Generative AI can support business operations by summarising information, drafting content, answering questions, and automating defined tasks. This article explains what generative AI does, how it differs from traditional AI, and where executives can apply it responsibly. One example is an assistant built with Slack and Vertex AI.
“ Generative AI could add $2.6 trillion to $4.4 trillion annually to the global economy. “
4 things Generative AI Does Well
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Discovery GenAI can sift through massive content data sets to find hidden patterns.
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Summarization Condense large volumes of text, images, video/audio etc into summaries.
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Creation AI-generated content, from text and images to music and software code.
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Automation Automate repetitive tasks, such as report generation or customer support, freeing up time for strategic activities.
You may be thinking .. “but don’t existing AI applications do that? Whats so special”.
The speciality of Generative AI is the ability to do all of the above using english language commands instead of programming languages or other sophisticated software tools to interpret between the human and the machine.
Practical use cases
Retail & CPG
- Creative assistance
- Conversational commerce
- Customer service automation
- New product development
Financial Services
- Financial document search and synthesis
- Enhanced virtual assistants
- Regulatory and compliance assistant
- Capital markets research
Healthcare
- Digital patient concierge
- Public and private contextual search
- Expedite Prior Authorization (PA)
- Clinical trial report generation
Telecom
- Customer or employee service automation
- Network planning and operations
- Employee knowledge search
- Contract analysis and negotiation
Manufacturing
- Machine-generated events monitoring
- Customer service automation
- Document search and synthesis
- Product/content catalog discovery
Media & Entertainment
- Media content discovery
- Internal document and media search
- Branded consumer interactions
- Content summarization and metadata
5 specific and practical steps to help you get stared on your GenAI journey
In the following series of 5 articles, we will explore the foundational ideas behind generative AI
- “Core Capabilities of Generative AI”: What You Can Achieve: Delve into the four key capabilities of generative AI—creation, summarization, discovery, and automation. This article will explore how each function can be leveraged to boost productivity and streamline decision-making within your organization
“Core Capabilities of Generative AI”: What You Can Achieve:
- “Generative AI vs Traditional AI: Understanding the Difference”: This article explains the difference between generative AI and traditional AI, helping executives understand the distinct value generative AI brings to businesses.
“Generative AI vs Traditional AI: Understanding the Difference”:
- “Building blocks of a GenerativeAI solution stack”: A brief executive level primer into the various technologies, tools and techniques that are used today build GenAI solutions.
“Building blocks of a GenerativeAI solution stack”:
- “Getting Started with Generative AI: A Step-by-Step Guide for Leaders”: A practical guide for executives on how to launch their first generative AI use case in 30 days. From identifying the right domain to measuring KPIs, this article will simplify the process of AI adoption.
“Getting Started with Generative AI: A Step-by-Step Guide for Leaders”:
- “Generative AI in Action: Industry-Specific Case Studies: This article will provide real-world examples of AI transforming core business operations. Want to explore how GenAI can drive results in your business? Check out our executive guide or speak with our solution team.