Conversational AI:
The Next Frontier in
Enterprise Collaboration

Workplace productivity and customer engagement are intertwined. Reinventing to optimize operations can only be an effective way for enterprise leaders to flourish and adapt to the changes.

In its report Reinventing Enterprise Operations, Accenture says that those who reinvent operations are likely to drive 360-degree business value, and those who do not achieve limited incremental growth.

Based on Accenture insights, enterprise operation maturity encompasses six key capabilities, including,

  • Data, analytics & automation
  • Artificial intelligence
  • Leading practices
  • Business-tech collaboration
  • Talent strategies
  • Stakeholder experiences
Enterprise operations maturity for operational efficiency

While all of these integrate to drive best-in-class performance for enterprise operations, customer engagement, and better employee engagement, one of the many differentiators to facilitate these business objectives can easily be low-code/no-code automation.

It isn’t difficult to ascertain what it means by no-code automation 一 one of the many automation components, as such, a conversational AI chatbot for enterprises.

With so many enterprise leaders preferring digital investment in AI-powered chatbots, why is it significant to harness chatbots for those who keep deferring the idea of transforming their traditional approach to optimizing enterprise operations?

Let’s walk you through why enterprise conversational AI platforms are strategic digital investments to rise to operational challenges.

What is conversational AI for enterprise?

It is hard to deny that customers hate to wait. So do your employees when it comes to seeking a solution for a problem.

Irrespective of whether it is your customer or employees, they want a frictionless solution with humanized experience across all the touchpoints of a user journey.

Conversational AI fulfills what users want to remove from their interaction journey 一 a bland experience, frustration, and an intense need to derive the right solution in real-time in the most humanized way.

An enterprise conversation AI sounds and feels more human as it transcripts texts to human-like conversation in a machine-to-machine exchange of natural language queries.

Referred to as an enterprise conversational AI or Enterprise CAI, the AI system can be purpose-built to define use cases for enterprise operations and offer suggestions to solve issues in an automated way.

Built on top of CAI, business leaders can design, customize, and deploy their enterprise workflows for chatbots that receive natural language queries, understands the intent, extracts entities, and performs the task by evaluating query data across its training database engine.

Experience the Power of Conversational AI for Your Business.

To define it more specifically, enterprise conversational AI enables you to build virtual assistants or chatbots with the ability to communicate with humans through a self-service interface tied together by a dialog flow and neural network-based database, aiming at facilitating auto-resolutions of repetitive tasks and problems.

With the enterprise conversational AI-powered chatbot sitting at the heart of your enterprise operations, it is no hard work for your operations team to be at the disposal of user services.

How does enterprise conversational AI work?

An enterprise conversational AI system is much more advanced than a typical question-answer database model. With such a former model, after a few rounds of enterprise-level interactions, the model seems exhausted and returns back to the repeated response.

Say a customer comes to your virtual assistant and wants an answer to tax payments via an app.

How the interaction goes between a chat interface and a customer:

  • A user connects with an interface
  • A VA asks to choose from a list of options
  • When the options offer limited suggestions, a custom query can come in
  • A VA asks, ‘do you want to make tax payments’
  • A user says ‘Yes’
  • A VA or bot offers related knowledge base articles
  • KB articles do not suffice, and a user sends more detailed queries
  • Chatbot would request to refine queries or repeat the question, ‘do you want to make tax payments’

This may irritate your customer and user if they continuously receive repeated responses with no appropriate solution.

But, the application of enterprise conversational AI makes it easy to train the models to retrieve information from its database fed with relevant and historic enterprise-wide data. This also helps the model eventually learn from the patterns and apply algorithms to respond appropriately.

Let’s see how an enterprise conversational AI works:

conversational AI interface for retrieving a solution to a problem
  • Multiple chat interfaces can help communicate a problem
  • An interface receives a query
  • Natural Learning Understanding, or NLU, analyzes context information to reveal its intent and entity through speech synthesis
  • Natural Language Processing or NLP processes its database, such as knowledge articles or information base, to relate back to what it refers to, external resources, or resources from enterprise systems
  • AI model either returns a template-based or FAQ-based answer or suggests a deep-learning-based response most appropriate to the search query

By searching the right pattern in the database, conversational AI provides a correct response that helps perform an action.

