Artificial Intelligence, for SMEs?

Small and medium-sized companies are now becoming aware of the benefits they can derive from digital tools. While the cloud is already a well-integrated concept, certain technologies such as Artificial Intelligence (AI) have yet to make their mark.

An all too common idea is that AI is only for companies with a lot of data. This claim is outdated! Even if algorithms are able to process a very large amount of data. Their real power lies in the number of variables they can take into account. Therefore, all companies that have CRM software have a sufficient database to run a predictive analysis solution. As for other applications of artificial intelligence (e.g. virtual assistants), their implementation can precede (or even motivate) the implementation of an operational database. Especially since SMEs are now able to benefit from the advantages of artificial intelligence (AI) at very reasonable costs, and in some cases, without the intervention of an IT department.

Ability to analyze

With the emergence of the Internet of Things (IoT), countless sensors are collecting vast amounts of data. Ubiquitous in many devices (machines, appliances, etc.) and environments (hospitals, homes, offices, etc.), these sensors provide relevant and proprietary data on people, products and processes.

Data Science

This analytical capacity is the result of all the research carried out in terms of computing power (connectivity, sensors, data collection, etc.), technologies and algorithms (deep learning, reinforcement learning, etc.). Data science and artificial intelligence (AI) have enabled the development of solutions that contribute to product and customer profiling, production optimization, intelligent traffic management solutions, medical recommendations,…

Usable and relevant results

Although this technology is now within the reach of SMEs, its integration requires a certain amount of know-how. Obtaining the data requires time and money. A perfect understanding of the objectives and operational constraints is therefore closely linked to the success of the project. Simply applying an algorithm to a panel of data does not necessarily (and very rarely) lead to usable and relevant results. All quality data (quality over quantity) must be collected, integrated, filtered and pre-processed before it becomes usable.

A good understanding of the application domain is also essential to verify the relevance of the results. Hence the need for a true collaboration between the data processing expert and the domain specialist.

Benefits of Artificial Intelligence for SMEs

Productivity gain

Artificial intelligence now offers SMEs functionalities to simplify the work of their employees: voice activation, e-mail dictation, setting up automatic reminders linked to locations or contacts, etc. Investment in predictive maintenance of production equipment is also essential to optimize cost control.

More effective internal communication

Via conversational agents, SMEs can have interactive knowledge bases that employees can consult to find information about the company (KPIs, processes, etc.) or their activity within it (vacations, etc.). Another advantage of the formula is that employees can express themselves in “natural language” and ask questions such as: “How many days of absence am I entitled to in the event of my husband’s death?” or “How many liters is tank B?”

Optimized customer relations

When integrated on a company’s website, conversational assistants have several advantages: they will help to relieve the congestion of the after-sales service, answer accurately the questions asked by customers and prospects, collect information by asking them about their preferences and allow them to place an order online. Multi-channel solutions help agents to respond faster and more efficiently to the majority of incoming requests (email, messenger, whatsapp, …)

Predictive analysis

Thanks to machine learning, SMEs can now benefit from tools capable of distinguishing significant relationships between different variables. This ability to build and test analysis models allows for advanced customization requirements. For SMEs, this activity management allows them, for example, to quantify the customer potential for a given product or to measure the implementation of acquisition strategies.

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