Oxygen achieves massive company-wide productivity increase through AI (GPT-4) integration

1. Business-wide access to the best tools

We evaluated all of the AI LLM tools available and came to the clear conclusion that GPT-4 provided the best possible quality for the team with direct access (instead of through another platform that uses GTP-4 like POE).

2. Group training sessions

Each month, we ran multiple AI training sessions via video call and in-person during our team events. These started quite basic, on understanding prompts and how to use the interface… eventually progressing to be more advanced, covering topics like token limits, code interpreter mode and mermaid coding via GPT.

3. Company-wide buy-in

Everyone at Oxygen, regardless of role or position, was encouraged to use GPT as much as possible to improve efficiency without impacting quality. Managers were required to be experts in AI to provide better training and help with any questions the rest of the team might have.

4. AI Charter

We drafted an AI Charter for our team to sign. Essentially, making it clear that while AI use is encouraged, misuse will not be tolerated. This document also clarifies that employees are responsible for ALL AI outputs and, therefore, must personally check everything written by ChatGPT. By signing this charter, our team also agrees that all content must have some element of human editing or influence not to seem generic or a departure from our brand tone of voice.

5. AI Certification Program

We have developed two certification programs, as the first had to be rewritten 2 months later due to all of the changes within the industry and the tools we were using. These exams test knowledge of the technology behind AI, understanding of the tool, and best-practise ways to use AI to generate amazing results.

Client #1: Average time logged

Before

10h 43m

After

6h 53m

Client #2: Average time logged

Before

12h 16m

After

4h 40m

Client #3: Average time logged

Before

6h 13m

After

3h 32m

Total Average

Before

9h 44m

After

5h 01m

Metric: Time spent brainstorming content ideas each week

There was an increase of approximately 26.6% in respondents who spent "less than 5 hours" each week brainstorming content after the AI implementation compared to before.

Metric: Time spent creating written content each week

There was an increase of approximately 26.8% in respondents who spent "less than 5 hours" creating written content each week after the AI implementation compared to before.

Metric: How often do you feel overwhelmed with work?

There was a decrease of approximately 49% in the respondents who said they 'often' feel overwhelmed after AI implementation compared to before.

	Before AI	After AI
Extremely Confident	5.3%	6.7%
Somewhat Confident	52.6%	53.3%
Unsure	26.3%	33.3%
Not that confident	15.8%	6.7%

	Before AI	After AI
Extremely Confident	5.3%	6.7%
Somewhat Confident	52.6%	73.3%
Unsure	42.1%	20%
Not that confident	0	0

Practical use of the tools and peer review of output was the fastest driver of AI adoption and proficiency. Teams could quickly compare results and help colleagues find flaws and solutions by using AI. Review sessions were an important part of this and without oversight from management, this wouldn’t have happened so quickly.
Only giving teams access to the tools is not enough. After suggesting that many of our clients start using ChatGPT, we found that the quality of their output decreased as they didn’t have sufficient training to get good results or even to benchmark what a good result might be. Teams must understand how to use the AI tools, and which tasks might not be appropriate for automation in this way, in order to get an optimal result.
Management should never penalise someone for just using ChatGPT for a task. But must always penalise someone if the quality of that output is not good enough. Ultimately, they are responsible for that output, and a response like “Well, that’s what ChatGPT gave me” will not suffice.

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Oxygen achieves massive company-wide productivity increase through AI (GPT-4) integration

How we facilitated learning and adoption

1. Business-wide access to the best tools

2. Group training sessions

3. Company-wide buy-in

4. AI Charter

5. AI Certification Program

Project Management Data

Average time logged per specific deliverable

we found that AI training and implementation led to a 48.5% reduction in time spent on one of our core services.

Client #1: Average time logged

Client #2: Average time logged

Client #3: Average time logged

Total Average

Quantitative Results

Metric: Time spent brainstorming content ideas each week

Metric: Time spent creating written content each week

Metric: How often do you feel overwhelmed with work?

Qualitative Results

Metric: Confidence level in creating high-quality written content without peer review

Metric: Confidence in colleagues’ ability to create high-quality written content without peer review

Impact on the team

What Our Team Are Saying

Key learnings & challenges

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