So, by synthesizing text-to-speech, or speech-to-text, a chatbot with conversational AI capability can understand the user intent and simulate human language with NLU to enable elevated human experience.

What are the application areas or multiple use cases of Enterprise CAI?

multiple use cases of enterprise conversational AI

The convenience of a conversational AI interface is that it can be used across multiple devices to lift the user experience.There are immense application areas where CAI chatbots can be used for multiple use cases, which also help enterprise leaders optimize operations and drive maximum business results.

Increase in employee productivity

Undoubtedly, an enterprise involves the most complicated work processes due to the large consumer base of its multiple product offerings.

From finance to supply chain and marketing, operations and HR to IT, the least number of people could refrain from doing repetitive tasks.

By allowing automated enterprise workflows, AI conversational solutions can reduce mundane work, increase accuracy, and free up time to focus on more critical business operations.

For example, an HR recruiter can save time by automating onboarding processes or IT personnel can solve more issues related to IT incidents or asset management.

A no-code conversational AI platform such as Workativ allows enterprise leaders to build their automated app workflows for enterprise systems and help take control of complicated operations that would otherwise complicate handling IT issues and delay the restoration of operations.

In addition to solving IT issues, Workativ’s conversational AI platform can help automate the onboarding process and create lasting impressions upon a new hire to increase engagement and foster brand advocacy.

Scaling eCommerce engagement

It is ideal to be where your customers are. The ability to allow customers to shop and pay no matter where they are is most promising for enterprise growth. Conversational AI solutions are useful for creating FAQs or dialogs that help buyers shop and pay in real time. For example, leading payment services such as Mastercard or Visa offer interaction across multiple digital channels of eCommerce merchants through integration with their service order bots and improve the shopping experience.

Boosting sales and marketing

With a conversational AI chatbot integrated with your CRM platform, retrieving contact details, following up with the ideal prospects, and generating business leads is no hard work. This is the most convenient and time-saving way when you must repeatedly interact with a CRM system for every event. With a CRM chatbot for tools like Hubspot, you can automate all these tasks and easily focus on improving customer experience by offering more personalized services. With a Workativ virtual assistant, you can ramp up sales and marketing activities without wasting precious time, especially when you know your customers are fickle-minded.

Enterprise Conversational AI for automated CRM app workflows

On the other hand, it is easier to track down contact details through a query in a chat interface like that of your MS Teams or Slack and proceed with the lead gen task while your manager is out on a business trip.

Monitoring the payment activity

It is always desirable to get paid on time. For procurement of supply orders, should you continue to have a lasting business relationship with your vendors, paying on time is important.

Automation workflows built to integrate with your enterprise systems, like ERP, can easily automate invoice processing to communicate accounts payable or accounts receivable needs. On top of that, you can also automate emails as a reminder to avoid payment penalties and enable payment on time.

Elevating contact center response

It is proven that customers hate to wait more than an hour for a response on social media platforms. Also, the kind of experience they have with the labyrinthian menu navigation on IVR, they prefer connecting with a brand that offers instant response and no friction to connect with a live person.

Many enterprise solutions or services can easily benefit from conversational AI-based chat responses specific to user problems. They offer suggestions by learning from experiences across platform interactions. In a scenario where pre-defined or deep-learning-based responses do not match user expectations, an escalation to live interaction with an agent occurs for the user.

How to build your Enterprise conversational AI?

 Enterprise conversational AI development stages

A conversational AI chatbot for enterprises needs time and effort to facilitate customized responses and auto-resolutions of issues. Architecturing a chatbot is a complicated process with multiple steps going inside to prototype, build, and deploy.

Let’s get an overview of how to prepare the architecture for a conversational AI chatbot.

Prototype

Design a prototype or a preliminary version of your chatbot to determine how it looks or performs.

