10 Real World Problems that AI Solves

AI or artificial intelligence can help automate tasks, and there are real-world problems that AI solves which impact us in a greater way. While it doesn’t always have a direct impact, it helps us help everyone else.

Today, there is a prevalent fear that AI is “after our jobs” or will replace us. While that might be possible decades and decades, or even centuries into the future, today, AI provides more benefits than dangers in this day and age. Additionally, let us not forget that it is not the technology but the user who decides the fate of the world. Like all technologies (phone, internet, computers) AI can be used for both good and bad. At the moment, the human race is primarily focused on the betterment of the world. So, let’s take a peek at 10 global issues that AI helps solve.


1. Healthcare

Problem that AI Solves - healthcare

Health is Wealth for a reason. When you are healthy, you are happy and can make most things work, while achieving your dream. No wonder then that the healthcare industry is one of the most prominent ones in the world.

So, how does AI come into the picture? AI can sift through massive amounts of data in record time, which helps researchers procure necessary information faster and focus on their research, rather than on data accumulation and sifting. Research is an essential part of healthcare as it enables identification of health issues, experimentation for possible cures, prediction of treatments and so on.

Let’s look at the prediction for a second. With artificial intelligence, researchers and doctors will be able to predict the outcome and effectiveness of their drug treatment for a particular person before recommending the drug. Who would not want this personalised approach, one that benefits not just the patients but also everyone in the medical field, saving time and money for both?


2. Hiring

Problem that AI Solves - hiring

HR personnel need to sift through hundreds and thousands of CVs. Now, what if they could find a shortlist of candidates they are looking for within a few minutes? That’s what AI helps them do. It takes up the monotonous task of going through applications and throws up the most relevant profiles. This gives the HR personnel more time to interview more candidates more effectively, garnering required insights along the way.

Predictive analytics would additionally be able to spot trends amongst people hired and those that applied. This would help HR teams prepare crucial reports that highlight any recognisable patterns. This, in turn, would help organisations identify employees with high potential much earlier, adding value to the business and promoting its growth.


3. Learning & Training

Problem that AI Solves - training

Imagine conversing with a well-versed teaching assistant for a semester or even a year. You’ve never met the person but she/he has been extremely useful and helpful. That’s pretty much what happened with Georgia Tech students, who were surprised to discover that their TA was, in fact, a robot. After initial teething problems, the robot started answering the students’ questions with 97% certainty.

Humans are fundamentally the same but our brains intake information differently and at different speeds. Bringing AI onboard to help personalise teaching processes would benefit most students and teachers, the latter of whom will be more aware of how to approach a certain child’s learning curve. Additionally, there is a great prospect for AI tutors that look and sound like human and that could continue teaching the child without tiring.

 We explored the use of AI for Hiring & Training 

Check out our case studies and find out how we do it and what impact we created through it.

4. Energy Conservation

Big corporations are already paying heed to the climate change warnings and have incorporated AI to help them conserve energy. Data centres at tech firms like are very energy intensive and need a lot of power to run servers and keep them cool.

To combat this, Google uses its AI platform Deep Mind to predict the overheating of its data centres, activating cooling systems when necessary, saving around 40% in energy costs.


5. Wildlife Conservation

Tracking and wildlife conservation have gone hand-in-hand for some time now. Conservationists are able to see the travelling trajectory of the animals, their movements, ideal habitats, and so on. Let’s take habitats as an example. With AI, we can determine the best place to establish wildlife corridors for various animals and ensure their secure movement.


6. Finance

Problem that AI Solves - Finance

AI seems to be doing well in FinTech. Currently, it is used for garnering data quickly and sometimes analysing it. However, with the power of AI, there is potential for financial simulation and proper analysis as well.

AI is able to quickly sift through and review large amounts of data, as mentioned above. This enables it to garner valuable customer insight. This doesn’t imply a loss of job for financial professionals. In fact, if anything, it could make their work more fulfilling, with their attention being required on more challenging, thought-centric tasks.

 We built chatbot for banks, trading offices, and insurance firms 

Download our exclusive case studies and discover how AI supports financial services industry.

7. Transportation

Cars. Another machine run by humans. While the world does have several brilliant drivers out there, to err is only human. Self-driven or AI-controlled cars could be a significant game-changer, despite the recent the crashes that have taken place during testing. Then again, that’s why they test technology first.

