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Embracing the GenAI Wave: A Journey with Devoteam

As the CEO of Devoteam, I am thrilled to discuss with you a revolution of similar magnitude to the arrival of the internet: the widespread adoption of Generative AI. Let’s start by recalling that AI is not a new topic. 

Gen AI vs. AI: Bridging the Divide

AI is not new. Companies in the aviation industry (for dynamic pricing) and insurers (for actuarial calculations) have been using algorithms for decades. But, Generative AI changes the game: it integrates text, language, images, and video, making this technology more accessible and closer than ever to our natural way of communicating. The good thing? It’s no longer confined to the knowledge of mathematicians and data scientists. Generative AI speaks to us, using human symbolism rather than machine symbolism, which was previously reserved for experts.

By now we’ve all gotten used to having a conversation with AI like you would with a colleague – that’s the promise of GenAI. It’s about democratising technology and unlocking productivity gains for everyone. 

The challenge today? Not to overestimate its short-term effects or underestimate its considerable medium-term impact. Goldman Sachs has estimated the impact of Generative AI on the global economy. Hold onto your seats: over 10 years, they estimate a +7% impact on the global GDP, which amounts to $7 trillion in value creation. 

Managing New Times: Embracing the Impact

So Generative AI isn’t just underway, it’s happening now. There is not a single company that is not under pressure right now, at the highest level. They will have to reconcile, on the one hand, the very strong pressures to demonstrate immediate uses, with, on the other hand, the start of a deeper transformation and its medium-term consequences on our business models, our organizations, our ways of working, our products…

How can you feel the pressure is there? ChatGPT went from 0 to 100 million users in two months and reached nearly 200 million users in early 2024. For comparison, it took the Internet 15 years to reach 100 million users.

So with which use case can you start? The first low-hanging fruits are productivity gains, increased automation, controlled use of data, retro-documentation of old applications, and much more… “For example, we observe measured productivity gains of 8% at a French software editor with 5,000 developers, at a cost of less than 0.1% of the payroll.”

Devoteam, who is at the heart of this movement already explored numerous use cases with clients. To summarise, there are three recurring axes:

  1. Large-scale deployment of “individual” Generative AI enterprise versions like ChatGPT: These are looking for innovation in daily tasks for all teams. In any case, if you don’t do it, employees will go elsewhere or use unsecured consumer platforms with your confidential data.
  2. 2nd level add your own data – Designing “in-house” Generative AI platforms, which require new architectures and technical foundations: LLM, SLM, vector databases, to host multiple use cases. 
  3. 3rd level – you need to govern better to keep it running and then lével 2 will be better – Projects to control data within organisations, to prepare these new assets which will be able to take on considerable value.

Convictions of Devoteam: Guiding Principles

At Devoteam, we stand by five core convictions that shape the approach to GenAI:

  • Tech Foundation: Mastering cloud, data, and cybersecurity lays the groundwork for GenAI adoption.
  • Multi-disciplinarity: Embracing diverse skill sets reduces dependency on IT and fosters collaboration.
  • Time Management: GenAI accelerates time-to-market, necessitating a reevaluation of traditional timelines.
  • Cost-Efficiency: Start small, go to market fast, and scale strategically for maximum impact.
  • Governance and Ethics: Proactive measures ensure transparent, responsible AI implementation.

Impact of AI on Your Business: Looking Ahead

GenAI opens doors to new opportunities, from intuitive data access to conversational interactions and automated content generation. How do you get started? 

The difference won’t lie in strategy, but in execution. There’s no point in making plans for five years given the speed of evolution in this technology. Therefore, we must dive in right away.

Use the following 4 points to shape your path:

  1. Roll out GenAI to all your “knowledge worker” employees immediately, rather than letting them work in isolation.
  2. Don’t give up on your cloud/data/cyber/legacy transformation, even if you’re asked to prioritise investments.
  3. Build your in-house AI architecture foundations without delay, as they will give you a competitive advantage.
  4. Foster a cross-functional approach within your company, like an ecosystem: IT & business of course, but also between different business units, your clients, your partners…

In conclusion, take into account that a monolithic approach, relying on a single technological foundation, cannot meet all needs. Who would have imagined that Microsoft, armed with OpenAI, would surprise the market in this field as early as 2023? Who could have predicted Mistral, a small French team, becoming world champions in just a few months? And who would have thought that HuggingFace would suddenly become the GitHub of AI?

Let’s start today, what are you waiting for?