Generative AI: demystification for SMEs and ETIs

Dive into the heart of generative AI and discover how it's redefining the landscape for SMEs and SMBs. This article reveals key strategies related to generative AI to overcome apprehension and harness its potential for innovation and growth.

In a world where technology is evolving at a dizzying pace, generative artificial intelligence (Gen AI) is emerging as a revolution that cannot be ignored by businesses of all sizes. Its potential to transform working methods, stimulate innovation and create new opportunities is undeniable.

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However, despite its promise, the adoption of generative AI raises many apprehensions among SME and ETI managers. These fears, often linked to the perceived complexity of the technology, the financial implications, the impact on employment, and concerns about data security, are major disincentives.

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But it's crucial to understand that generative AI is not just the preserve of large companies with considerable resources. It is also accessible and beneficial to SMEs and SMBs, provided a thoughtful and informed adoption process is put in place. This article aims to demystify generative AI, addressing common apprehensions in a transparent and enlightened way, and providing keys to overcoming them.

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As managers and decision-makers, you'll discover in this article how this content creation technology can be your ally in the quest for innovation and competitiveness, and not a source of worry.

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Join us in this exploration to lift the veil on generative AI, understand its transformative potential for your business, and initiate the journey to successful, secure adoption.

A few definitions - What are the different categories of AI?

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What does the term "AI" mean?

Artificial Intelligence (AI) is the umbrella under which all other categories of AI are grouped. It refers to all the theories and techniques used to create machines capable of simulating human intelligence. AI is the dream of imitating human cognitive abilities: learning, understanding, reasoning, even feeling.

What is machine learning? 

Machine learning is a sub-discipline of AI that focuses on the ability of machines to learn from data. Instead of explicitly programming a computer to perform specific tasks, it is taught to learn from experience. A classic example is e-mail filtering (spam or non-spam) based on pattern recognition in received messages.‍

What is deep learning?

‍Deeplearning is a subset of machine learning that uses deep artificial neural networks. These networks are inspired by the structure and functioning of the human brain, and are capable of learning to perform tasks by processing large amounts of data. An emblematic example is facial recognition, where the system learns to identify and differentiate between human faces with astounding accuracy.

‍Whatis generative artificial intelligence (Gen ai)?

Generative artificial intelligence (AI) is a branch of AI that focuses on the creation of new and original content, from text generators to image generators, music and beyond. Unlike traditional AI, which is often limited to analyzing and interpreting data, generative AI learns from vast existing datasets to produce novel creations.

What does the term "LLMs" mean?

‍LargeLanguage Models (LLMs), such as ChatGPT, are specific types of generative AI specializing in text comprehension and generation. These models are trained on huge text corpora to predict the next word in a sentence, enabling the generation of coherent, contextually relevant text.

How does generative AI work?

Large language models (LLMs) like GPT (Generative Pre-trained Transformer) and associated generative AI tools build their answers using probability generators to predict the next word in a sequence of words, based on the context provided by the previous words. They use massive computing power to provide the most appropriate answers.

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• Instruction: also called prompt. This is the initial request or problem to be solved by the AI, such as generating a specific text or image.
• Generative model: at the heart of the system, it relies on pre-trained Deep Learning algorithms to process instructions and data.
• Training data (Dataset): this is the data previously used to teach the model how to perform its tasks. The larger and more varied the dataset, the more accurate and relevant the model's responses will be.
• Supplementary data: this is additional information provided to refine the task requested of the AI in input data. This could be a link to a website, an image or a PDF document, for example.
• Answer: the result generated by the AI, be it text, images or other forms of content.

What are the main models? 

It is possible to distinguish 6 main models of generative AI:

• Text generation
• Video generation
• Image generation
• Code generation
• Audio generation
• 3D model generation

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What arethe best generative ia? ‍‍Listofthe main AI tools on the market

On the market, several generative AI tools stand out for their efficiency and accessibility, based on sophisticated algorithms. ChatGPT, developed by OpenAI, uses advanced algorithms to become famous for its ability to generate complex text responses. Midjourney, for its part, relies on advanced algorithms to specialize in the creation of high-resolution images from text descriptions.