These cars could reduce the number of deaths and injuries significantly. According to a report by Stanford University, they might also bring about a change in our lifestyle. Being driven around would mean that we have more free time on our hands and would be able to indulge in things we like during the commute.


8. Marketing and Sales

Problem that AI Solves - sales

Marketing and Sales departments are already using AI to their advantage, gathering essential customer insights and behavioural patterns in order to make their advertising and sales more welcome and relevant to the consumer’s life. Interestingly, conversational and interactive AI play a significant role in marketing, and their interfaces rely on voice, tone, persona et cetera. This enables the organisation to become friendlier with consumers via AI while gathering relevant data.


9. Logistics and Operations

Problem that AI Solves - operations

This industry sees AI taking over labour-intensive and menial tasks, leaving the humans to do more important and impactful jobs, thus aiding their lives and not taking away from it.

Retail stores are also able to keep a tab on foot traffic while analysing behavioural patterns in both customers and managers/salespersons, and calculating the growth of the company in relation to the work hours in the store.


10. Research and Development

Problem that AI Solves - research

Researchers are always on the lookout for patterns, opportunities to develop models, uncover efficiencies and so on. Irrespective of the field or industry, AI will aid researchers in getting accurate data across fields faster to expedite information-based decision-making and encourage improved and informed frameworks.

Undeniably, Artificial Intelligence or AI has much to offer, without harming our lifestyles, if only we let it. Want to know more about how it works?

 Check out how AI impacts our lives 

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7 jobs that will be radically disrupted by AI and automation

‘Artificial Intelligence’ and ‘Machine Learning’ are the most favoured terms in any industry today. While they make their inroads into almost all fields, let’s take a look at the 7 industries that will be most impacted by their presence.

Chatbots have become synonymous with AI but their efficiency has been a topic of hot debate for some time now. In the past, people were sceptical of how AI, specifically chatbots, would enter modern-day companies; today, the questions centre around how good the bots can be.

The success of chatbots in the current landscape is heavily dependent on two things: performing mechanical and basic analytical tasks to free up employee time and the bot’s ability to interact conversationally.

AI has already made its mark in several industries and here, we present to you, in no particular order, a list of the seven jobs that will see the biggest increase in efficiency and productivity via AI and automation.


1. Customer service

Jobs disrupted by AI - Customer Serviece

Customer Service is the first function that comes to mind when we think of automation, AI, and chatbots. Most of us are familiar with automated responses from various businesses. Unfortunately, these have been less than pleasant (especially when we’re trying to reach our bank officials!).

Chatbots add a more conversational and efficient layer to this process. They make these interactions more seamless for the customers and the customer service representatives, both of whom are thus able to avoid, to an extent, unnecessary, sometimes frustration-inducing engagements.

Several big brands, like Uber, Pizza Hut, Domino’s have incorporated chatbots in their Customer Service strategy. While the example of ordering items might seem quite basic, it paves the way for chatbots to execute more intuitive conversations, enabling them to augment human service workers in more complex scenarios, like troubleshooting technical issues or providing detailed responses to complaints. Thus, chatbot inclusion helps businesses ensure that their customer service representatives are able to increase their productivity, focusing on problems and tasks that require human attention.


2. Human resources

Jobs disrupted by AI - HR

Ah, Human Resources! The least liked department in almost any company. Can chatbots really help an industry that, according to most people (not us), is heartless at its core? Surprisingly, yes – and they can help HR personnel show their human side too.

A process-heavy undertaking, HR needs to loop in several stakeholders – from new hires to Managers, to the Finance Team, to Senior Managers et al – for most decisions, be it hiring, onboarding, or relieving from work. Chatbots aid in providing the necessary information to all stakeholders in a timely manner and via an easily accessible database.

Let’s take the instance of interviewees requesting for status updates or an existing employee asking whether they have Christmas off. Instead of sending these queries directly to the HR, who probably gets countless similar ones, the questions get routed via the chatbot and the respective parties get the relevant responses automatically. In one-off cases, where the question or task is unprecedented, the chatbot can bring the HR representative’s attention to it and the HR can then handle the matter directly.

This helps free up an HR representative’s time and they can focus on the more challenging tasks at hand – employee satisfaction, streamlining processes, understanding hiring requirements of different departments, even understanding and befriending employees.

