From simple conversation to automation.

From a program that can answer just a few selected questions, to intelligent algorithms that independently support selected processes in an organization: chatbots in business have come a long way. And they successfully convinced companies, institutions and users. It is estimated that by the end of 2020 as many as 80% of companies will have a virtual assistant in their ranks (according to McKinsey & Company), and the savings that will generate globally will reach billions of dollars each year. The beginnings of chatbots in business services were rather modest, and after the initial results, not everyone predicted their future successes.

The bots answered only a small group of selected questions, they could not understand the context of the statements. For users, they were more often a source of frustration than tangible help. Therefore, 1st generation bots did not always achieve the goals expected by the managers in organizations. Rapid growth after humble beginnings The problems with chatbots were quickly noticed and service providers began to tune their conversational systems. The introduction of additional improvements, such as: contextual understanding, artificial intelligence supporting understanding or even the ability to communicate the bot using voice (voicebots) gave measurable results.

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Conversational systems have not only started to understand users, but also to give correct answers based on the context of the conversation. At present, as much as 95% of users’ intentions are correctly recognized. As much as 80% of queries within a given process can be handled without human intervention, which greatly extends the possibilities of using bots. A tool with such effectiveness is already an investment that definitely pays off. The growing number of implementations and the development of existing programs, as well as the optimization of subsequent processes within the organization, are the best proof of this.

Bots as a cost optimization tool A bot that can help a person and, for example, conduct a conversation with a user for half the price (e.g. when paying for an interaction) than a consultant, is a source of savings. Both direct costs and time count here. This does not mean, however, that the bot should always function “instead of a human”. In many cases, it simply relieves him or her by performing the most schematic and repetitive tasks for him. Does such a bot also help the company optimize costs? Of course! Employees performing more demanding and specialized tasks generate more value for the company. And this translates into better results for a given department.