Which LLM model are you most likely to adopt for your enterprise?

Machine Learning (ML)Artificial Intelligence (AI)

BERT (Google)18%

GPT-3 (OpenAI)41%

GPT-4 (OpenAI)56%

LaMDA (Google)17%

PaLM (Google)7%

LLaMA (Meta AI)7%

Other (Please comment)2%

282 PARTICIPANTS

2.9k views2 Comments

Sort by:

IT Manager in Construction2 years ago

I am for Claude 3.

Fractional CIO in Services (non-Government)2 years ago

Other. It really depends on what they offer the org and what prolems we need to solve.

It's much like cloud storage - 90% of what is offered is the same, it's the 10% of uniqueness that will be valuable.

Content you might like

Have you deployed AI agents? What’s been an unexpected use case you’ve discovered?

Which of these tools are you using to monitor/identify shadow AI use in your organization? (Choose all applicable to you)

SaaS discovery solution (like Netskope or Cisco Umbrella) 26%

CASB tool 38%

Packet sniffing (deep packet inspection) tool 26%

EDR tool/platform 26%

Something else (please share in a comment) 18%

N/A — we’re not currently using any tools to track shadow AI8%

View Results

How would you rate the readiness of your systems and data to work with AI?

data is scattered across different applications16%

some systems have APIs, but not everything connects71%

we have a single source of data, but without AI integration12%

our data is already being used by AI models2%

View Results

Which AI development platform or framework are you primarily using today?

OpenAI / GPT-based

Anthropic (Claude)

LangChain or Flowise

Building custom LLM stack (open-source models + vector DBs)

Curious to hear what’s working best for your team, especially around cost, speed, and integration flexibility.

How does your organization balance using AI to make entry-level jobs more efficient with the need to maintain a robust talent pipeline? Are there specific roles you're purposely shielding from automation to retain pathways for employee development?