Top 5 Conversational AI Trends to Look out for in 2021  

Introduction

We saw a huge growth in AI trends in the year 2020 due to the global pandemic. However, we are still in the growth phase and a lot is going on in the AI industry and conversational AI trends are on top of them,  

In this world, conversational artificial intelligence has given us hope for a better and digitally advanced future. With the ongoing global pandemic COVID-19, there is a change in industries, vendors, and customers’ prospects towards this technology. This has competent in accelerating the business growth.  

Development stats say that the conversational AI market capped off 2020 at $4.8 billion. Furthermore, they have continued to grow with an estimated $13.9 billion in valuations by 2025. With conversational AI being at the forefront, there will be more advancements this year unlike ever before.   

However, it can be challenging to cut through the noise with the continuous buzz in the tech market. In the Hype Cycle for Artificial Intelligence, even Gartner has upgraded its prediction. They have declared conversational AI as a leading case for AI. 

 While implementing this technology, businesses need to keep in mind that the marketplace will get crowded in the next few years. Various vital trends in this race will define the market. They will also help the companies with the right technology.  

Today, there are mainly three conversational AI trends in 2021 that will be followed and promote advancement. So, in this blog post, we are going to cover some of the popular conversational AI trends in 2021:  

1. Maximizing Business Efficiency with Conversational AI   

In the past few years, AI has continued to make drastic changes in the industrial landscape. First conversational AI tends is that the organizations try to maximize their efficiency by buying AI solutions.  

Today, with digitalization more and more business organizations are opting to buy conversational AI platforms rather than building them.   

When implementing an AI solution, the first thing businesses consider is the cost of buying and building. After considering the monetary and manpower costs they usually conclude that developing a platform is more expensive than buying it.   

If they chose to build their customized software, most organizations are left with no choice but to hire external AI professionals to dedicate to train internal employees.   

At the end of the day, the second option organization can also prove to be incredibly costly. This is because the companies either have to spend their maximum budget or waste their valuable time in ensuring proper training.  

On the other hand, implementing a third-party Conversational AI solution is more cost-effective. This is because it requires far fewer resources and offers custom Conversational AI platforms.   

The purchased Conversational AI solutions eliminate the need for data cleansing or additional training as it comes with pre-defined workflows.   

Besides, third-party conversational AI solutions have the ability to self-learn from existing knowledge. For instance, it can quickly ingest historical, tech, and medical data for continuously learning. It can even remove the need for human intervention which saves the time of employees and companies.   

2. Conversational AI Chatbots  

Digital experiences are an important part of “the new normal”. They can help businesses boost their user engagement and fostering brand loyalty enormously. Hence, a business cannot afford to underplay effective customer service.  

Although traditionally businesses have used rule-based chatbots with digitalization they are quickly upgrading to Conversational AI chatbots. Chatbots are revolutionizing and upgrading customer service experiences.   

Even though many might perspectives all chatbots the same but the rule-based chatbots are quite different from Conversational AI chatbots. They differ from each other in terms of sophistication, functionality, and level of impact.   

Rule-based chatbots are simple in their functioning and ability. They use a series of predefined rules to interact with customers that have been previously installed by human agents. But, with the scripted guideline, their responses become limited to few user queries.   

They are also quite bland and unhelpful. Such customer interaction is fruitless and drives the levels of customer satisfaction down. Hence, making them unlikely to return for future resolutions.  

Conversational AI chatbots, on the other hand, are more advanced and sophisticated. They can understand and extract user intent with the help of unsupervised natural language processing (NLP), natural language understanding (NLU), and machine learning (ML) capabilities.  

They can also generate immediate and appropriate responses to customers’ queries in real-time. As Conversational AI chatbots are not confined by a set of rules they can engage in human-like conversations.  

Conversational AI chatbots can ensure accurate resolutions to support requests the first time around and reduce customer waiting time.   

Hence, Conversational AI chatbots enhance user experiences by providing accurate resolutions and engaging in a lively manner.  

3. Conversational AI-powered Industries   

Business organizations implement Conversational AI not only for customer service but their workforces are also its major part.   

For instance, companies can boost the productivity, efficiency, and enthusiasm of their IT and customer service employees by driving down high call volumes and escalating support requests.   

Conversational AI solutions reduce call and support request volumes by empowering customers to serve themselves. By doing this, it allows the customer service agents to focus on higher-value tasks. This shift can boost overall morale, productivity, and operational efficiency while minimizing workplace stress.   

Let’s take an example of HR departments, Conversational AI solutions can reduce routine tasks such as onboarding and employment verifications. It can even help deliver efficient resolutions to developing strategies and employee inquiries.   

Lastly, it enables HR teams to focus more on more meaningful activities by streamlining repetitive processes by workflow automation. This ensures employees are safe and well-equipped to work comfortably.   

4. Conversational AI with Shorter Development Cycles  

The next interesting conversational AI is the shift of pilot projects towards accelerated project development cycles. Gartner Conversational AI has noted that AI development is wisely accelerating AI development much sooner due to the pandemic.  

To keep up with this demand, vendors are working non-stop on its process and implementation to accommodate this shift.  

In 2021, Self-learning AI will become a significant force that substantially reduces the time needed to develop and deploy virtual agents. It will also improve their maintenance and development.  

It will help businesses scan and index their website and obtain relevant information to build a useful model. It helps build a model in a matter of hours which generally takes hundreds of working hours to do manually.  

This acceleration in the development cycle supported by self-learning AI will eliminate entry barriers to starting a conversational AI project, and it will occur drastically.  

Accelerated proofs will replace sandboxes-as-sales-tactics and facilitate the need of vendors to prove that their solution can fulfill its promises. Hence, businesses will start to see ROI day zero.  

5. Conversational AI will Drive Design of Virtual Agent    

Businesses are relying on conversational AI every day to automate large portions of their customer service interactions. It is also helping them in data analysis and applying the insights to building better customer experiences.   

Gartner predicts that by 2022 70% of white-collar workers will interact with a virtual agent daily or at least at some capacity. Businesses will have to move beyond the basic design principles that they have relied on for making chatbots if they hope to effectively engage.  

Today, businesses are seeing everything from a virtual agent’s personality and avatar to its placement on a company’s website. It is user-friendly, flexible, and appeals to a large number of audiences impacting their customer experience.   

Leading technology will always be crucial however by combining design with a no-code or low-code platform which can solely be operated by existing customer service staff will become a critical factor.  

Conclusion:  

The year 2020 has thrown many curveballs at several markets. However, in the future, it will be interesting to see how the next 12 months shake out.   

Conversational AI has proven itself to be an adaptable and capable technology. It can also prove its abilities to be counted as being of assisting businesses and consumers in unprecedented times.  

Author Bio:

Shreeya Chourasia is an experienced B2B marketing/tech content writer, who is diligently committed for growing your online presence. Her writing doesn’t merely direct the audience to take action, rather it explains how to take action for promising outcomes.