 Download our HR chatbot case studies 

Get detailed insights on how we can implement chatbot in HR workflows and its results.

3. Security professionals

Jobs disrupted by AI - Cyber Security

Security provides an interesting use-case for artificial intelligence. AI and machine learning have been a part of cybersecurity for a while now, making tasks easier for both security professionals as well as cyber attackers/hackers.

Helping the Security industry are products like IBM’s Watson, which augments the efforts of security professionals. AI is essentially able to comprehend the behaviour of normal users, raising a red flag to security professionals when it deems any activity to be out of the ordinary. Artificial intelligence also widens the scope of experimentation and research done by security representatives, enhancing their productivity and providing greater insight. Essentially, AI implementation helps to understand the possible risks and the potential of AI-infused technology, keeping them, hopefully, a step ahead of black hat hackers and cyber-attackers.


4. Marketing

Jobs disrupted by AI - Marketing

Automation has become a godsend for industries like marketing. A data-centric and data-reliant field, marketing can gain much by incorporating chatbots and artificial intelligence technology that makes it easier to analyse and access information in an efficient, timely manner.

Additionally, based on the user’s responses, the chatbot can take further action on behalf of the user. The user, a Marketing Manager, for example, might want to know how well a campaign did in terms of product sales. She or he can easily refer to the bot and then ask the bot to execute other tasks based on this information. They can get scattered market data from the bot, which the chatbot then analyses and displays in a comprehensive, visual format, saving time for the people involved and increasing their efficiency.

Interaction with bots is set to get easier as chatbots are becoming more domain and vertical-specific, with NLP adding to their overall functionality.


5. Business intelligence (BI)

Jobs disrupted by AI - Business Intelligence

Data accumulation, data analytics, data representation, insight discovery. Business intelligence is a job heavily dependent on information, on getting data and analysing it for relevant insights. Since it is humanly impossible to go through all the data in the world, the inclusion of AI technology and automation provides a beneficial opportunity to sift through information effectively, provide more in-depth insights, and make it accessible at any point. In addition, drag-and-drop GUI, aided by NLP and Natural Language Generation, will make it easier to gather insights sans “custom-coding a solution”, making the analytics available to professionals not familiar with data or data analytics. As the cherry on top, artificial technology also lessens the work required to build custom apps and tools for Business Intelligence and makes data processing of unstructured data easier.

“AI-infused BI will somewhat, albeit not completely, automate all of the steps necessary to transform data into formats and models that BI tools can work with. This includes machine learning-based data discovery and machine learning-based data curation — cleansing, integration and so on” — Boris Evelson, Vice President and principal analyst at Forrester Research

This onslaught of automation, however, is not to be feared. Evelson is of the opinion that the aforementioned changes will greatly increase the amount of data available for analysis, thus increasing the number of jobs for data analysts.


6. Software engineers/web developers

Jobs disrupted by AI - Software Engineers

We can expect better, more intuitive digital experiences as AI helps developers and designers access relevant information with increased speed, greater efficiency, and comprehensive representation. Developers can easily understand their users’ behaviours and create contextual experiences accordingly.

In terms of software, AI is likely to aid in the creation of products, automating security, developing additional features, and maybe even encouraging self-healing in applications. The possibilities are endless!


7. CIO

Jobs disrupted by AI - CIO

CIO is set to be one of the industries most affected by the introduction of automation and AI. A large number of tasks have the potential to be automated and this calls for a massive restructuring within the field. This holds the promise of increasing productivity by ensuring an effective delegation of work amongst the human employees, while the monotonous, mechanical tasks are handled by AI and automation.

“The CIO’s workforce will be comprised of a mix of digital workers — RPA bots, AI programs, chatbots — and humans, and, keeping this mixed workforce in mind, the CIO will need to hire and train human workers for RQ — the Robotics Quotient, Forrester’s term for the skills required to work well with machines and AI” — J.P. Gownder, Vice President and principal analyst at Forrester Research

Another interesting facet of this is the AI assistant. Junior and mid-management employees seldom have personal human assistants or secretaries, but with the advent of AI, it is imminent that every worker will have an AI-powered one (personal assistant), making it easier to set reminders and schedule meetings, in accordance with the behaviour pattern of each worker.



