How to Deploy Conversational AI In 8 Easy Steps

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Want to learn how to deploy conversational AI?

Deploying conversational artificial intelligence (AI) can help you manage and automate any customer interaction using Natural Language Processing (NLP) and machine learning.

However, you need to deploy a robust conversational AI system correctly so that it can be employed for all use cases of your business, exceeding customer expectations.

In this ultimate guide, we’ll learn how to deploy conversational AI, from start to finish, through eight easy steps.

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How to Deploy Conversational AI? (Step-By-Step)

How to Deploy Conversational AI? (Step-By-Step)

Deploying Conversational AI isn’t as daunting as it sounds. All you need is a well-thought-out plan before you take any action for this important digital transformation.

Here’s what you can follow to build and deploy a result-oriented conversational AI solution:

Step 1: Set Goals

First, try to discuss the following questions with your team:

  • What do we want to accomplish with implementing conversational AI? What is our end goal?
  • How can conversational AI serve our business objectives?
  • What are the primary issues of our customers that conversational AI can help solve?
  • How will this AI system help our customers?
  • How can we decide KPIs needed to track progress?
  • What kind of AI assistants do our customers need: an AI-powered voice assistant (IVR), a website live chat messaging (conversational bot), or an all-in-one digital assistant (virtual assistant)?
  • Where in our workflow does the AI solution fit?

Answering these questions will help you set the course of your conversational Artificial Intelligence deployment.

Step 2: Align Company Functions

To deploy conversational AI, you’ll need a lot of company functions to align, such as customer care, compliance, tech teams, and more!

Together, they handle and move forward several stages, starting from integrating and deploying to improving the conversational AI system and expanding it to new channels, products, and markets.

That’s why your company should carefully consider these factors after evaluating your organization’s preparedness.

Step 3: Choose a Conversational AI Building Approach

To build a conversational AI bot or an AI system, you can choose any one of three approaches:

  1. Build In-house (DIY)

    You can opt to build your own conversational Artificial Intelligence in-house from scratch. That’ll require you to hire a development team which will be expensive and time-consuming, but you’ll have complete control over the process.

  2. Build In-house Using Third-Party Conversational Platforms

    You can also choose to experiment with a DIY conversational AI platform offered by IBM Watson (Watson Assistant), Google Dialogflow, Amazon Lex, or open-source frameworks like Botpress and Rasa.

    These conversational platforms take a graphical user interface method to help your conversational interfaces.

    This is perfect if you wish to reduce Artificial Intelligence creation time while keeping development in-house.

    A third-party DIY conversational AI platform often charges a reasonable price as a part of a larger cloud package. However, the expertise required to build and maintain an AI solution, in-house or on a consulting basis, is both expensive and difficult to find.

  3. Opt for a Conversational AI Vendor

    If you don’t want to opt for solutions like IBM Watson or Amazon Lex, partner with conversational AI vendors or conversational platforms specializing in your industry. This can drastically reduce risks when deploying an Artificial Intelligence solution for your business.

    But choosing the right provider is important. While deciding on the conversational AI solution provider, ensure that they have the following abilities:

    • Competence in professional services
    • User experience-oriented approach
    • Offers reasonable price plans for companies ranging from startups to large enterprises.
    • Conversational AI technology and industry expertise (customer service, banking, CRM, real estate, etc.)

    Speaking of industry expertise, if you run a contact center or company that handles customer query calls regularly, we have just the conversational AI solution for you: iovox Insights.

    What’s that?

    iovox Insights is the most powerful conversational AI solution that lets you:

    • Record and search conversations between your human agent and customer
    • Transcribe recorded calls to gain insights, spot trends, and predict outcomes
    • Add triggers or filters to train your AI
    • Use conversation insights to train contact center human agent teams
    • Track customer interaction calls that use specific keywords or phrases that you think are important
    • Enables real-time coaching
    • And more!

Step 4: Strategize Content Creation

Once you know your approach and goals for building conversational AI or bot, you need to develop a strategy for the high-quality content that’ll flow through to your AI system.

To do so, assess your company’s existing content and data sets, and decide the best sources to incorporate into the platform. For starters, you can leverage the content often used by your human agent team, such as customer support materials, website FAQs, etc. Then the content you choose needs to be refined for customer interaction and better customer engagement.

You can also develop scripts by conducting conversation roleplay sessions, mimicking direct interactions with your users. This will also help you create your script in plain English and detect unexpected conversation possibilities.

