How to make an AI assistant to automate business processes

Technology is transforming at an exhilarating speed. Not long ago, a conversation with an artificially intelligent system or a machine was only possible in a fantasy novel. Now, humans asking Siri and Alexa to play their favorite song or book a table at a restaurant on a daily basis is a common occurrence. People are increasingly becoming comfortable talking to machines. And that’s good news for business; it allows them to automate some of their most cumbersome processes. Automation frees up humans for tasks requiring critical-thinking abilities and also ensures 24/7 availability of business for customers without incurring additional costs.

What can a chatbot do?

There are plenty of tasks that a bot can do. Trust us, the possibilities are endless. A bot can be your salesperson, relationship manager, support technician, concierge, or travel guide. It can have a conversation with customers or employees in chat rooms on your website, social media, messenger, voice assistants, IMs – including WhatsApp and Slack – or even SMSs. From a business point of view, chatbots can be both customer-facing and employee-facing; these are the two broad ones that we elaborate below.

  • Employee engagement:

    In addition to helping companies personalize employee interactions, these bots bring in process automation to a lot of business functions. For instance, a HR bot can relieve the HR manager from a lot of straightforward tasks, such as giving a report of leave balance, or the procedure to apply for travel reimbursement. A technical support bot can assist the IT administrator in tasks such as creating a desktop movement request and updating the relevant team with the details. The opportunities for embedding conversational bots in Facilities Management processes can also prove to be an immersive experience for employees. These AI bots that take over functional teams to perform mundane tasks allow them to focus on more critical assignments.

  • Customer support:

    Customers are happy as long as they get fast replies to their questions and do not care whether they’re talking to a bot or a human. A chatbot can help businesses save up on customer service costs while expediting response time and answering routine questions. They also act as part salespersons/part marketers; they cross-sell and up-sell products and help businesses with lead-generation initiatives. As a result, marketing and customer support chatbots prove to be a great asset for certain business processes and take over repetitive, static tasks off a salesperson’s plate.

  • Relationship management:

    Taking customer support a notch higher, conversational AI can also be employed for long-term relationship management, lead generation, and revenue generation. But this is not just limited to customers, in terms of application, and can also nurture relationships between partners, complex internal/external entities, employees, and prospective clients. Deployed on different mediums like e-mail, SMS, and smart voice assistants, bots can disseminate valuable information, engage in conversations, and also recommend preferences. Relationship managers that regularly interact with other parties can leverage this tool effectively.

  • Technical Support:

    Once trained on extensive data pertaining to a particular field, AI bots can seamlessly support stakeholders in that particular domain. It can not only answer static queries but also guide users through processes, redirect to important pages/policies/standards, and loop in a human operator whenever needed.

Companies that integrate conversational AI in one way or another into their business processes become conversational enterprises. They leverage the unique blend of chatting and talking human tendencies with advanced tech to reach their goals optimally. And as AI and ML improve upon their respective competencies to eventually reduce the “I don’t understand your question” scenarios, conversational enterprises will dominate the market.

Chatbot Adoption

From paying taxes to reserving tables at a restaurant, consumers are increasingly turning to virtual assistants in their everyday lives. In fact, chatbots are no more limited to just using text as a means of communication. With the emergence of smart voice innovations, a complete virtual assistant is one that has an integrated voice interface. Brands should make the most of this trend to cement their relationships with both customers and employees as well as make their processes more efficient.

However, this does not imply a thoughtless adoption of chatbots. Before adopting a chatbot, you should ask the following questions:

  1. Who is your target audience?
  2. How do you wish to serve them?
  3. What problem do you want to solve?

Answering these questions can help you design the right architecture for your chatbot. Wondering what is architecture? To put it in simple terms, a chatbot architecture is the mechanics that operate a chatbot. It involves the coding required to automate conversations between your company and the end-user. It is a complex process requiring a lot of domain expertise. However, that should not put you off from implementing a chatbot; adopting a conversational AI platform such as A.ware could help you design a chatbot without coding from scratch.

How to Build your Chatbot?

