Convergent Computing / CCO
Artificial Intelligence for Enterprises
Artificial Intelligence (AI) in business refers to the application of intelligent systems to automate tasks, analyze data, enhance decision-making, and improve operational efficiency. AI tools such as machine learning, natural language processing, and computer vision are utilized to optimize business functions, boost employee productivity, and drive business value. And businesses who leverage AI aim to improve efficiencies, save time, and reduce costs, making it a valuable resource across various industries.
Luckily, having been an early AI adopter seeing its potential dating back to its early stages, CCO has since worked with customers in practically every vertical adopting real-world AI use-cases as a key competitive advantage. Here is a sampling of those use-cases across nearly 200 private, CCO-led, implementations, to-date.
AI Producing Financial Outlook Reports and Protections. This has been a common scenario for most organizations where we ingest financial statements, real time financial data, and up to date operational and transactional data into the private AI instance for the organization. The AI chatbot enables a finance team to ask questions like: "based on last month's financial results and our rolling 6-month financial data, write a statement on our financial outlook and projections for the next 6 and 12 months that we can provide for our investors." The AI Chatbot formulates its response based on previously crafted statements by execs in the org, and updates its analysis and data based on the most recent financial data.
AI Used in Projecting Manufacturing Production Success. For several manufacturing organizations, CCO connected the organization's private instance of AI to their internal inventory, order processing, sales, and manufacturing systems to gather real time data. The AI chat questions being asked are "how many devices can we manufacture given our current and 60-day confirmed incoming inventory over the next quarter?” or “what components do we lack sufficient inventory to produce whole systems?” or “compare production and current orders and demand trends, what insights can be derived?" Organizations with sophisticated ERP systems can sometimes produce this type of report; however, organizations with disparate systems benefit from private AI setups that assimilates data from multiple systems to come up with analysis and projections.
AI Assisting in Clinical Trial Protections. For life sciences organizations, getting results back from clinical trials from data that has been anonymized and injected into the organization's private instance, with a timely response, is beneficial in getting real time insight to incoming information. The private AI environment leverages the data analytics capabilities of the cloud to produce projective reports. Common questions in these types of environments include things like "comparing the clinical trial results over the past 3, 6, 12, and 18 months, what projections can be made on the success rate of this drug treatment over the next 6-12 months?" Most scientific processes have analytics experts working on the data; however, having a quick analysis from AI has made it easier for medical scientists and researchers to query their data to come up with informational data points to review.
AI in Retail and Consumer Goods. AI is being integrated into consumer-focused systems to help customers find and choose the right product; use AI to answer questions about their product selections; and use AI to supplement customer service queries. Just like how AI is integrated into basic Google searches to provide “answers” not just a list of links, AI on eCommerce sites, for product information searches on enterprise websites, and even as a knowledge base assistant to provide detailed information on sizes, dimensions, weight, material components in use, inventory availability, and providing product spec sheets enhances sites created 5-10 years ago with the latest in AI that’s available today. End users and buyers frequently have questions, and the easier it is for users to ask questions and get answers that make sense to them (than just links to pages and pages of information and files), the better experience users have in their experience to make a purchase.
AI for Law Firms and Internal Legal Departments. There’s no question that anyone doing work with legal content has a LOT of information to sort through, whether it’s court documents, legal precedence information, case evidence, case law information, etc. AI is great about collecting information specific to a matter, summarizing and assessing the targeted content, looking external to public and past case materials, to come up with insight in a matter of seconds. Of course, the legal industry is very cautious of AI as any information gathering and insight has to be based on citable fact and not AI hallucinations; however, going back to the analogy that AI is like a new associate or legal intern, while AI gathers information and provides its analysis, it’s up to a “real” attorney to review the materials before advancing along with the information. However, when the AI system can gather information in minutes that might otherwise take days to gather, attorneys can more quickly start building case strategy and validate data and assumptions.
AI in Banking. Several regional banks and credit unions that have embraced AI to assist their loan offices, customer support personnel, and managers quickly find the latest auto or home loan information, get clarity on step-by-step processes, improve the response time on gathering information to be able to respond to the barrage of questions that come in all day long. The competitive advantage of smaller entities is they are quick and nimble in their response, and AI helps these institutions do better job at quickly responding to their customers. Additionally, AI’s ability to automate processes helps institutions with a smaller support team work smarter and faster with fewer resources available.
AI in Healthcare. In a globally connected (and impacted) healthcare environment, access to the latest viral outbreaks, accessing the latest in symptom analysis, leveraging the latest in treatment information can literally mean life or death for patients. AI is being used to take regularly distributed information, summarize the information into small chunks that frontline workers, healthcare system administrators, and physicians can benefit from having the latest information at their fingertips. AI has helped healthcare workers expand their knowledge far beyond personal experience to tap into the latest knowledge, breakthrough information, and novel approaches to solving healthcare challenges.
AI in Sales and Business Development. Any organization that has a frontline sales or business development team that fills out Request for Proposal (RFP) responses and writes Statement of Work (SOW) documents benefit from AI. AI takes a dozen or two previously written RFP responses and can then craft answers to new RFP documents in minutes. AI utilizes the words, phrases, and content from previous submissions and crafts a response to answer questions on new RFPs. Organizations that used to take 3-4 days to prepare an RFP response are now getting draft content back from AI within an hour, and the frontline teams spend another 3-4 hours cleaning up content, validating information for accuracy, and preparing details that is best done by a human than an AI bot. However, by cutting back the amount of time it takes to respond to RFPs, organizations have been able to double and triple the number of opportunities they can propose responses to with the same number of employees.
AI in Social Media Sentiment Analysis. A big buzzword in the marketing world these days is “social media sentiment analysis,” which effectively a whole side of marketing and public relations that assesses “who’s talking about your company / your brand,” “are they saying good things or bad things,” and “how to get ahead of public relations disasters using the latest in AI resources.” AI is being used to scrape social media sites (X, Instagram, Tik-Tok, Bing, Meta, Baidu, etc.) every time an organization’s name, product name, brand, key personnel names, or even things related to the organization (like the type of products, location/marketplace mentions, etc.) pop up on social media. AI analyzes the information to determine whether the mention could be harmful to the organization (and thus a response needs to be proactively launched). Or something good is said that should be amplified through re Tweets and mentions, maximizing the best capabilities of current market response tools.
A.I. Agent Chat with Structured Data - Demo and Pilot Offering