its creators call it “the world’s most dynamic humanoid.” It was unveiled in 2013, but its prowess for jumping platforms was released in a video in 2017. Atlas was created to carry out search and rescue missions.

Ocean One: Stanford Robotics Lab developed Ocean One, a bimanual underwater humanoid robot. Since Ocean One can reach depths that humans cannot, it can be very instrumental in researching coral reefs and other deep-sea inhabitants and features when it explores. Its anthropomorphic design and resemblance to a human diver make it very maneuverable.  

Petman: Boston Dynamics, the same company responsible for Atlas, also created Petman (Protection Ensemble Test Mannequin) to test chemical and biological suits for the U.S. military. When you see bipedal Petman in motion, it’s easy to see its human-like characteristics.

Robear: Other humanoid robots such as Robear might look more cartoon than human, but their actions definitely mimic human movement. Robear was developed to possibly help with the shortage of caregivers in Japan as the population ages. As a result, this humanoid has very gentle movements.  

Sophia: A humanoid robot developed by Hanson Robotics, is one of the most human-like robots. Sophia is able to have a human-like conversation and is able to make many human-like facial expressions. She has been made the world’s first robot citizen and is the robot Innovation Ambassador for the United Nations Development Programme. 

Digital Human Beings

Digital human beings are photorealistic digitized virtual versions of humans. Consider them avatars. While they don’t necessarily have to be created in the likeness of a specific individual (they can be entirely unique), they do look and act like humans. Unlike digital assistants such as Alexa or Siri, these AI-powered virtual beings are designed to interact, sympathize, and have conversations just like a fellow human would. Here are a few digital human beings in development or at work today:

Neons: AI-powered lifeforms created by Samsung’s STAR Labs and called Neons include unique personalities such as a banker, K-pop star, and yoga instructor. While the technology is still young, the company expects that, ultimately, Neons will be available on a subscription basis to provide services such as a customer service or concierge.

Digital Pop Stars: In Japan, new pop stars are getting attention—and these pop stars are made of pixels. One of the band members of AKB48, Amy, is entirely digital and was made from borrowing features from the human artists in the group. Another Japanese artist, Hatsune Miku, is a virtual character from Crypton Future Media. Although she started out as the illustration to promote a voice synthesizer with the same name, she now draws her own fans to sold-out auditoriums. With Auxuman, artificial intelligence is actually making the music and creating the digital performers that perform the original compositions.

AI Hosts: Virtual copies of celebrities were created by ObEN Inc to host the Spring Festival Gala, a celebration of the Chinese lunar new year. This project illustrates the potential of personal AIs—a substitute for a real person when they can’t be present in person. Similarly, China’s Xinhua news agency introduced an AI news anchor that will report the news 24/7.

Fashion Models and Social Media Influencers: Another way digital human beings are being used is in the fashion world. H&M used computer-generated models on its website, and Artificial Talent Co. created an entire business to generate completely photorealistic and customizable fashion models. And it turns out you don’t have to be a real-life human to attract a social media following. Miquela, an artificial intelligence “influencer,” has 1.3 million Instagram followers.

Digital humans have been used in television, movies, and video games already, but there are limitations to using them to replace human actors. And while it’s challenging to predict exactly how digital humans will alter our futures, there are people pondering what digital immortality would be like or how to control the negative possibilities of the technology.

The article is written by Bernard Marr on: