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The business world is buzzing about AI, and for good reason. One of the most transformative applications of this technology is conversational AI — a powerful tool that can reshape how businesses interact with customers, streamline operations, and gain valuable insights.
But beyond the hype, there’s a real need to understand how conversational AI actually works, where it can be applied effectively, and what it takes to implement it successfully.
To demystify conversational AI, I sat down with Sabih Ahmed, Director of Conversational AI at Scotiabank, on the Behind the Growth podcast. Sabih is an accomplished product leader with over 15 years of experience in AI-driven enterprise transformations, making him a leading voice in his field.
In this blog, we’ll explore Sabih’s expert insights, providing a guide to conversational AI to help you uncover the practical applications of this technology, learn how to navigate the implementation process, and discover what the future holds for conversational AI in the business world.
What Is Conversational AI?
Conversational AI is a type of artificial intelligence that enables machines to have human-like conversations. It goes beyond simple, pre-programmed responses, allowing systems to understand, interpret, and respond to natural language in a way that feels intuitive and engaging for the user.
As Sabih puts it: “It’s really a subset or the subfield of artificial intelligence where we teach machines to talk to humans in a human-like way.”
This is a significant departure from traditional chatbots, which typically rely on rule-based systems. Instead of following a rigid set of pre-defined paths, conversational AI leverages machine learning and natural language processing to adapt to different conversation flows and handle a wider range of user inputs.
Real-world examples of conversational AI are becoming increasingly common.
Think of the chatbots that help you book appointments online, the voice assistants like Siri and Alexa that answer your questions, or the AI-powered systems that guide you through troubleshooting steps when you encounter a technical issue. These are all powered by conversational AI, making interactions with technology more natural and efficient.
Why Is Conversational AI Important for Your Business?
As a tech leader, you’re always looking for ways to work smarter, not harder. Conversational AI offers a practical solution to enhance customer experiences, optimize operations, and drive bottom-line results.
Improved Customer Experience
Conversational AI enables you to provide instant, around-the-clock support. Customers can get answers to questions or resolve issues anytime, without waiting for a human agent. AI-powered systems can also personalize interactions, tailoring responses to individual customer preferences.
Increased Efficiency
Conversational AI can be used to automate repetitive, high-volume tasks, freeing up human agents to focus on more complex, strategic work. Sabih explains, “We usually tend to look at things where it’s a repetitive task, it is high in volume, and it is low in complexity.”
Cost Savings
Sabih emphasizes that one of the primary benefits of conversational AI is its ability to reduce operational costs. By automating tasks that would otherwise require human agents, businesses can optimize resource allocation and free up budget for other strategic initiatives.
Data-Driven Insights
Every conversation with a customer is an opportunity to gather valuable information. Conversational AI systems capture and analyze this data, providing insights into customer behavior, preferences, and pain points.
“When it comes to conversational AI, that data is everything,” says Sabih, emphasizing the power of data-driven decision-making. These insights can be used to improve offerings, tailor marketing campaigns, and drive better business outcomes.
How to Implement Conversational AI
Successfully implementing conversational AI requires a strategic approach. It’s not just about choosing the right technology. It is also important to understand your business needs, secure buy-in from key stakeholders, and commit to ongoing optimization.
Here’s a practical roadmap, based on Sabih’s insights, to guide you through the process:
Step 1: Identify the Right Use Cases
Begin by pinpointing specific areas where conversational AI can provide the most value for your business.
Sabih emphasizes the “golden rule” for selecting use cases: focus on tasks that are “low complexity, high volume, and repetitive.” These are often the easiest to automate with conversational AI and yield the quickest wins.
Think about automating frequently asked customer service inquiries, lead generation processes, appointment scheduling, or even internal workflows that involve repetitive actions.
Step 2: Build a Compelling Business Case
Before diving into implementation, it’s crucial to secure buy-in from key decision-makers.
Sabih stresses the importance of a strong business case, stating: “Even if you have a business case, if you don’t have the right sponsors and the right executive buy-in … this will only be a pipe dream in PowerPoint decks and pieces of paper which wouldn’t see the light of day.”
To build a compelling business case, quantify the potential return on investment (ROI) of conversational AI.
Outline the expected cost savings, increased efficiency, and revenue growth that the technology can deliver. Clearly articulate how conversational AI aligns with your broader business goals and address any potential risks, outlining mitigation strategies to alleviate concerns.
Sabih suggests showcasing successful implementations at similar companies, stating: “If you’re building it for a FinTech or if you’re building it for a large FI, there are always partners, within Canada, down south, or across the kind of Atlantic where you will find partners who have done this, who have built this and who have success stories. I think that reference validation also really helps.”
Step 3: Choose the Right Partner
One of the most crucial decisions you’ll face is whether to build your conversational AI solution in-house or partner with a vendor. Weigh your team’s technical expertise, available budget, and desired timeline.
Sabih acknowledges that many companies find this decision challenging: “I think one big question that comes even before the implementation journey begins is do you build internally or do you partner? And I think that’s a big question that, more often than not, companies struggle with.”
If you choose to partner, carefully evaluate potential vendors based on their experience in your industry, technical capabilities, and their approach to collaboration. Look for partners who have a proven track record of successful implementations and can provide ongoing support and guidance.
Step 4: Design Engaging and Effective Conversations
This is where conversational design comes into play. It’s the art and science of crafting seamless and engaging interactions between users and your conversational AI system.
Sabih emphasizes the critical importance of this step, stating: “You could potentially have the best technology behind your conversational AI. But if the quality of the conversation that AI is having with you is not top notch, you’re going to fail either at adoption or at conversion or at resolutions, something or the other is going to break downstream.”
To create a positive user experience, invest time in designing conversation flows that feel natural, intuitive, and human-like. Think about the tone of voice you want your AI to convey, the types of questions it should anticipate, and how it should handle errors or unexpected inputs.
The goal is to create a conversational experience that feels as natural and helpful as interacting with a knowledgeable human agent.
Step 5: The Crucial Role of Testing
Thorough and comprehensive testing is paramount to ensure a seamless user experience, identify potential issues, and avoid costly mistakes.
Sabih underscores the importance of testing, drawing from real-world examples of chatbot failures: “Air Canada’s chatbot ran into some issues.Then I think WestJet’s chatbot also had an issue. So all that to say, you can build a good chatbot or build a good conversational AI experience, whether it’s in chat or voice. Testing is foundational.”
Your testing process should include usability testing to assess the user experience, ensuring that interactions are intuitive, clear, and easy to navigate. Additionally, conduct A/B testing to optimize conversation flows, comparing different variations to determine which perform best in achieving your desired outcomes.
Sabih emphasizes, “It is very important that the testing ecosystem is set up from day one, which can avoid a lot of unpleasantries.”
Step 6: Monitor, Analyze, and Optimize
The work doesn’t end once your conversational AI solution is launched. It’s crucial to continuously monitor its performance, analyze user interactions, and make ongoing improvements.
Sabih stresses the importance of a continuous learning cycle: “In conversational AI, the last thing you want to do is build it and forget it. There is nothing like that in conversational AI. You build it for once, but you are then incrementally adding on it throughout the time that it’s out there in the market. There is no stopping that.”
Track key metrics like user engagement, conversation completion rates, and customer satisfaction to identify areas where your AI is performing well and areas that need improvement. Use this data to refine conversation flows, expand the AI’s knowledge base, and ensure that it continues to provide a valuable and engaging experience for your users.
The Future of Conversational AI
Sabih sees a future where conversational AI moves beyond simple chatbots and voice assistants to become a truly transformative force.
One of the most exciting developments, according to Sabih, is the rise of “virtual agents.” These AI-powered systems will be capable of replicating human roles and responsibilities to a far greater extent than current technologies allow.
He envisions “a true 100% replication of human beings’ roles and responsibilities,” driven by advancements in “machine-based brain power, as well as machine-based language capability.”
To prepare for this future, Sabih believes that businesses need to embrace an AI-first culture. This means moving beyond the perception of AI as a job-stealing threat and instead viewing it as a powerful tool to augment human capabilities.
He argues that AI should be “looked at as an augmentation of human capabilities and augmentation of our business outcomes rather than potentially a replacement.” This shift in mindset will be crucial for businesses to fully leverage the potential of conversational AI and other AI-driven technologies.
Takeaway
Conversational AI is no longer a futuristic concept — it’s a powerful tool that businesses can leverage today to enhance customer experiences, streamline operations, and drive tangible results.
As Sabih wisely advises, the key is to approach this technology with a customer-centric mindset, focusing on delivering genuine value through engaging, intuitive interactions.
By embracing an AI-first culture and strategically navigating the implementation process, businesses can position themselves at the forefront of this exciting technological evolution.
Want to dive deeper into Sabih’s expert insights on conversational AI? Be sure to listen to the full episode of Behind the Growth for a conversation you don’t want to miss!
Link to podcast
Mastering Conversational AI for Business
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