Go From Information to Knowledge with GenAI 

Rocket Software

Business users dedicate too much of their workweek searching for, organizing, analyzing, and acting on endless streams of information to satisfy operational workflows. This is further exacerbated with the exponential growth in data that organizations must capture, store, manage and access to deliver value. To improve efficiency and productivity, organizations lean into content management, packaged and homegrown applications to manage and create information experiences.  These applications are foundational to streamlining and automating important business processes, which includes working with many supporting pieces of transactional content: business contracts, account statements, and text in transactions such as work item summaries. And there’s no overlooking supporting business documents like technical manuals and other industry-specific directions and mandates. With the increasing availability of data coupled with the need and dependency to leverage all forms of data to drive insight, organizations are looking for innovative ways to stay ahead.

Generative AI (GenAI) and, more broadly, conversational AI experiences have sparked the imagination of users, software architects, and industry executives. Through GenAI, users benefit from more natural and nuanced interactions that consume fewer resources while producing fresh insights, for both internal and customer-facing business processes. Architects and technology implementors enjoy the simplification of their data processing pipelines with less maintenance and faster innovation cycles. And executives are excited about GenAI for next-generation organizations arriving today, business-creating transformations, and growth rewards from investors and the marketplace. AI is transforming traditional information into differentiating knowledge for greater business and industry impact.

The table below summarizes the stakeholder impacts of integrating GenAI to create information experiences. 

Table 1: Traditional vs GenAI Approaches

Stakeholder 

Topic 

Traditional 

GenAI 

Users  

Inquiry  

Search queries 

  • Arcane syntax   

  • Needed user precision - exact words for key matching required   

Natural language prompt 

  • “Just ask” – simplifying user training   

  • Bring greater nuance to target outcomes   

Users  

Insights  

Results list 

  • Users must often read large lists of information to derive insights  

  • Users must refine inquiries and know exact words for key matching  

Answers with references 

  • “Just ask” – simplifying user training   

  • Bring greater nuance with statistical insights and conversations, over a broader set of related information  

Architects / Engineering  

Data Processing  

Structured indexing 

  • Requires precise data structures known ahead of time  

  • Manual and expensive maintenance, leaving orphaned data that is hard to manage  

LLM vectorization 

  • Delivers post-hoc relationships without naming specific indexes  

  • Greater automation that matches concepts and meaning, making it easier to find “a needle in a haystack”  

Architects / Engineering  

Pace of innovation  

Mobile & cloud datastores 

  • Nearing apex of innovation in scaling down (mobile) and up (cloud) traditional databases  

  • Not many low hanging fruit opportunities  

Mobile, cloud, and local LLMs 

  • Many innovative options that match various on premise, local device/data center, or cloud use cases  

  • Numerous models and use cases existing and emerging  

Executives  

Competitive differentiation  

Incremental improvement 

  • Differentiate by economizing org designs, cost improvements, and industry consolidation  

Next-gen transformation 

  • Differentiate by modern products experiences and speed of operations with built-in efficiencies   

Executives  

Investment for growth  

Limited growth levers 

  • High capital investments with less market, brand, and scale impact 

 

Multiple times returns 

  • Faster rewards from investors and market, brand transformation, and scale  

This is the first entry in a series that explores the role that GenAI plays in transforming content management. Be on the lookout for our next blog where we’ll explore some of the challenges faced when adopting GenAI.

For more information about Rocket® Content Smart Chat (Smart Chat), Rocket’s GenAI-powered capability that makes the retrieval of critical data and information quick and easy, download the brochure or speak to an expert today.