A Strong Development
According to Sopra Steria Next's study, the global AI market, estimated at $540 billion in 2023, is expected to experience spectacular growth of 19% per year, to more than double by 2028. This remarkable expansion is attributed to technological advancements
and dynamics specific to each of the four AI categories.
In addition to projecting the growth and revenue of each category by 2028, Sopra Steria Next has analysed the trends and technologies that will drive this growth.
- Supported by the rise of 5G/6G networks, the proliferation of connected sensors, and the emergence of digital twins, AI for Machines is revolutionising machines, factories, and supply chains.
- AI for Processes is driven by the convergence between automation solutions (RPA, OCR), flow management (BPM, process mining), and ERP. This integration improves anomaly and fraud detection, as well as the automation of support functions and public services.
- Generative and predictive AI, now used in key sectors such as finance, health, and e-commerce, is propelling AI for Humans towards rapid growth, thanks to decision support tools and virtual assistants (like ChatGPT) that offering unprecedented efficiency gains.
- Finally,AI for Software, stimulated by the growing popularity of low-code and no-code solutions, is transforming coding practices while reducing errors and increasing developer productivity.
Taking these factors into account, our consulting firm projects:
- AI for Machines to grow 13% annually to reach $330 billion in 2028, representing 26% of the global AI market.
- AI for Processes to grow 18% annually, peaking at $390 billion in 2028, accounting for 31% of the AI market.
- AI for Humans to increase from $130 billion to $380 billion over 5 years, representing 30% of the total AI market, the most significant growth in volume.
- AI for Software to triple in size, reaching $170 billion by 2028, with annual growth of 25%.
Steering investments using the 4 categories
For decision-makers facing the complexity of AI, understanding how to invest in AI is as crucial as recognising its potential. Sopra Steria Next's based approach allows AI investments to be mapped strategically and compared against peer investment profiles within the same sector.
For example, Sopra Steria Next recommends that financial services decision-makers distribute their AI investments evenly among 3 of the 4 categories, excluding AI for Machines, while the manufacturing, energy, and defence industries should focus most of their investments there. For the pharmaceutical and healthcare sectors, the firm recommends a balanced investment profile between AI for Machines and AI for Humans.
Succeeding in Industrialisation
"Today, only one in seven AI algorithms developed in companies is finally deployed at scale; in other words, 85% are abandoned at the experimentation stage," notes Fabrice Asvazadourian. "The challenge for leaders is therefore clear, it's about optimising this ratio. This is the objective of the 4 categories, built on hundreds of use cases across a wide variety of industries."
To effectively industrialise AI within their organisations, Sopra Steria Next recommends that companies simultaneously address four challenges:
- Concentrate 80% of efforts on use cases already mature in their industry, avoiding blind spots and exploiting the complementarity between Predictive AI and Generative AI.
- Modernise Data/AI technological platforms to manage unstructured and synthetic data, and equip themselves with appropriate AI solutions.
- Integrate new AI algorithms into IT industrial processes without degrading performance, ensuring their traceability and scalability over time.
- Secure the recruitment and development of AI tech talent and create an environment conducive to the confident adoption of these new tools by all employees.
Faced with the major challenge of large-scale AI deployment for European companies, Sopra Steria Next has developed dedicated offerings, from acculturation to POC realisation, modernising Data/AI technological platforms, and industrialising with the implementation of our AI Factory. This holistic approach enables companies to develop AI progressively, according to their needs and maturity.