The Rise of Generative AI: A Conversation with Gartner’s AI Research Head

Gartner’s head of AI research, Erick Brethenoux, has witnessed the exponential growth in interest around generative AI among enterprises worldwide ever since the launch of ChatGPT in 2022. The impact has been so significant that even Brethenoux’s 83-year-old mother now understands what he does for a living, thanks to the creative ways she has been using generative AI.

Despite the surge in interest, there is still confusion in the market about generative AI, as highlighted by Brethenoux at the Gartner IT Symposium/Xpo in Australia. Many organizations are grappling with misconceptions about the technology, influenced in part by the terminology used by vendors.

Confusion about different types of AI

The sudden hype surrounding generative AI has led to a widespread misunderstanding among people, confusing AI as a whole with generative AI capabilities. Brethenoux stresses that AI is a vast field that encompasses a variety of applications beyond generative AI.

“AI and generative AI are not the same thing,” Brethenoux explains. “They are not interchangeable.” Generative AI falls under the broader umbrella of AI, which includes decision intelligence, data science, and various other practices.

One common confusion stems from the usage of the AI/ML acronym in the industry. Brethenoux dislikes this acronym, as it implies that AI equals machine learning, which is not accurate. AI encompasses a plethora of techniques beyond machine learning, such as rule-based systems, optimization techniques, and graph technologies.

Generative AI used in only 5% of production use cases

Despite the buzz around generative AI, it currently represents a small portion of AI implementations in production environments. Brethenoux estimates that generative AI accounts for only 5% of actual use cases, with the majority of AI technologies being utilized in diverse applications.

While generative AI garners attention, other AI techniques play a crucial role in ensuring the smooth operation of various systems, such as optimizing airline schedules for on-time arrivals.

AI agents are being confused with static AI models

Gartner has identified agentic AI as a strategic technology trend to watch in 2025. Brethenoux warns against the misconception of equating AI agents with static AI models, emphasizing that they serve distinct purposes.

An AI agent engages actively in performing tasks, while an AI model acts as a passive entity created by algorithms. It is essential to differentiate between the two to avoid misapplication and confusion in AI implementations.

AI confusion causing costly mistakes for organisations

Misunderstanding AI concepts has led organizations to make expensive mistakes in their AI initiatives. Brethenoux recounts instances where businesses have opted for unsuitable AI models, resulting in delays and inefficiencies due to a lack of infrastructure to support dynamic AI capabilities.

AI ‘recess’ over with focus now on operationalizing AI

Following the frenzy around generative AI, organizations are shifting their focus back to operationalizing AI systems and managing technical debt. Brethenoux refers to this as AI engineering and highlights the resurgence of interest post the “recess” phase in early 2024.

As the industry grapples with the practical implications of implementing generative AI capabilities, the spotlight is back on effectively integrating AI solutions into existing infrastructures.