In recent years, the business has already mastered technologies based on artificial intelligence (AI) and neural networks and is now actively looking for ways to use them in the corporate segment. A popular vector of development in this direction is the automation of typical workflows.
Today, the topic of using AI and neural networks in business is more relevant than ever. If you ignore the innovations in the IT sphere, then today the company will begin to lag behind, and in six months you will have to make every effort to catch up with competitors who have introduced advanced digital tools, such as Chat GPT, into their processes in time.
Let’s consider the advantages and disadvantages of optimizing business processes using neural networks. First, put yourself in the shoes of one of the most important audiences in the company. Do you think we are talking about managing partners? No, first of all, let’s talk about ordinary employees of various departments. These are:
- sales managers;
- service center specialists;
- marketers.
How can they use neural networks in their work?
One of the most important advantages of working with AI-based technologies is the ability to analyze colossal amounts of information quickly. Where a human person would need hours to search and analyze data independently, GPT would need several minutes. For the sales manager, GPT will prepare a comparative analysis of competing products, help justify to the customer the benefits of a large purchase or implementation of the service, and immediately transfer this to the presentation slide in the commercial offer. Neural networks can also provide “stress protection” for the manager’s speech to potential clients, assessing potential risks and including pre-prepared answers to all possible complex questions.
Let’s go further: the dream of all support specialists is a quick intellectual search through the knowledge base and open sources, building dialogue scripts based on the accumulated experience and communication history in the company, moving away from general answers to individual ones, as a result, reducing service time and increasing customer loyalty. AI-based technologies allow to optimize such work.
Finally, the marketing specialist closes the list of “beneficiaries” from the implementation of AI. With the help of neural networks, he can compose the structure of an important webinar or marketing event, taking into account the interests of the target audience. Making a beautiful announcement for it, perhaps, can be delegated to a neural network too.
Not so simple
The solution to all these problems can and should be given to the “machine”. However, there is a nuance: it is one thing to use any of the available neural networks for personal purposes, and quite another one to fully integrate it into the workflow, making it part of the company’s IT landscape, training it to give relevant answers and recommendations on a volume of data specific to your business and at the same time to comply with all security protocols.
Here we come to the conclusion that the use of open generative models is impossible at least due to security issues. This is distressing, but not stopping, because the vector has already been set. The market is turning towards AI solutions that are part of the product, do not contradict information security policies and are gradually developing from an amateur tool into a professional one.
Russian vendors already have quite mature products and ready-made BPM platforms for automating business processes, including those based on low-code. They include machine learning algorithms (ML – Machine Learning) designed for intelligent work with large data sets. The use of such tools increases significantly the analytical capabilities of CRM, as well as improves recommendation services.
ML configurations can be used to score data predictively implementing an intelligent hint mechanism. For example, the ML model helps in forecasting sales – traditionally one of the most difficult business tasks: it optimizes the processes of assortment management, inventory planning and pricing. It can also customize a process for certain requirements: after analyzing a large amount of data, it will recommend the values of the required fields, prompting the user with options or filling them automatically. All this increases the speed and quality of management decisions in business.
What is important to pay attention to
When choosing products for automating business processes with built-in AI-based tools, you should pay attention to several parameters. Firstly, to the presence of a generative language model of own development, isolated from external services. This will increase the degree of information security of the company. AI, trained on its own knowledge base and supporting the Russian language, will be able to respond to simple requests from platform users.
Secondly, it is worth paying attention to the presence of a model for predicting customer outflows. It will become an assistant to the head of the sales department, will be able to analyze the history of interaction with the customer and suggest the percentage of probability of his departure.
Finally, it is worth assessing how systematic the developer is working on the product to ensure a high level of information security, compliance with the requirements of supervisory authorities, as well as how quickly he responds to market requests in this area and conducts regular releases of product updates.
In conclusion, I would like to recommend now to automate a number of business tasks with AI tools. If a company does not use modern technology, it loses time, resources and opportunities, regardless of the size of the business. The use of modern technologies is about efficiency: the faster a business works, the more profit it brings. The more it is competitive and adaptive to rapid change.
By Daria Kagarlitskaya, CTO, Navicon