Chatbots have not yet reached the level of intelligence many of us had envisioned, but the mass acceptance of AI across industries is a promising start. Interactions between customer and businesses are process-heavy, resulting in several frustrated parties and sub-par efficiency. Today, chatbots are primarily used for queries, but as can be seen from the list, this seems to be changing. We are on the edge of a massive digital transformation and there is constant innovation taking place in the background to make it happen. As the world continues to develop AI, machine learning, NLP, and NLG technologies, we come closer to a more efficient, decluttered world.

 Check out how AI transforms our job 

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Innovating with HR Chatbots: What Can I Use Them For?

I often used to say that my team, by the sheer nature of their work as human resource generalists in a startup, were stuck with the unenviable job scope of an “internal customer service officer”. Being lean, we didn’t have the luxury of having more hands on deck, and as such, often had no choice but to compromise on our ‘employee service’. It wasn’t until much later that I realized this wasn’t a problem unique to startups — regardless of whether you were one in a team of 20 HR professionals, or the leader of a team of 1, the workload around HR roles today will leave you feeling overwhelmed and understaffed.

Interestingly, though many technologies have come up here and there in the HR space with products that streamline processes, increase savings, increase engagement, few of them have offered actual gains in productivity of existing HR teams, which is to say, while some of them have been value-adds, some of them cost-cutting, there haven’t been many that play in the space of augmenting what HR teams already do. With the increased uptake of artificial intelligence in the enterprise space, chatbot solutions have claimed to drive productivity and efficiency of the existing team. This is in close alignment to HR’s long-standing ambition of becoming true business partners instead of administrative cost centres, yet past the standard usage of chatbots as knowledge bases and recruitment companions, we rarely come across use cases that fully exploit the capabilities of A.I. today.


Using chatbots to augment your team

| Use Case #1: Candidate Experience Surveys


Letting your chatbot handle non-textbook questions

| Use Case #2: Onboarding Concierge


Condensing complicated processes into bite-sized, executable steps

| Use Case #3: Dipstick/Heat Checks/Pulse Surveys

 Download our HR chatbot case studies now 

Get detailed insights on how we can implement chatbot in HR workflows and its results.

First of all, use chatbots to augment your team

Is there something you wish your team could do that they can’t now because they’ve run out of bandwidth? What is the one thing that would accelerate your standard HR processes, or the one best practice you read about that you want to implement, but can’t because it’s too tedious? Capitalize on those ideas. Don’t confine chatbots to simply taking over work you’re already tired of doing, but also open up the possibility of chatbots doing work or gathering data that excites you.


Use Case #1: Candidate experience surveys

As much as recruiters want to engage with candidates, it can sometimes be difficult to. With the number of candidates that cross our desks every day, we often find our hands full with simply scheduling interviews and executing on those, let alone finding out what the candidate thinks of their interview experience. Yet one of the gold standards that I’ve always strove to achieve is to make every recruitment journey one filled with learning for the candidate. What that means is that each of them is supposed to step away from the interview having learnt something, but how do we keep track of that?

Recruitment chatbots can often be customized to include a simple candidate survey feature. After each interview, the chatbot asks the candidate a series of questions, prepared by the HR team, to gather data on the experience and respond empathically. To handle such use cases, you’ll want to look for a chatbot product that has sentiment analysis capabilities and can handle simple form-filling. The chatbot leads the conversation with the candidate, for example, “Did your interviewer brainstorm together with you? What did you learn from that session?” If the candidate responds positively, the chatbot stores that either in an ATS or a simple spreadsheet. This would be functional for use, but a chatbot with sentiment analysis functionalities would be able to go above and beyond by responding with empathy, such as, “Oh no, I’m sorry to hear that you felt unprepared during the session. Would you like to tell me more about how we can improve on that?” At the end of the day, such a survey aims to give talent acquisition teams crucial, qualitative action points on how to streamline or enhance recruitment processes.

Chatbot in Recruitment

Secondly, let your chatbot handle non-textbook questions

Knowledge-based chatbots are old news, you know, the ones that allow you to ingest your HR policies so users can ask it straightforward questions like how many days of leave they have per year. What they really want to know (and what they are likely to hesitate before doing, but will still keep asking you) are answers to questions like “Do we get half-day off for Chinese New Year?” or “What time can we go home on Christmas Eve?”. Let your chatbot handle those questions with lots of tact and a little humour. Engage copywriters to make the conversational experience engaging and intriguing, even when it touches on prickly questions that you wouldn’t want to be caught answering in black and white — because everyone can read the employee handbook, but they’re going to keep coming back to you for answers to edge cases, and that helps no one.