Text generators

• GPT-4 by OpenAI, the most powerful on the market today
• Anthropic's Claude 3, which comes close to GPT-4 in terms of performance, but is currently unavailable in France.
• Copilot from Microsoft, integrated into the Office suite
• Gemini from Google
• Llama 2, the AI from Meta
• Mistral 7B from Mistral AI, Open Source and French start-up.

Image generators

• Midjourney V6 by US research lab Midjourney, the most powerful generative AI tool for images and graphic design on the market today
• DALL.E 3 from Open AI
• Stable Diffusion of Stability.AI
• Adobe Firefly, the most accessible, with a wide range of tools (text to image; generative fill; generative recolor; text to vector image, etc.).

Video generators

• Runway Gen-2 is a generative AI model for animating images
• Pika, an animated text-to-video model
• Open AI's Sora, currently under development, which uses a simple prompt to produce a stunning video lasting just a few seconds.

Examples of real-world applications of generative AI in business

• Day-to-day tasks : the AI can draft or synthesize e-mails, take notes and write meeting minutes, lightening the administrative load on teams.
• Customer service : AI manages customer queries, analyzes data to improve the customer experience and can even offer virtual assistants
• Marketing : it creates advertising messages, optimizes customer segmentation and personalizes campaigns for more effective targeting. It can also be a valuable aid in content creation and image generation.
• Sales : AI develops sales scenarios, writes sales pitches and personalizes communications with customers, contributing to better prospect conversion.
• Human Resources : automating the filtering of applications, personalizing training paths, and drafting job offers are all tasks that AI can facilitate.
• Innovation : by stimulating creativity, identifying innovative opportunities, accelerating test cycles and improving strategic decision-making, generative AI drives innovation.

Demystifying the main obstacles

Perceived complexity

One of the main concerns surrounding generative AI is the complexity it seems to entail. Executives ask: do you have to be a data expert to adopt this technology? The answer is reassuringly no. Thanks to increasingly intuitive tools and targeted training, AI is becoming accessible, even to non-specialists. Awareness programs help to dispel apprehensions, highlight key AI functionalities that can be effortlessly integrated into organizations' processes, and identify AI applications.

Investment costs

The cost may seem prohibitive at first, but it's important to consider investment in generative AI as a long-term strategic investment. Indeed, the gains in productivity, efficiency and the creation of new offers pave the way for a considerable return on investment. Adaptive solutions exist, from the most economical ones that take advantage of already existing tools, to tailor-made developments that can be staggered over time to match the investment possibilities of SMEs and SMBs.

Fear of employee replacement

It's one of the most common ethical questions, the idea that AI could replace employees is a common misunderstanding. Rather than replacing humans, generative AI is designed to augment and extend human capabilities. It takes over repetitive or complex tasks, freeing employees for higher value-added activities that require creativity and human judgment. It's complementarity that strengthens teams, rather than competition that threatens them.

Data security on generative AI tools like Chatgpt or Google

In an era where data is precious, its security is a top priority. Adopting generative AI doesn't mean neglecting confidentiality. By choosing reputable suppliers who do not train their algorithms with company data (a key point to check), and by implementing robust cybersecurity practices with its security teams, companies can reap the benefits of AI while protecting their sensitive data. Specific training courses can also help to understand and manage data security risks.

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The introduction of an AI usage charter is a decisive step towards securing data, based in particular on the recommendations of the European Union. This charter functions as a set of guidelines that clearly define how and for what purposes data can be used by generative AI.

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By confronting these obstacles, we see that each can be overcome with a well thought-out strategy and the right tools. The key is to start with measured steps, adopt a continuous learning approach, and focus on the growth potential that generative AI can unlock for SMEs and SMBs.

