Understanding the use of AI in business to boost efficiency and innovation

Today, it's impossible for any organization to envisage its future without thinking about how it will benefit from artificial intelligence. Regardless of the sector in which it operates. At the same time, in the face of competitive pressure, it would be a shame not to exploit the potential of this technology, which helps us to work faster, more skilfully!

How does AI impact companies in concrete terms? How can it be integrated into everyday processes, and with which tools?

Automation, text generation, facial recognition, personalization... there are numerous use cases, addressing different professions. But we still need to use artificial intelligence properly, with full awareness of its limits, the issues surrounding it...

... and to understand what we mean by AI in business. That's why we need to start with a definition.

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Definition of artificial intelligence

What is AI, and AI in the enterprise?

Artificial intelligence defines a set of technologies capable of reproducing human behavior and cognitive capacities (planning, decision-making, creation, etc.). Whether in our private or professional lives, AI is steadily gaining ground, and is increasingly seen as the obvious way to support us in our day-to-day tasks and decisions.

On the pro side (since that's what we're interested in today), the use cases for AI in business are numerous, ranging from text generation and automation to image analysis and the Internet of Things.

💡 There are several types of artificial intelligence:

• weak AI, specialized in one task (voice assistants, for example) ;
• strong, hypothetical AI, capable of reasoning like an individual.

The different artificial intelligence technologies

Depending on your point of view, there are many different artificial intelligence technologies.

Let's focus on three of them that come up quite often in debate, because understanding them will help you visualize the resulting field of possibilities:

• Machine Learning: this is the famous automatic learning. Here, machines are able to learn on their own from data, without first being programmed to perform a specific task. The more they analyze, the more precise they become.
  
  
• Deep Learning: this is a branch of Machine Learning. What makes it special? Process complex information (images, text, sound, etc.). Inspired by the human brain, it relies on artificial neural networks composed of large volumes of data.
  
  
• Generative AI: we've heard a lot about this in recent years, as it is the technology that enables, among other things, the production of content (text, image, video, even music). To achieve this, it exploits vast quantities of data, including language models (LLMs).

How can AI be used in business? 10 examples

#1 Virtual assistants for everyone

When the subject of artificial intelligence in the enterprise is raised, the example that often springs to mind first is that of virtual assistants.

In this case, we're talking about generative AI. Microsoft Copilot, Google Gemini, ChatGPT... these tools, widely used within organizations, support employees in the performance of their daily tasks.

We can imagine, for example, an HR department using them to draft job offers, or a sales department to develop its sales pitch.

#2 Personalized recommendations

Well-known to marketing and sales departments, this facet of artificial intelligence relies on recommendation algorithms to analyze users' habits, with the aim of suggesting suitable products, content or services. The aim: to further enhance the customer experience. 🤩

This is, for example, the strategy employed by Netflix, which suggests movies based on your preferences and history.

#3 Intelligent decision-making

Whether executed by the highest levels of the company, endowed with strong decision-making power, or by the more operational profiles, the necessary analysis of corporate data would take, a la mano, an incalculable amount of time.

Thanks to machines, large quantities of historical data can be examined in record time, in order to draw the best conclusions...

... but also to project into the future, as demonstrated by predictive sales analysis, for example!

#4 Automating administrative tasks

When we think of use cases for AI in business, we often think of " automating processes and repetitive tasks ".

And this reality concerns most professions: the accounting department using AI to process invoices, the HR department sorting out CVs, etc.

#5 Robotization in industry and logistics

Artificial intelligence and robotization form a powerful alliance to save time in industrial and logistics operations. Thanks to AI, robots no longer simply execute programmed movements: they are able to adapt and make decisions based on their environment. 🤖

Examples include the machines used by Tesla to assemble car parts, or by Amazon to sort and transport packages in warehouses.

#6 Facial recognition for surveillance

Facial recognition, the process of identifying an individual from an image or video, relies on artificial intelligence and computer vision.

In fact, this technology involves studying facial features and then comparing them with a database to validate (or not) a match. It is widely exploited in the security field, for everything from simple validation of access to a machine or premises, to the identification of criminals by defense bodies.

💡Note that marketing departments also use facial recognition, with the aim of understanding individuals' emotions when faced with an advertisement.

#7 Real-time fraud detection

Financial institutions now routinely use artificial intelligence to analyze banking transactions and detect suspicious behavior in real time.

More specifically, AI compares each transaction with the customer's habits (amount, location, type of purchase, etc.). If an anomaly is detected, the system either blocks the transaction or sends an alert.

#8 Enhanced cybersecurity

Cybersecurity threats are constantly evolving, and attacks are becoming increasingly complex. Here, artificial intelligence is a real asset for businesses, enabling them to identify and respond to attacks in real time.

Using Machine Learning and deep learning algorithms, AI detects suspicious behavior... even before a risk has been fully validated! 🛡️

#9 Image analysis for medical diagnosis

The medical field, like all others, is increasingly seeing artificial intelligence at the heart of its processes.

The technology excels, in particular, in the analysis of X-rays, MRIs, scans and other medical images. Using computer vision algorithms, it can detect anomalies and diseases much more quickly than the human eye!

#10 Predictive machine maintenance

Finally, let's talk about predictive maintenance, which is used to anticipate equipment breakdowns before they happen.