Use Case #2: Onboarding Concierge

If your company has a global presence, you may have colleagues coming from different offices around the world, and then what happens? Some teams choose to leave them to figure transport, food and entertainment out on their own. Some teams redirect these employees in droves to HR, who isn’t always free enough to show them around, as much as we’d like to, and no, we certainly don’t know what great food there is in your vicinity.

Building a concierge feature on top of an existing onboarding chatbot will help to address some of these questions. Whether it’s integrating a local travel chatbot like Zumata or just crowdsourcing some of these recommendations from colleagues and putting them into a database, a concierge can help to keep employees engaged through a trusty chatbot, an extension of the HR team. While creating a database of such knowledge could take a while, there are two approaches that could catalyse that process: chatbots that have supervised artificial intelligence could possibly also ingest new suggestions from other employees that HR teams can easily filter for relevance and add to the database. Alternatively, the chatbot can sit and listen in to existing conversations between HR and employees to learn from responses. It’s a quick, organic approach to collecting data and supplementing your content, and with richer content, the chatbot’s utility surges as well!

Chatbot for Onboarding

Lastly, condense complicated processes into bite-sized ones that a chatbot can execute for you

There tends to be a correlation between the age of a HR team and how convoluted their processes are – with each new addition to the team adding their two cents to a process, a simple effort such as performance reviews could become so complicated that it barely justifies the time we spend on it any more. My mantra is “minimum effort for maximum impact”, and what tends to guide me in detonating unnecessary processes (a quarterly affair) is – what is this process trying to achieve, and what’s the shortest, most efficient way to get there? The solution may not be as elegant, but few outside of HR teams can appreciate the elegance of intricate processes anyway. What they can appreciate, however, are insights drawn from data-driven approaches, or transactions that now take less time to complete, or the convenience of simply being able to type a question and get a straightforward answer.


Use Case #3: Dipstick/Heat Checks/Pulse Surveys

Performance reviews don’t always have to be onerous forms and an exercise more in formality than anything else. The aim of performance reviews is to, ultimately, tell an employee how they’re faring, and most times the manager only gets notified of an issue once a quarter or by the time the annual review rolls around, they can only remember what’s happened in recent months, making the review ineffective at best.

Dipstick surveys (also called heat checks or pulse surveys) are simple, one or two question surveys sent out once every 3 days or weekly that aim to get a quick gauge of an employee’s motivation and level of engagement. After having come across the idea through Know Your Company’s methodology, it became a use case that targeted organizations that were scaling and beginning to experience “manager blindsiding”, a situation in which managers are surprised by departures, or employee unhappiness, because they “didn’t see it coming”. A simple question such as “Is there a promise you remember the company making that we haven’t delivered on?” or “Do you know what your team has been working on recently?” could kickstart a dialogue where employees can voice their questions before they become concerns, and HR teams can intervene by stepping in to help employees take ownership of the problem and solve it together with the company. After all, we’re not just bridges from management to the employees — it works the other way round, too.

 Find out how enterprises have used chatbot to augment their HR workflow 

Check out their problem set, how the chatbot helps them, and the outcome of the chatbot implementation.

Chatbots will become commonplace in the HR tech scene in the coming years, but as with all technologies, its utility is largely dependent on how imaginative we can be. The HR space is an exciting one for the technology because by nature, HR is a communication-intensive function, and the potential to disrupt those communications with conversational interfaces is immense. Quit confining chatbots to your conceptions of their limitations, and let chatbots show you what they can do. Your team will thank you for it.


Reposted from Chelsea’s Guest Post on HR Digital Today.

7 Best UX practices in Chatbot Design

No matter how amazing a chatbot’s backend and NLP is, if it suffers from poor UX, your users are unlikely to use it again. Afterall, the user really only interacts with the UX, so neglecting your UX in favor of other components is generally not recommended in the long run.

Good chatbot UX design can be hard to nail down; creating conversation flows that cater to users across different backgrounds can be a messy process, especially without clear direction. That said, here are a few things that you can do to make your chatbots more accessible to your users.

