LLMs alone won’t solve all your AI challenges. Here’s what will.

LLMs alone won’t solve all your AI challenges. Here’s what will.

Business leaders are setting themselves up for AI failure in a misguided rush to train and deploy their own LLMs.

The truth is that LLMs alone can’t solve all AI challenges. What can? A carefully-designed system that integrates data, AI, and automation to answer your questions and autonomously take action for you.

Here we explain what that looks like, as well as the AI anti-patterns that lead to expensive mistakes.


[Image: Aleona Pollauf / Salesforce]

AI agents might just be the secret to the survival of hybrid work

Many employees are pushing back against returning to the office, even though leaders insist that in-person work is essential for success. Here’s where AI can help. AI agents can boost productivity, innovation, and collaboration, and keep both employees and leaders satisfied with their work setup.


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What we're reading


This newsletter was curated by Lisa DiCarlo Lee , Contributing Editor at Salesforce .


What’s the biggest question you have about AI? Let us know in the comments. We read each one and may just feature yours in a future newsletter!


Cecilio Benn

SEO Specialist | Driving Organic Growth & Enhancing Digital Presence | Expertise in Keyword Research, Content Optimization, and Data Analysis

1w

It’s like trying to bake a cake with only flour; LLMs are a great ingredient, but they need the right mix of data, AI, and automation to truly rise! 🤖 The real key to AI success is a thoughtful system that works together, not just a rush to deploy shiny new tech. And as for hybrid work, AI agents could be the productivity heroes we didn’t know we needed. Let’s make sure we’re building a solid foundation before we dive into the AI kitchen! 🍰 #AIIntegration #HybridWork #AIinBusiness #Automation #DataDriven #Leadership

Muhammad Barbarosa Javed

Experienced Business Support Analyst | Application Support Specialist | Jira & Power BI Enthusiast

1w

Even though companies are trying hard to test and adapt AI to automate and replace their current lengthy tasks, but AI itself is in its learning stage. Take an example of Strawberry. Ask chatGPT how many 'r' are there in strawberry and often it fails to give the correct answer. Even the data we give it returns different interpretations every time we rerun the question. It is causing security issues and companies then have to make policies and request their employees to avoid giving exact code or company information. The company needs full team with LLM experts who know the boundaries and limitations of the language.

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