Universal Containers (UC) wants to improve the productivity of its sales team with generative AI technology. However, UC is concerned that public AI virtual assistants lack adequate company data to ge

The correct answer is A. fine-tune the Einstein AI model with CBM data.. The core concern is that generic public AI models do not have access to UC's proprietary company and CRM data, making their responses less relevant. Fine-tuning the Einstein AI model with CRM data directly embeds company-specific knowledge into the model, addressing the gap. Opti

AI Features for Service (e.g., Einstein Bots, Next Best Action)

Question

Universal Containers (UC) wants to improve the productivity of its sales team with generative AI technology. However, UC is concerned that public AI virtual assistants lack adequate company data to general useful responses. Which solution should UC consider?

Options

Afine-tune the Einstein AI model with CBM data.
BBuild Al model with Einstein discovery and deploy to sales users.
CEnable Agentforce and deploy to sales users.

How the community answered

(22 responses)

A
73% (16)
B
18% (4)
C
9% (2)

Explanation

The core concern is that generic public AI models do not have access to UC's proprietary company and CRM data, making their responses less relevant. Fine-tuning the Einstein AI model with CRM data directly embeds company-specific knowledge into the model, addressing the gap. Option B (Einstein Discovery) is a predictive analytics tool, not a generative AI assistant suited for this use case. Option C (Agentforce) is a strong real-world candidate and uses grounding techniques, but the specific framing of the question - focusing on the AI model lacking company data - points to fine-tuning as the exam-intended answer, as it directly incorporates company data into the model itself.

Topics

#Generative AI#Einstein AI#Fine-tuning#AI Customization

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