GEN AI and Automation, How it impacts the way Businesses operate across multiple industries:
In this series I will be writing how different real world business use cases across multiple industries can take advantage of Gen AI and LLM, augmenting with their existing Automation investments.
Part 1 of N: The GenAI Wave and What it means to Business Automation?
We are very fortunate to be in the middle of the Golden Age in Tech, especially accelerated by AI and Automation. Concepts like Gen AI, LLM are seeing a lot of life and every Technology Vendor partner are positioning a AI first approach, and many have started working on re-calibrating their products with AI strategy.
Wit the amount of awareness that is created in Social Media, Blogs, Tech Conferences about Gen AI, I can safely presume there is a basic understanding of what is GenAI, LLM , Foundation models, RAG Fine tuning and related items. But I will just put in a “one-liner” to be safe.
Generative AI a.k.a GenAI is a Artificial Intelligence technology that uses Machine Learning models to generate output for an input query.
Foundation Models are a form of GenAI models. LLAMA, BERT, BLOOM, GPT are examples of foundation models.
The Machine Learning Model that is used in GenAI is called Large Language Model a.k.a LLM. LLM is a deep learning model that is trained using unsupervised massive volumes of datasets (that contains user interactions, coding, business interactions across industries, public knowledge bases) and can generate output that may be text, code, image.
Now let’s put all in perspective with some examples and FAQ.
ChatGPT is a chatbot that responds to user queries by going against a ML model that is trained on Open AI’s GPT foundation model.
Hey Can I use ChatGPT as a chat bot for my case workers to search knowledge bases to respond my claims users coverage question for Disability claim?
Big NO.
Firstly, ChatGPT goes against a foundation model that is trained on massive unsupervised dataset that has NO idea about your organization’s Disability claims. Secondly, there is no governance on how the responses are generated in alignment to Bias, accuracy etc., Thirdly, because they are ungoverned and untrained on your enterprise data, the results are inaccurate.
So, when any Enterprise taking advantage of GenAI must make sure the GenAI model ticks the boxes below,
- Governance,
- Security,
- Scalability,
- Reporting,
- Relevance.
Retrieval Augmented Generation a.k.a RAG is a technology in machine learning that helps any LLM to fine-tune the generated response to the Enterprise’s use case.
Business Automation
Business Automation involves automation of Enterprise tasks across Industries. The different flavors of Business Automation includes,
ECM a.k.a Enterprise Content Management,
RM a.k.a Records Management,
Workflow to automate business processes,
Process Mining to understand how your Manual and Automated Business Processes perform,
RPA to automate manual tasks that involves a user sitting on a machine and clicking buttons,
Decision Management in automating and governing business rules at scale,
Capture/Imaging to intelligently extract information out of structured and unstructured documents,
Web content management to manage and control your wed based interfaces,
Customer Communication Management is how you communicate with your customers using both Digital Tech and Mails.
Enterprises have already made Significant investments past 20 years in above areas with multiple vendors like IBM, Opentext, Pega etc.,
In this series, I will break it down how the GenAI wave with LLM’s can augment these existing investments of Enterprises to powerfully drive the Modernization wave for Business use cases across Industries.
