But trust concerns of the technology behind it is widespread.
This is the second of a three-part series examining how companies are transforming their customer experience strategies through the use of technology. The first article in the series is about the use of all types of AI in the contact center.
In all my decades covering technology, I haven’t seen one catch on with the speed of generative AI. Already, 27.3% of companies are using the technology for their customer-related activities, with another 47.2% planning to do so this year, according to Metrigy’s Customer Experience Optimization:2034-24 global study of 641 companies.
Generative AI is a category of techniques and models that respond to natural language prompts to produce text, images, audio, software code, or other media from data on which they’ve been trained. Examples of generative AI, also known as Large Language Models (LLMs), include Open AI ChatGPT, Google Bard, Microsoft Copilot, and many others.
Potential Uses of Generative AI
The biggest value of generative AI is to automate tasks—keeping in mind that the algorithms are trained on language, not truth, so the ability to put guardrails around data becomes vital to the success of generative AI in business. How can businesses and consumers use the technology?
- Content creation, including papers, articles, proposals, books, art, music, presentations, and software code
- Summaries of calls or meetings, internal or with customers
- Classification of topics
- Training or coaching, based on prompts
- Financial filings (with proper human reviews, of course)
- Investment suggestions, based on goals, investment amount, philosophy
- Health analysis, including possible conditions based on blood test or other diagnostics, and treatment options
- Task management, for personal or team jobs
- Rudimentary legal advice and draft of legal documents
Current Uses of Generative AI
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