Conversational AI and Contribution to Enhancing Business

5 minutes read


Covid-19 has left many businesses with no choice but to embrace digitalizing more of their services in order to accommodate the growing needs of the customers and the pressure on the services in the online sphere. In the light of these new conditions, thriving in such highly competitive and ever-changing fast-paced market requires businesses to develop and adopt better strategies and long-term plans with embedded digital solutions as core pillars to the success of the execution of these strategies.

“According to a new McKinsey Global Survey of executives, their companies have accelerated the digitization of their customer and supply-chain interactions and of their internal operations by three to four years. And the share of digital or digitally enabled products in their portfolios has accelerated by a shocking seven years.” (McKinsey, Oct. 2020)

The shock of the pandemic and the rapidness in changes it has brought to the world of business, has made companies look to update their strategies so as to prepare years ahead. By then, most of the companies realized that there are no means to achieve such leap in thinking and putting that thinking into agile action but through technology; and even highly advanced tech such as artificial intelligence and machine learning.

According to a report by Altimeter in 2017, where they have interviewed 24 enterprise companies and technology experts and innovators, the question about whether to adopt conversational AI solutions appeared to be an outdated one that has been replaced by where to best adopt and integrate the services of conversational AI and how to use them for the ultimate best of the company’s goals through the crafting of effective use cases.

“The ability to deliver a more naturalistic relationship between human and machine is transformative. Shifting the way we interact with technology from commands to conversations will reshape digital experiences. It will enable organizations to reduce operational costs and identify new revenue opportunities and business models. But this won’t be quick or easy. Implementing bots requires the right technology, the right data, the right use case, the right design, and the right cultural mindset.” (Altimeter, 2017)

That was back in 2017, yes, but this case has become more enhanced and validated in the covid days where more businesses are taking their services to the internet in order to survive and reach their customers.

Still, picking the right conversational AI platform that fits within your business needs is not an easy task, because the industry is such a fast-paced one with so many players and solutions in the scene.

To make this task easier on you, we recommend breaking down the jobs you want to get done whether on the web page you wish to integrate the conversational AI solution with or within your platform’s back end if you have any, or even more concisely, use it for your internal departments and processes.

Additionally, understanding the use case will make it easier for your design process of the conversational AI experience that best fits your needs. For example, an internal conversational AI solution requires a platform that enables easy training of data that would change periodically according to the change of processes and the different announcements and updates you would want to communicate to your employees especially in the current dominant remote working mode. Platforms that support optimization and monitoring tools alongside the build and design stage will then be the best choice for what you are looking for.

Besides the efficiency conversational AI brings to the different businesses within diverse use cases, it also enables a wider spectrum of flexibility and adaptability to the user experience and customer care, businesses are trying to provide. This is enabled by the massive advances in the field of AI and Machine Learning with the introduction of new technologies such as Natural Language Understanding (NLU), Natural Language Processing (NLP) and Natural Language Generation (NLG).