What is generative AI?
In the field of artificial intelligence, generative AI refers to algorithms that enable the creation of new plausible content from existing content, such as text, audio files, or images. In simple terms, It allows computers to identify patterns in input and then generate similar content based on those patterns.
In contrast to traditional artificial intelligence systems, generative AI is designed to produce a wide range of new content in the form of images, text, and audio. In addition, this differs from predictive AI, also known as supervised learning, which uses historical data to predict future outcomes.
Why the buzz?
After years of research, artificial intelligence (AI) has reached a point that has captured the imagination of everyone, all over the globe. From students and Salesforce candidates to CEOs and industry leaders.
Are your news feeds filled with chatgpt updates, AI tools, and speculation about the future? That's what I thought, so is ours! It's everywhere... and as AI tools unlock new possibilities, excitement grows, but it is still unclear what exactly these tools can accomplish and how they work.
How does generative AI work?
The creation of new content is accomplished using generative adversarial networks (GANs). In a GAN, two neural networks are involved: a generator that generates new data and a discriminator that evaluates that data. Together, the generator and discriminator work to create content that is indistinguishable from real data as a result of the feedback they receive from each other.
AI & Salesforce
Artificial intelligence is only as good as the data it is powered by.
As part of Salesforce's efforts to be one of the earliest CRM vendors to implement AI capabilities, Salesforce Einstein was launched in September 2016. By combining Artificial Intelligence with its Software-as-a-Service (SaaS) solution, it was able to provide predictive analytics, natural language processing (NLP), and machine learning capabilities to customers by using data gathered on every user action.
Examples include but are not limited to:
- Forecasting and lead and opportunity scoring improve sales by predicting whether a customer will buy a product.
- In the context of customer service, it helps with case classification and routing so that retention or problems can be predicted.
- In marketing, engagement scoring and predictive recommendations can help predict who is likely to engage with an email and increase conversion rates.
- In commerce it helps increase revenue by predicting if a particular product is more or less likely to be purchased based on information about the customer.
Through layering Einstein and generative artificial intelligence, Salesforce could:
- Create a smarter, more personalized chatbot that can understand, anticipate, and respond to customer questions.
- Increase first-time resolution rates by providing more accurate answers to nuanced customer queries.
- Analyse customer resolution data to identify trends, drive continuous improvement, and accelerate bot training.
- Salesforce can train the AI to automatically generate drafts of knowledge articles based on all the case notes employees write, greatly reducing the time to create and maintain them.
- The better the quality and relevance of knowledge across the company, the more valuable self-service portals and chatbots will be, allowing human agents to focus on complex issues and build long-term customer relationships.
Although the current wave of generative models is very powerful, AI can generate inaccurate and even harmful outputs, as well as false information. Whether it is a service agent or a knowledge expert, keeping a human reviewer on board will be crucial for the foreseeable future.
Salesforce recently published five guidelines for trusted generative AI development in light of the considerable opportunities and challenges associated with this technology. In these guidelines, Salesforce describes how generative AI can be implemented in enterprise technology and how to balance its transformative potential with its potential risks.
Summary
Combined with Salesforce's long-standing expertise in artificial intelligence, generative AI models will revolutionize customer service, enabling companies to operate more efficiently, respond more empathetically to customer concerns, and resolve cases more efficiently. Lets watch and see.