Benefits of adopting Generative AI for SMEs and SMBs

Increased efficiency

Automating repetitive tasks with AI reduces human error and boosts productivity. For example, automating customer relationship management and after-sales services means that a greater volume of requests can be handled without sacrificing service quality.

Product/service innovation

The adoption of generative AI opens up new horizons in product and service design. It makes it possible to explore options that were previously unthinkable, such as personalized products in real time, or ultra-responsive customer services thanks to intelligent chatbots. With AI, companies can not only enhance their existing offerings but also create new ones, harnessing data to anticipate customer needs and respond proactively.

Competitive advantage

SMEs and SMBs that adopt generative AI have a clear advantage over competitors who stick to traditional methods. AI can identify hidden market trends, anticipate consumer demands and personalize offerings, enabling them to position themselves as market leaders.

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Adopting generative AI is therefore not a matter of following a trend, but a strategic move towards a more resilient, innovative and competitive enterprise. Highlighting these benefits can inspire leaders to take the step into the future of AI.

First step towards the adoption of generative AI

For SMEs and SMBs ready to explore generative AI, the road to adoption may seem fraught with uncertainty. However, with a structured approach and experienced partners, the first steps in this digital transformation can be taken with confidence and efficiency.

Generative AI awareness and training

AI adoption starts with a clear understanding of what the technology can deliver. At Dynergie, we've developed awareness and training programs to help companies get to grips with AI. Our events, conferences and webinars are designed to dispel myths and demonstrate the practical benefits of generative AI. We also offer specialized training to master tools like ChatGPT and for the development of specific agents, enabling companies to take charge of their digital transformation.

Identification of relevant use cases

For AI adoption to be successful, it must be relevant to the company's current operations. This requires an in-depth inventory of existing processes, and the identification of internal and customer use cases where AI could have the most significant impact. At Dynergie, we support companies in this crucial stage through workshops and design sprints to unveil innovative solutions thanks to AI.

Development and implementation of AI tools

Identifying the right tools to implement AI is essential. Whether using existing tools or developing specific agents, each company needs to find the path that suits it best. Initial testing is essential to gather feedback and fine-tune solutions. Dynergie is committed to providing expert advice in choosing tools, customizing them and integrating them into companies' existing operations.

Implementation and support

The implementation of generative AI systems does not end with the deployment of the tools. Ongoing support is crucial to ensure smooth integration into daily practices. Employee-tailored training, rigorous project management and change management consulting are all elements that Dynergie provides to ensure that AI adoption generates sustainable added value.

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These first steps towards the adoption of generative AI are steps towards a future where innovation and efficiency are the keys to success. With the right support and resources, SMEs and SMBs can turn generative AI into a major asset for their growth and competitiveness.

Conclusion

The integration of generative AI in SMEs and SMBs is less a question of trend than of transformation, essential to remain competitive in a constantly changing world. The benefits are obvious: greater efficiency, advanced innovation and a significant competitive edge. However, apprehensions about complexity, cost, job substitution and data security may stand in the way of this forward-looking technology.

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At Dynergie, we've demonstrated that these obstacles are surmountable. By focusing on awareness, training, identification of relevant use cases and personalized support, we have made generative AI not only a practical reality, but also a vector for growth and innovation. The adoption of this technology, far from replacing humans, amplifies their capabilities and opens the door to unexplored horizons.

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We invite you to consider generative AI not as an insurmountable challenge, but as an exciting opportunity. The era of generative AI is here, and it's accessible to all companies ready to embrace change and invest in their future. Now is the time to be part of this revolution, and Dynergie is here to guide you.

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So take some time to think: how could generative AI transform your business?

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Find out more about our AI offers: https://www.dynergie.fr/sous-offres/integrer-lia-dans-votre-entreprise

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If you wish to contact us : https://www.dynergie.fr/equipe