Here, artificial intelligence is used to process real-time data from sensors installed on machines. In this way, it detects signs of wear and tear or malfunction, to reduce downtime.

Artificial intelligence: advantages and disadvantages for companies

The benefits of artificial intelligence for businesses

Productivity gains

The first advantage that appeals to businesses is, of course, the promise of time savings and productivity gains.

Indeed, there are numerous examples of machines performing tasks in place of humans: answering e-mails, entering invoicing data, sorting CVs, etc.

As a result, AI frees up time for employees, who can then focus their efforts on higher value-added missions. The company becomes more efficient, and cuts costs!

A more refined strategy

Artificial intelligence supports companies in their prediction and analysis work, thanks to mass data processing (Big Data).

As a result, organizations are able to fine-tune their strategies, and even stay one step ahead of their competitors, by reacting quickly to future consumer trends and changing consumer behavior.

Improving the customer experience

In marketing and customer relationship management, artificial intelligence is the answer to a major challenge: how to achieve ever-greater personalization, at a time when interactions are taking place less and less in person?

As you might expect, AI is once again emerging as the solution. And with good reason, it can personalize the customer experience based on their preferences and buying behavior.

💡 Let's not forget that, at the same time, increased consumer satisfaction also involves the aforementioned time savings! Working faster means irrevocably satisfying their demands for speed and responsiveness.

Greater agility and innovation

Artificial intelligence enhances business agility, making it easier for companies to adapt quickly to market changes. Organizations now adjust their strategies in real time, without delay (price optimization, production, marketing actions, etc.), and react swiftly to changes in their environment.

In short, AI stimulates innovation by offering the flexibility required for competitiveness. 💪

Limits and issues surrounding AI in business

Of course, such an upheaval in our professional and private lives is not without raising certain questions and fanning a few fears!

First of all, every company needs to consider the ethical issues involved in exploiting consumers' personal data. For example, when collecting data for their systems, they need to make sure they comply with the requirements of the RGPD.

But ethics also means not entering a vicious circle, in which a self-perpetuating system runs the risk of reinforcing one-track thinking and discrimination that is already (unfortunately!) entrenched. Let's take the case of recruiters: they need to find the right balance between human intervention and automation, otherwise they run the risk of missing out on certain "atypical" profiles that don't correspond to statistical standards.

Last but not least, there's the issue of job transformation. Let's face it, AI is scary. Yet, more than the disappearance of certain jobs, it's their mutation that's at stake. Consequently, organizations are obliged to take this issue seriously, supporting their employees as much as possible with training as well as a solid change management approach.

Implementing AI in the workplace: an example

Faced with the challenges of AI, its implementation within companies is no mean feat! You need to be able to deploy systems that are both robust (to support large amounts of data) and secure.

👉 Here's a sample process for a smooth and successful integration.

• Define your objectives. Artificial intelligence takes on many faces. And given how cumbersome it is to implement, it's hard to instill it uniformly into all strata of your organization. So define your priorities, the objectives you want to achieve with it. More productivity? More personalization? Better decision-making?
  
  
• Select appropriate technologies. AI solutions vary according to use case. You can go for Machine Learning, Deep Learning, or even NLP for tasks related to textual data.
  💡If you prefer turnkey, turn to a global business management solution that will harness the potential of AI for you. Such is the case with SAP S/4HANA, an innovative ERP developed to optimize numerous processes thanks, among other things, to artificial intelligence. In addition to automating a multitude of tasks, it provides powerful real-time analyses, even of large quantities of data, for better decision-making.
  
  
• Rely on the right people. Implementing an impactful AI strategy means calling on a diverse range of skills. An interdisciplinary team is essential: data experts, AI scientists and project managers must work hand in hand. And let's not forget the commitment of top management, which is essential for the adoption of technology within the organization!
  
  
• Collect and prepare the data. AI relies on quality data. Identify internal and external data sources, then make sure they are clean, complete and well-structured.
  
  
• Integrate AI into business processes. Once AI models have been validated, it's time to integrate them into existing processes, via software platforms (cloud or otherwise) or in-house applications. The aim? Make AI accessible to all users, without disrupting day-to-day activity.
  
  
• Test and iterate. The AI deployment process never stands still. Regularly test AI performance and adjust models according to the results. Also set up a technology watch procedure to maintain the relevance of your models over time.

💡 As a reminder, it's important to get employees on board when faced with such an upheaval. We therefore advise you to set up training sessions, which will help teams understand AI and its impact on their work. In fact, we invite you to visit the economie.gouv.fr page to discover examples of quality training (theoretical, practical, more targeted on ChatGPT for example, etc.).

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What does the future hold for AI in business?

Artificial intelligence is profoundly transforming businesses. To remain competitive and innovative, they now understand how important it is to deal with these new technologies.

However, as AI evolves, new challenges are emerging, particularly in terms of data security, ethics and the impact on jobs. This is why the future of artificial intelligence must rely more than ever on human-machine collaboration.

This synergy will open up new opportunities, enabling employees to take advantage of the analytical capabilities of artificial intelligence while preserving their creativity and critical thinking. Companies that master this interaction will have a decisive advantage in tomorrow's digital economy. Are you ready?