The launch of ChatGPT, Midjourney, and DALL-E has put artificial intelligence (AI) firmly in the spotlight. Yet AI is nothing new, and these applications are just the tip of the iceberg. AI has been present in our daily lives for many years, with social media algorithms, chatbots, and the Waze application just a few examples.
“Generative AI” systems offer sophisticated, high-performance tools and, while they are not yet endowed with "creative" human-like minds, they are playing an increasingly central role in the corporate innovation process. The ability to process and cross-reference huge volumes of data creates an enormous level of knowledge and AI is therefore a valuable decision-making tool, particularly in complex environments.
"AI will continue empowering us, rather than overpowering us."
- Hager Group
Therefore, every stage in the innovation cycle can benefit from AI's formidable capabilities.
Although the term "Artificial Intelligence" (AI) has now entered the mainstream, it is often misused to overstate the capabilities of a product or service. Talking about AI requires an informed vision to avoid misunderstandings and promote responsible use of this technology.
AI refers to the process by which a machine reproduces certain cognitive functions, such as learning and problem-solving. At a more basic level, AI can also refer to rules preset by human beings, dictating how computers should behave in specific situations.
Within the definition of AI, we need to distinguish between two specific subfields: machine learning and deep learning.
Machine learning is based on statistical methods and algorithms that enable computers to learn automatically. These algorithms analyze data, learn from it and make decisions based on what they have learned.
Deep learning is a more recent subfield of AI, derived from machine learning. It requires larger volumes of training data, and learns from its environment and mistakes, with less human intervention than machine learning.
OpenAI's ChatGPT and Dall-E and Google's Bard and Midjourney have introduced generative AI to the general public.
Generative AI stems from deep learning and specializes in the independent creation of data and content in contrast to "classic" AI, which is designed to automate certain tasks and create decision-making tools.
In a constantly evolving environment, developing an innovation strategy is essential for companies seeking growth and competitiveness. To achieve these objectives, it’s important to identify value-creation opportunities and define innovation objectives to guide R&D and investment efforts. Innovation strategy is the foundation on which innovative products and services are created, strengthening the company's position in the market and promoting its long-term development.
Given its advanced data-analysis capabilities, AI can play a key role in this phase of the innovation cycle:
Example: Airbnb is looking to tackle the problem of apartments being ransacked by tenants. The company has developed an AI system that can detect people's character traits by scanning as much information as possible online, and thus establish compatibility scores between landlords and tenants.
The use of AI therefore offers companies a valuable competitive advantage in building their innovation strategy.