Integrating generative AI with company-specific knowledge offers businesses unprecedented opportunities for innovation, efficiency and digital transformation.Generative AI, epitomised by the widespread adoption of technologies like ChatGPT, stands as one of the fastest embraced innovations of our time. A McKinsey study estimates its economic potential to soar between $2.6 trillion and $4.4 trillion annually, primarily driven by its capacity to enhance productivity.
Jean-Pierre van Niekerk, Lead Data Scientist at TrueNorth Group, echoes a pressing concern within the realm of generative AI projects: the risk of abandonment due to factors such as inadequate risk controls, poor data quality or unclear business value. Gartner's estimation suggests that over 30% of generative AI projects and proof of concept work are susceptible to this risk.
Many companies possess a wealth of experience and intellectual property encapsulated within unstructured documents, constituting a reservoir of proprietary information and the culmination of significant human investment in research. However, due to the fragmentation of this information across various data locations and formats, it often remains dormant or inadequately utilised.
Furthermore, integrating generative AI solutions with existing systems and processes allows for a complete, end-to-end process. By seamlessly embedding AI capabilities into platforms, organisations can facilitate efficient query resolution and provide agents with access to curated and cataloged sources of company-specific information.