{"id":5697,"date":"2024-01-15T19:02:08","date_gmt":"2024-01-15T19:02:08","guid":{"rendered":"https:\/\/www.horsesforsources.com\/?p=5697"},"modified":"2024-01-17T05:39:55","modified_gmt":"2024-01-17T05:39:55","slug":"process-intelligence-genai_011524","status":"publish","type":"post","link":"https:\/\/www.horsesforsources.com\/process-intelligence-genai_011524\/","title":{"rendered":"Process intelligence unlocks faster and better innovation with GenAI"},"content":{"rendered":"

\"\"<\/a><\/p>\n

Watch the videocast, here<\/a><\/em><\/h3>\n

Generative AI (GenAI) has been top of mind for leading executives globally since ChatGPT first stole headlines in November 2022, but enterprises have yet to realize anything close to its true value. Organizations must understand that GenAI and large language models (LLMs) cannot act alone; they are only as good as the data built and designed to power them. <\/em><\/p>\n

Celonis Co-Founder and Co-CEO Alex Rinke<\/a> believes that process intelligence tools could hold the key to unlocking faster and better innovation with GenAI, and every enterprise should be keen to learn why.<\/em><\/p>\n

In a recent Fireside Chat<\/a>, I connected with Alex Rinke to understand his perspectives on GenAI and how Celonis will shape the future of the technology. <\/em><\/p>\n

For GenAI to reach its full potential, it needs complete insight into your business\u2014and that\u2019s no easy task<\/strong><\/span><\/h3>\n

While UHG is the world\u2019s largest commercial healthcare enterprise with ~$360B (Sep 30, 2023) in revenues, it is also amongst the largest enterprises by workforce of some 440,000 clinicians, technologists, and market-facing professionals. An enterprise of this size with even greater implications for the health and well-being of over 150 million people must be deliberate when exploring new technologies. That is precisely the approach that is being considered while the world is abuzz with GenAI.<\/p>\n

The ease of using ChatGPT has driven the rapid excitement of GenAI for enterprises\u2014something Alex admitted has taken him by surprise. Despite this, many enterprises don\u2019t yet understand how to deploy it effectively in their organization. The technology needs complete insight into a business to deliver accurate, efficient, and reliable results. Traditionally, this means tackling siloed and unstructured data to create a mature data foundation\u2014a time- and cost-consuming task. For example, developing HFS\u2019 first-of-its-kind large language model (LLM)<\/a> is the result of a six-month process that required a complete restructure of data and a fresh approach to how we work.<\/p>\n

That\u2019s exactly where Alex believes tools like Celonis can help, accelerating the speed of innovation by unleashing the synergy of GenAI and process intelligence.<\/p>\n

Enterprises should put process intelligence at the heart of their operations, serving as an engagement layer for LLMs<\/strong><\/span><\/h3>\n

Technology is best leveraged in combination with other technologies. Throughout the conversation, Alex highlighted how he believes Celonis and other process intelligence tools will be key enablers for GenAI, helping address adoption challenges and delivering more intelligence-data-driven insights and rich process context.<\/p>\n

He explained that process intelligence tools provide a unified view of a business, pulling together all the pieces of fragmented systems and providing a single view for AI models. He called this the engagement layer. This unified view drastically reduces the need for extensive infrastructure changes, accelerating innovation.\u00a0It\u2019s important to note that this doesn\u2019t eliminate the importance of maintaining a high data quality; ultimately, the garbage in, garbage out adage still applies!<\/p>\n

To bring this concept to life, a large bank is working with Celonis to build an LLM-fueled customer service chatbot. To deliver it effectively, the model needs access to internal business processes, the ability to collect data from multiple sources, and an understanding of everything. Celonis had already been deployed across the business, which allowed data to be pulled directly from Celonis with deeper process context, such as where an order is and when it will arrive. This allowed the bank to implement the chatbot faster and deliver more intelligent responses, improving customer experience.<\/p>\n

The Bottom-Line: <\/span><\/span><\/span><\/span><\/span><\/span>Enterprises should consider process intelligence\u2019s role in better connecting their data with GenAI.<\/span><\/span><\/span><\/span><\/span><\/span><\/strong><\/span><\/h3>\n

If GenAI is set to be as impactful as the Internet, as Alex believes, organizations must ensure they are using it to its full potential, or they might just give their competitors an edge. To fulfill its potential, an LLM must have a deep understanding of the business and its data to deliver intelligent answers.<\/p>\n

When enterprises define their GenAI adoption roadmap, they must consider the value process intelligence can deliver if they want the technology to reach its full potential. Celonis understands the power of ecosystems, and Alex teased the idea of partnerships between Celonis and the likes of LLaMA and Hugging Face, so it might be about to get even easier to infuse process intelligence with your Generative AI plans.<\/p>\n","protected":false},"excerpt":{"rendered":"

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