1) Know your users

One of the things that UX designers often overlook is who they’re creating their chatbots for. Is the user the average guy looking to order a dinner takeaway at your local diner? Or is he maybe a management executive asking to see the profiles of the people on his team? The former is likely to prefer a chatbot with a friendly and casual demeanor. The latter would probably appreciate receiving the information in a direct and professional manner. Knowing the demographic you’re designing for allows you to create chatbots with a laser focus towards addressing the needs of the client.

Know Your User
Number of messages per user

2) Initiate conversation

When people use your chatbot for the first time, chances are they won’t know what to type. Welcome messages are great opportunities for setting the tone of the conversation and informing the user of the chatbot’s functions and capabilities. A well-crafted greeting will introduce the chatbot in a natural and informative manner, affecting the overall UX of the chatbot for the better.

3) Redirect lost flows

Now that your chatbot has an effective introduction, we need to focus on how it recovers from invalid requests. A user’s response should never lead to a dead-end in the conversation! This tends to be a dealbreaker for many people as it completely destroys immersion in the UX of the conversation.

Craft fallback responses that apologize for the chatbot’s failure to understand, then provide options that redirect the user towards the ideal flow.

You can also provide an option to collect feedback whenever a fallback response is triggered. This can be used to further develop the bot to address invalid requests in the future.

Redirect Lost Flows
Botbot.AI initiates a conversation with your customers again and keeps in touch with them

4) Use button responses

So we all know it’s technically called a chatbot, but buttons are still an extremely useful tool in directing UX flows towards your intended outcomes. Buttons help to guide your users towards the answers they want to find. This also means they help prevent the user from veering off-topic when asking questions.

Buttons have the added bonus of taking less time and requiring less thought than typing text for the user to use. Don’t make me think, right? UX-wise, that’s unbeatable!

Here at Botbot.ai, many of our chatbots take advantage of buttons in all the time, with only certain responses requiring text input from the user. After we started using buttons, query numbers for our bots increased several-fold, with many users providing positive feedback.

Customize your buttons depending on the use case; there’s no end to the ways you can design your buttons, but the design should always help the user reach his answer one way or another.

5) Write button titles and quick replies from the POV of a person

It’s easy to use simple yes/no or ok/cancel replies in your buttons, but that’s what people have come to expect from their computers. One of the perks of using a chatbot is that it feels like talking to a person. In the same way that bot responses try to seem as human-like as possible, button responses to the bot should also be phrased as if the user were replying to a person.

Not only does this keep the user immersed in the impression of speaking to a person, it also appeals to the user’s sense of etiquette when speaking to the bot. Imagine saying cancel to a friend giving you options on where to eat dinner. You’d feel pretty bad, wouldn’t you? The key idea here is to make sure that your user interacts with your bot like an actual person, even when asking it questions.

Bot vs Human Ratio
Botbot.AI can be the only interface for the capabilities of many specialized bots

6) Break down your responses

People are prone to lose interest if they see giant walls of text. Try to space out long content into easily-digestible chunks to give your user an easier time when reading.

This is especially important when your bot is an FAQ-style information provider. People are asking the chatbot because they’d rather not read through the entire help section, so try your best not to throw an encyclopedia at your users.

7) Provide avenues of re-engagement

After your user gets his answer, it’s a good idea to leave some sort of prompt that allows him to re-engage the chatbot in a natural way. Anything from a button that redirects the user back to the start of the conversation to a simple “Feel free to drop by again to say hi” will help to make the conversation seem more natural while keeping the user within the designated flow of the conversation between uses.

Using data, Botbot.AI is able to identify the best workflow and conversation flow to get to your business goals

More than anything, it’s important to put yourself into the user’s shoes. If you find your chatbot hard to talk to, chances are your users won’t find it any easier!

 We’ve implemented all these practices for our chatbots

Check out our chatbot and see how these practices have made a user-friendly chatbot.

6 Chatbots for Banking and Financial Services Industry

Chatbot for banking and financial services industry has been one of the forerunners in the adoption of A.I. for automation of back-office processes — from eliminating paper trials to ramping up security protocols, the array of enterprise use cases for chatbots are limitless. According to McKinsey Global Institute’s 2018 automation research report, many activities in the financial services industry can be automated — 42 percent can be fully automated, and 19 percent mostly automated — and have been with significant success.