Finally, since conversational AI is an extension of your company, ensure it reflects your brand’s personality. How your AI chatbot, virtual assistant, or iovox Insights keyword rules are defined is definitely important. However, how the Artificial Intelligence bot engages can enhance customer experience and boost customer satisfaction.

Step 5: Secure Collaborations and Approvals

You need to get security, compliance, and legal to be on the same page as you to deploy your virtual assistant, voice assistant, chatbot, or any other conversational agent successfully. Involve these key stakeholders as early as possible to smoothly deploy conversational AI.

For example, let’s say you want to license a conversational AI platform with customer support industry expertise. They should be confident and experienced in demonstrating how their AI system has mechanisms to meet your unique stakeholder requirements - such as safeguarding customers’ personal information.

You also need content approval.

Specifically, spend some extra time on this with your legal and compliance teams.

They need to approve every word and will need to adjust to the ways of conversational AI. That’s because most Artificial Intelligence interactions and responses to a customer query will be computer-generated based on contextual situations and machine learning.

Help your legal and compliance teams understand the innate differences of a conversational AI experience to prevent potential deployment delays.

Step 6: Determine Conversational AI Deployment Channels

Decide the deployment channels you’ll employ to achieve the touchpoints within your customer journey. Thoroughly analyze your Artificial Intelligence use case to make the decision. Some channels include voice, advertising, social media, websites, and in-store displays.

No matter what channel or channels you pick, conversational AI can enhance your outcomes in more ways than traditional marketing technologies.

Step 7: Decide the Deployment Infrastructure

When it comes to deployment infrastructure, you have three options to choose from:

  1. On-premises Deployment

    With on-premises deployment, resources are sorted on your own servers (in-house). So you’re responsible for maintaining the AI solution and its processes. On-premises deployment also gives you total control over security, letting you decide who can or can’t access your data.

  2. Cloud Deployment

    Cloud deployment involves employing third-party servers to host your data that you can access remotely from any location whenever you like. This deployment infrastructure is a good option cost savings as its significantly cheaper than on-premises deployment.

    Moreover, the third-party server can keep offering continual AI solution upgrades.

  3. Hybrid Deployment

    With a hybrid deployment, you can enjoy the benefits of cloud deploying while you’re connected to your in-house systems. Here, the production infrastructure is on-premises, whereas conversational AI training, analytics, and similar processes are accomplished in the cloud.

    Most importantly, hybrid deployment allows uninterrupted movement of apps between on and off-premises deployment infrastructure.

Step 8: Phase the Plan

Finally, when you’re ready with everything you need to deploy conversational AI, implement three phases for a systematic deployment:

Phase 1: Prepare

Bring together your team and your conversational AI solution provider’s crew to define and discuss prepared checklists on specifications, installation requirements, and KPIs.

Phase 2: Test

Test the conversational AI system specifications to check if they work in practice. Then launch the conversational AI internally before releasing it to your customers. This way, you can complete user and security testing and work out the necessary fixes to ensure high-quality customer service.

Phase 3: Monitor

After your project is live and your customers start interacting with your AI solution, monitor their behavior. That’ll help you get as much customer experience feedback as possible. Use it to detect areas of conversational experience improvement.

Phase 4: Evaluate

Objective performance evaluation is the key metric to measure the success of your conversational AI deployment.

Monitor and examine your efforts regularly to keep the efficiency of your Artificial Intelligence in check and define your next steps for optimization and improvement.

For example, you can always rely on iovox Insights to record and monitor customer query calls. The conversational AI platform will help you understand what you need to improve your customer experience and customer satisfaction.

Final Thoughts

It makes sense for your businesses to provide customers with a conversational AI experience in a world driven by conversations and going through a digital transformation.

Deploying conversational AI will help focus on the customer’s needs and offer a humanlike conversational experience without human agent interference. And the customer interactions will continue to improve - thanks to AI’s machine learning, Natural Language Processing (NLP), dialog management, and Natural Language Understanding (NLU) ability.

As a whole, it’ll only increase customer engagement and customer satisfaction, making the deployment worth it.

Ready to deploy your conversational AI?

Talk to the experts at iovox and see if iovox Insights can help speedtrack your conversational AI deployment over voice channels. With the ability to identify keywords and trends in conversations, we’re helping companies worldwide discover valuable information on every call.

Start using iovox Insights today!

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