AI: 4 business-centric categories to leverage performance

In an era where artificial intelligence is redefining business practices, Sopra Steria Next publishes a prospective report that reimagines its contours. This approach offers decision-makers an innovative analytical model, categorising AI into 4 business-centric categories. The report anticipates very strong growth in the AI market, with its size doubling by 2028. 

While traditional approaches focused on the technological dimension to analyse the market, they have not been well-adapted to business leaders' decision-making needs. Sopra Steria Next therefore developed a usage-centred approach. Fabrice Asvazadourian, CEO, explains: "Formerly considered a technical subject, relegated to data scientists, the advent of generative AI has brought AI dramatically into the domain of Executive Committees and Boards of Directors." 

Through its apparent ease of access and the fascination it generates, generative AI has truly transformed the rules of the game in business strategy. With the arrival of ChatGPT, then Mistral, Copilot, etc., it's not just the image of AI that has evolved, but also its applications, implications, and development prospects. 

Fabrice Asvazadourian continues: "Our clients sought a strategic compass to fully grasp this revolution. By structuring the market into 4 main types of AI applications, 4 business-centric categories we have called archetypes, we allow our clients to optimise their investments while exploring AI’s true potential. We thus position AI as a true lever for business performance, rather than simply a technological concern." 

From technology to usage 

Until now, the AI market was segmented by purely technological indicators (such as natural language processing, deep learning, machine learning...) that were inadequate to support strategic decision-making. The new analysis methodology developed by Sopra Steria Next now allows the AI market to be segmented by business value – by benefits for clients, users, employees, and the company. 

There are four categories: AI for Machines, which will enable, through advanced simulation functions, to design more optimal machines, factories, whole supply chains, spearheaded by digital twins and their networking in the industrial metaverse. AI for Processes, focuses on management activities, particularly in financial and public services, and in support functions. AI for Humans encompasses successive generations of tools, knowledge management, and various types of virtual assistants. Finally, AI for Software involves everything related to software development and corporate IT activities. 

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. 

*Navigating the AI Era: State of Today and Prospects of Tomorrow, Sopra Steria Next, Sept. 2024 

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