For the operational side, chatbots can offer the following benefits:

  • Enhancing end-user experience and satisfaction

  • Retrieving relevant information more rapidly

  • Increasing compliance across team processes

  • Reducing costs by adopting self-service practices


Chatbots are disrupting the financial services industry and the following six processes will benefit from A.I.-powered chatbot assistants:

1. Customer engagement

Chatbot for customer engagement

One of the most common use cases of chatbots in the financial services industry has been to increase customer engagement. After sufficient iterations and machine learning, the bots can become personalised and respond to customer’s questions – from account opening concerns to executing transactional requests. The chatbot offers an entire suite of functions all rolled into one convenient platform that users can access at any time of the day, doesn’t rest regardless of the volume of queries or requests, and makes product recommendations.

Since the entire conversation takes place via messaging, it can benefit those who’d rather get help with financial difficulties from a bot for general queries, and communicate with a customer service officer for more transaction-specific requests. Recommendations also tend to appear less forced and can even be tailored to each individual based on their query types, resulting in a higher likelihood of the product being taken up.

 See what our consumer bank clients have achieved with chatbot 

Read more on the problems they faced and how chatbot has reduced their customer service cost.

2. Stock management

stock management

When it comes to big data and pattern recognition, A.I.-powered applications provide the most advanced tools for acquiring and applying business intelligence. Game-changing tools that can produce predictive analytics are being embraced by analysts, investors and other key players in their stock management workflows. With chatbots, users can leverage on these functions via a conversational interface — making the interactions natural and seamless.

The greatest benefit here is that A.I. eliminates any room for human error, and enables managers to be better informed when investing their clients’ money. By allowing the bot to take over and automate the error-prone and repetitive tasks, human agents can expend more resources on higher-value tasks. Overall, this will undoubtedly increase opportunities for the underbanked to gain greater financial access, minimize fraud and mitigate investment risks. Its potential to not only revolutionize the industry, but also to improve the financial health of millions of people in the US and across the world, is immense.


3. Investment portfolios

investment portfolio

As the investment landscape evolves, AI-powered platforms that automate processes within asset management have become increasingly common. The introduction of A.I. advisors will augment the work of current financial advisors in the investment process, such as by cutting down reaction time for repetitive tasks like purchase and management — processes that can be easily automated. The chatbot is also capable of collecting and “learning” information about an investor’s financial objectives and their risk appetite, which can then be input into algorithms that could potentially be processed into advice and actionables. With all this data, the investor is augmented in his/her functions, being able to make better and informed investment decisions while utilising the bot to execute purchase of investments.

 Find out how a trading office uses chatbot in their operations 

Check out how chatbot can automate back-office tasks within a trading office.

4. Fraud detection & risk management

A.I.-powered tools have evolved to a stage where it can detect fraud before it happens by reviewing each transaction in every portfolio meticulously and in a way that is suitable for each specific bank’s practices. This is a task that might have taken its own employees a much longer period of time to organise and detect. Chatbots can provide assistance in ordering and retrieving data in a way that can be easily reviewed for potential fraud. An alert may be sent to ping all relevant staff if suspicious activities have been detected, enabling banks to adopt a prevention over cure approach, and giving customers the peace of mind that their accounts are in the bank’s good hands.


5. Regulatory compliance

stamp of approval

Security has become a top priority as more financial services transition onto a digital platform. For many financial institutions, however, keeping up with the constant regulatory standards can be challenging and time-consuming. With a chatbot that can “learn” and dispense information about all applicable policies as they change, whether it be the latest KYC or anti-money laundering regulations to asset management and GDPR, this ensures that financial institutions operate at the highest compliance standards, greatly boosting the efficiency of their workflows. The conversational data that the chatbot collects may also aid in identifying patterns in areas of compliance that your team may need more assistance in.


6. Onboarding new personnel


Yes, you read that right. Beyond just customers, chatbots can be a great tool for taking over the repetitive tasks that usually come with onboarding new personnel. Whether it be general questions related to certain industry terms and policies, or specific ones about company policies — a chatbot can help your team field and manage large volumes of queries. The result is a team that operates at a greater capacity and eliminates inefficiencies in the workflows. The bot can also collect and store the data into a database that users can easily retrieve information from, greatly simplifying the task of manually filing and extracting of information — a task many staff in financial institutions face.

 Read our case study on chatbot for onboarding new personnel 

Get detailed insights on how chatbot onboards new personnel and its impact on the HR team.