These are the following options at your disposal to integrate or adopt a chatbot.

  • Open-source services:

    It involves building an intelligent system with the aid of open-source services and APIs. You can find many open-sourced platforms like IBM Watson and Microsoft Bot Framework. The technical support, however, is limited and this option is best if you have a well-versed development team. Some of the most notable open-source chatbot building environments are provided by the below:

    • Melissa:

    It can read the news, upload photos, play music, take notes, and so much more. It is written in Python and works on Windows, OS X, and Linux with a JavaScript web interface.

    • Jasper:

    It is ideal for those who want to customize AI. Written in Python, it can listen and learn; while Melissa is run by an active module, Jasper takes a passive role.


    Besides supporting voice recognition, it also converts voice into text. Analyzing nuances and arriving at conclusions are also within its purview and it supports APIs such as iOS, Windows Phone, Cordova, Android, Python, etc. It comes with both a free and paid version, where the paid version lets you work in a private cloud.

    Only recently, big names like Google and Apple have started offering their creations like Google Now and Siri to third-party developers. While this is viewed as a reluctant move owing to their low integration capabilities, using open-source tools to build your own tool may not meet your expectations. On the other hand, creating your own virtual assistant, though a challenging task can help you meet your business needs.

  • Integrate a well-established conversational bot:

    This is the most popular way of adopting a chatbot into your legacy system and pre-existing social/web/mobile platforms. Many conversational AI vendors offer pre-trained, industry-specific conversational AI models with different capabilities, training databases, and channel-hosting options that you can customize to your brand’s look and feel. It is therefore recommended to integrate a chatbot from a well-established vendor for the obvious technical support, faster time-to-market, benefit of pre-trained models, and ease of integration into a full-throttle business. The majority of these platforms offer some unique features or capabilities to simplify the development of an AI assistant.

  • Opt for one or a collective choice of these features:

    • Speech to text:

    This involves converting speech into digital data. The system can access the voice either as a file or a stream and use CMU Sphinx to process it.

    • Text to speech:

    This is just the reverse of the above-mentioned one. It is used to translate a text or an image into human speech. One of the instances, when this functionality is required, is when someone wants to listen to the pronunciation of a word.

    • Decision making:

    Intelligent tagging is useful in decoding user’s requests. For instance, the user might ask the system for suggestions to visit on the weekend. The system will tag top places to visit in the user’s country and suggest a few places accordingly.

    • Biometrics:

    This is an important feature for both security and convenience. This lets the voice assistant identify who is speaking and respond only if needed.

    • Image recognition:

    It is a useful feature that can be later used for branching into multimodal speech recognition. Check out OpenCV in case you want to explore more.

    • Noiselessness:

    Background sounds such as traffic noises, television sounds, and other people conversing can confuse the virtual assistant. However, implementation of this feature can either eliminate or reduce background noise.

With a place in the top 10 spots of the SquAD 2.0 leaderboard, is a leader in the market that has developed its proprietary platform, A.ware, to build chatbots across multiple mediums like websites, messenger apps, email, text, and even voice-enabled smart assistants. Organizations can leverage its technical expertise and experience that has gained the interest of several businesses and has a prominent clientele. Senseforth offers full-stack AI solutions that fit the bill of multiple industries and business processes with a choice of customization.

In addition to the technical capabilities of your virtual assistant, it is important to ensure that the user is having a good time interacting with the chatbot. Thus, it is suggested that your bot has a personality. It could be either nerdy, comic, serious, or witty. Your chatbot is an extension of your brand, and thus, it should reflect your brand voice.

While building and implementing a bot is cool and fun, it is important to measure its success to really understand the value it brings to your business. If you have integrated your bot with Facebook Messenger, you can use the analytics tool to see the increase in leads and conversions. Alternatively, you can also send a questionnaire or survey to your customers and employees and ask for their feedback. With a well-established feedback loop in place, keep adding functionalities, UI factors, and revisit your underlying code as and when required, to pull your users closer to your brand than ever.

Looking to harness conversational AI to automate business processes?