The Call for Ending Discrimination Between Classic AI and GenAI Approaches

The Call for Unifying Traditional and Generative AI Approaches

In the ever-evolving world of technology, a new transformation is taking centre stage - General AI (GenAI). Unlike its specialized counterparts, GenAI is more visible, conversational, and accessible, making it a game-changer for businesses.

Shivanku Misra, an AI expert and Vice President overseeing enterprise advanced analytics and AI initiatives, is currently leading the charge at Wells Fargo. Meanwhile, at McKesson, he has also held a similar position, demonstrating his deep understanding and commitment to the field.

Forward-thinking organizations are embedding GenAI capabilities within their analytics platforms and designing AI solutions that span structured and unstructured data. This shift is leading to the creation of intelligent systems where forecasting, summarization, explanation, and action co-exist, streamlining business operations and decision-making processes.

However, the integration of GenAI is not without its challenges. Companies often create separate teams for GenAI exploration, leading to organizational fragmentation and redundant infrastructure. To address this, these organizations are creating talent models that reward cross-disciplinary fluency, ensuring a seamless integration of GenAI into their existing structures.

GenAI is trained on unstructured content and produces new text, images, or code based on context. It is not a specialized tool, but a foundational capability like Excel or PowerPoint, with utility stretching beyond content generation. To get the most out of GenAI, there needs to be a shift in thinking, treating it as a tool that belongs everywhere, not in isolation.

Traditional AI has been helping organizations make smarter decisions, faster through predictive models and machine learning systems. GenAI does not replace traditional AI, but amplifies it, making the work more usable, understandable, and impactful. Both traditional AI and GenAI require governance, training pipelines, monitoring, and an understanding of business context. The divide between the two should be stopped, as they are both driven by the same foundational elements: data, algorithms, and infrastructure.

The most forward-looking organizations are driving toward business value, not just technical novelty. They understand that GenAI can accelerate documentation, summarize insights, help translate between business and technical language, and guide how models are interpreted or communicated. The separation between GenAI and traditional AI is also due to leaders starting conversations with "What can we do with GenAI?" instead of focusing on the desired outcome.

This shift towards GenAI is not just a technological advancement, but a paradigm shift in how businesses approach AI. The Forbes Technology Council, an invitation-only community for world-class CIOs, CTOs, and technology executives, is at the forefront of this movement, providing a platform for these leaders to share their insights and drive the future of AI in business.