The generative AI fascinates but remains experimental. Business AI already transforms business processes. Their convergence is key, provided they anchor innovation in the operational.
Since the arrival of Chatgpt, like many, I have been struck by the speed at which the generative AI has captured attention. Fascinating, sometimes destabilizing, she worries by her ability to automate creation or even, in some cases, to simulate human thought. However, behind this effervescence, I observe another revolution, less noisy, but much more anchored in operational realities on a daily basis, continues its way: that of corporate AI.
For years already, corporate AI depths the business processes in depth. Whether it is invoicing, contractual management, regulatory compliance, supply chain or human resources, corporate AI has demonstrated its robustness, reliability and its measurable impact. While generative AI is still looking for its place, corporate AI is already in a daily age, at the heart of critical environments.
From AI to divergent realities
The generative AI impresses by its ability to produce content (texts, images, codes, etc.), to synthesize information and to suggest unpublished tracks. But it also presents its limits, hallucinations, cognitive biases, safety risks, and persistent uncertainty around regulatory compliance. If its potential is immense, its integration into corporate critical processes is still experimental.
Conversely, corporate AI based on proven technologies such as natural language treatment (NLP), supervised machine learning or intelligent OCR, has imposed itself as a strategic lever. She knows how to interpret even complex business documents, automate repetitive tasks and extract from the value of internal information flows while guaranteeing traceability.
Companies are not only looking for the spectacular effects that generative AI can offer. Above all, they await a measurable return on investment, reliable and interoperable tools with their technological environment (ERP, CRM, GED, etc.), and especially an AI capable of generating efficiency gains on all processes, far beyond individual productivity.
The risk of being mistaken for revolution
Faced with the ambient craze, some companies give in to the temptation to adopt generative AI without real business need, only so as not to appear to be lagging behind. The risk occurs when this choice is made to the detriment of solutions based on corporate AI, which have cases of concrete application. Such a decision runs the risk of neglecting immediate transformation opportunities, not to mention the risks in terms of security, compliance or quality. In many projects, we note that the fastest gains come precisely from better exploitation of existing processes, in particular thanks to the intelligence process, before any generative AI layer. In other words, investing massively in maturation technology, while leaving aside solutions already capable of providing fast, measurable and secure gains is a more than questionable choice for the sustainability of activities.
At a time when the media feeling dictates the trend, it should not be overlooked that real technological ruptures do not always make the headlines. In reality, they often nest out in discreet but decisive improvements such as the ability to process a document faster, to avoid human errors, to streamline a validation chain. It is these “small” operational revolutions which, put end to end, form the base of a digital transformation in depth.
Towards a convergence of the two AIs?
Capable of producing intelligent summaries, generating contextualized responses or offering conversational interfaces adapted to trades, generative AI gradually complete the capacities of corporate AI. But for this promise to become reality, a solid foundation is needed, namely well structured, reliable, governed data. This is precisely what business AI allows, which organizes information, makes it exploitable and creates a confidence base.
In this context, the Intelligence process is an essential prerequisite. By mapping, analyzing and optimizing business processes in real time, it makes it possible to structure operational data and identify where and how AI can really create value. In other words: no relevant and durable AI without process intelligence.
The convergence of these two forms of AI is therefore desirable, but it supposes a logical order: first structure, reliable and automate; Then enrich, dialogue, generate.
The generative AI marks a cultural revolution, corporate AI, an operational revolution. The challenge, for companies, is not to choose between the two dynamics, but to articulate them intelligently. In my eyes, the future belongs to companies capable of marrying these two forces: the creative power of generative AI and the rigor of corporate AI. It is not just a question of technology, but of vision: that of an AI at the service of reality, which transforms companies in depth, in a tangible, measurable and sustainable way. This is what I see on the field, and that’s what fascinates me in this silent revolution.
