“At the start of the gold rush, the first to strike it rich were actually the ones selling shovels and pickaxes; similarly, despite its lightning-fast market penetration, generative AI generated only limited revenue in 2023, essentially for cloud providers and their graphics processor manufacturers,” explained Fabrice Asvazadourian, Chief Executive Officer of Sopra Steria Next. “Our study shows that 2024 will mark the beginning of an exponential rise in the monetisation of generative AI, with more and more services being sold, both by major tech players as an extension of their current product ranges and by a multitude of startups that are beginning to emerge, targeting specific use cases.”
Technology on the verge of scaling up
According to research by Sopra Steria Next, the generative AI market is expected to increase tenfold by 2028 to around $100 billion, equating to annual growth of 65%. This commercial take-off in the generative AI market can be explained in particular by the introduction of policies and guidelines governing the controlled use of GenAI, particularly in the business world, as well as greater competition between major generalist AI models and the rise of specialised large language models (LLMs) enabling the proliferation of applications targeting multiple use cases.
The study predicts that generative AI will continue to mature and includes recommendations for senior executives to gradually implement generative AI applications that will enable managers and their staff to familiarise themselves with these new tools while embedding guidelines and policies for controlled, compliant use of generative AI into their operating methods and modernising their data management technology.
This approach is based on projections of how generative AI’s capabilities and use cases will develop over the next 36 months:
Currently, and over the next 18 months, its use will mainly involve GenAI solutions provided by software development companies and technology partners, focused on assistance and service for users under their supervision and with them in charge of its improvement. Sopra Steria Next calls this first phase “GenAI augmented by humans”. The study highlights four highly mature areas in which generative AI can be applied: digital marketing, software development, customer service and knowledge management (see below).
Next, the following 18 months will see a major acceleration in the deployment of generative AI at scale. This will include new GenAI applications that will expand and improve upon existing predictive artificial intelligence applications. The first company-specific use cases will also start to emerge, with applications refined by startups or customised in cases where the company has a mass of proprietary data. This second phase, which the consultancy calls “GenAI customised by proprietary data”, will see companies substantially ramp up their investments in GenAI skills and infrastructure.
Finally, in three to four years’ time, GenAI – by combining optimised generalist multimodal models with specialised models – will have greatly reduced its risk of error and hallucinations, and will be ready to start being applied to industrial-scale business processes with virtually no need for supervision, giving rise to a new wave of automation. GenAI will then enter this third phase, which Sopra Steria Next calls “GenAI applied to the core”.
By 2028, the main business sectors to use generative AI will be financial services (25%-30%), healthcare (15%-20%), consumer goods and retail (15%-20%), and media and entertainment (10%-15%).
Sopra Steria Next forecasts that the number of users will double – or even triple, depending on the scenario – by 2028 (400-600 million users), and that the proportion of paying users will more than triple (from 15% to almost 50%). Daily use of generative artificial intelligence is expected to increase by a factor of 6, driven by the explosion in GenAI applications designed for specific use cases. In other words, by 2028, we’ll be spending 30 to 60 minutes a day using our preferred generative AI applications, with average revenue per paying user of between $30 and $40 a month.
In 2024, 100 use cases for generative AI in four key fields
The study carried out by Sopra Steria Next highlights around a hundred use cases for generative artificial intelligence in the four priority fields for its application in 2024, with the potential to boost productivity by between 7% and 10% over the next three years, if deployed at scale in these four areas:
In customer service, generative AI, with its ability to assimilate multiple sources of data in real time and deliver recommendations in natural language, is opening up a new era of competitiveness. Initial rollouts have shown both a significant improvement in the self-service rate thanks to more “empathetic” virtual assistants and greater efficiency on the part of contact centre operators in handling customer enquiries, as well as in their ability to proactively rebound to convert service requests to sales. For example, Sopra Steria is working with a major European administration to create a conversational assistant to handle simple questions and document requests, so that staff can focus on more complex cases.
In digital marketing, through its ability to ingest data of all kinds, generative AI brings brands closer to their customers, resulting in greater engagement and conversion and significant gains in productivity. This is made possible by GenAI’s ability to prepare more personalised content drafts tailored to each type of media, to develop a finer segmentation of audience targeting and to refine the keyword strategy on increasingly vocal search engines. For example, Sopra Steria Next helped a major consumer goods group to optimise the online display and promotion of its several tens of thousands of pages on its various websites, by combining analytical AI and generative AI.
In software engineering, as Sopra Steria is already seeing on a daily basis in its pilot teams, generative AI is improving the various stages in the software development life cycle, particularly at the development level, by 1) helping to generate and review new code and improving existing code by detecting errors, suggesting improvements and refactoring; 2) optimising tests; and 3) improving user support by helping to bring self-service levels to a new high through its capacity for “empathetic” dialogue, and even for formalising expressions of requirements by optimising the consolidation of customer feedback, analyses of customer usage and internal brainstorming.
Finally, in knowledge management, generative AI is revolutionising the creation and accessibility of knowledge bases. For example, for an international law firm, Sopra Steria Next developed a series of tools based on generative AI, enabling all employees to access past legal consultations more easily and efficiently, to anonymise documents to make it easier to consolidate information, to draw up drafts for simple consultations, and to summarise and classify the various documents involved in each case file.
“What these cases show us is that generative AI represents a whole new paradigm for business competitiveness, so it’s vital that leaders move from the discovery and familiarisation phase to a true programmatic approach in 2024,” continued Fabrice Asvazadourian. “The challenge lies in implementing this technology gradually, striking the right balance between proactivity and control, and coordinating the technological, regulatory and human dimensions involved. At a time when everyone is talking about ‘humans augmented by AI’, our experience with our customers in 2023 has convinced us that the key to success is to ensure that GenAI also remains ‘augmented by humans’.”
