Generative AI: Adoption Challenges & Opportunities
This article examines the rise of generative AI, its transformative potential for consulting and software firms, and the key adoption barriers—data quality, tech stack maturity, and change management.
Generative AI has stunned and excited the world! The buzz of AI, Chat GPT, or other AI-driven chatbots is all over.
On a recent road trip, I asked Chat GPT to build an itinerary for my trip. It came up with a complete day-wise activity list, including suggestions for evening dinner venues and gourmet meal options!
Over the past several decades, the possibilities of Artificial Intelligence have been fascinating. In 1950, Alan Turing published a landmark paper in which he speculated about the possibility of creating machines that think. He devised his famous Turing Test. If a machine could carry on a conversation that was indistinguishable from a conversation with a human being, then it was reasonable to say that the machine was "thinking."
Anyone who has interacted with GPT or any other Large Language Models (LLM) - especially in depth and with sophisticated prompting - will know that these systems are remarkable in terms of their output.
So, how do we harness the power of Generative AI?
What does it mean to consulting houses and software services companies?
Challenges in the Adoption of Generative AI
There are two major roadblocks in the adoption of Generative AI technologies.
Data Gathering…
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