Prototyping always helps tweak the product and create a feasible solution for your enterprise-specific problems.

Create dialog flows: You can prepare conversational flows based on your business requirements. Unlike simple FAQ-based conversation templates that you require for handling less critical issues, enterprise-level queries need custom dialog flows. Look for relevant use cases and design your conversation architecture.

Database integration: Choose to get your model to connect with your enterprise systems or create a new knowledge base for integration, allowing you to fetch appropriate information during natural language queries.

Data collection: Train the conversational AI model with the possible chat samples or queries and prepare it to recognize the sequential data to be able to respond to unpredictable queries.

Collect relevant enterprise-specific data, which further gets processed by NLP to provide appropriate and accurate responses to the user. NLP processes data in four ways 一 tokenization, normalization, entity recognition, and sentiment analysis.

Build

Once your prototype is ready, you need to scale it on the architecture like a no-code platform or robust machine learning-based conversational AI chatbot platform. A scalable platform lets you implement the dialog flow using classifiers.

you created in the prototype stage. A dialog management engine supported by classifiers can synthesize a query's intent, contexts, and entity and fetch a response suitable to the conversational AI for enterprise architecture.

No matter what platform for chatbot development you choose, the key objective is to provide meaningful responses to users to solve a problem.

Deploy

It is time for your chatbot to be deployed in the live environment. Once you put it into chat interfaces like Messenger, web widgets, MS Teams, or Slack, keep a continuous tab on its performance. Monitor its activity, collect data, check logs, and analyze to make necessary tweaks to enhance your users' conversation experience.

What is the cost-effective way to build your enterprise Conversational AI bot?

No code platform like Workativ removes the need to nail the learning curve on the coding side, removing the development cost and time to deploy.

With a no-code chatbot building platform like Workativ, you achieve faster time to market and steadily keep allowing your business to thrive while solving enterprise-grade problems at scale.

On the HR side, your human resource team needs to align with your business objectives regarding the right talent acquisition, which pays off to ramp up future business prospects.

 onboarding automation through conversational AI chatbot

During a new hire onboarding, the enterprise processes can be as much seamless and frictionless as possible with Workativ virtual assistant enabling you to automate and streamline processes such as,

  • Documentation
  • Software installation on a laptop
  • Application provisioning
  • Ease of access to company culture resources, etc

It is easy for your HR team to auto-resolve day-to-day HR activities while spending more time solving more critical processes. As a result, it saves you time and reduces operational costs related to onboarding.

Not only can HR activities be streamlined and automated, but all IT issues are easy to streamline and scale with app workflow automation on top of the Workativ conversational AI platform.

  • 1. Just sign up for the platform
  • getting started with chatbot automation for enterprise processes
  • 2. Create your workflows for enterprise apps
  • Conversational AI workflows for enterprise use cases
  • 3. Deploy your chatbot
  • dialog management for enterprise chatbots
  • 4. Integrate with your collaboration channels like MS Teams, Slack, or Web Widget
  • Chatbot channel integrations
  • 5. Get started
  • Enterprise-level conversational or chat in action in collaboration channels like MS Teams

In conclusion

Reinventing innovation to optimize enterprise services gives you a competitive edge, and capturing real value from your digital investment hinges upon a strategic partnership with Workativ. Your digital investment in a no-code automation platform helps you drive operational efficiency and enterprise resilience, which means you will be prepared to anticipate and mitigate business challenges using data analytics and stay competitive.

To drive holistic business value enterprise-wide, harness the leading automation technology like Workativ virtual assistant for maximum user experience and customer satisfaction.

Book a demo today.

Auto-resolve 60% of Your Employee Queries With Generative AI Chatbot & Automation.

Deepa Majumder

Content Writer

Deepa Majumder is a writer who nails the art of crafting bespoke thought leadership articles to help business leaders tap into rich insights in their journey of organization-wide digital transformation. Over the years, she has dedicatedly engaged herself in the process of continuous learning and development across business continuity management and organizational resilience.

Her pieces intricately highlight the best ways to transform employee and customer experience. When not writing, she spends time on leisure activities.