1️⃣ Getting started: The real problem
In many companies, strategic goals sound like this:
- "We need to use AI more."
- "Our marketing should generate more leads."
- "We need to become more efficient."
These statements describe wishes - but not controllable goals.
The problem quickly becomes apparent in everyday life:
- Teams experiment with ChatGPT
- individual employees test Claude
- Gemini is being tried out somewhere
Ideas, prompts and individual automations emerge.
But after a few months, the crucial question remains unanswered:
What has actually improved?
- More turnover?
- More leads?
- faster processes?
- better productivity?
Without a clear definition of objectives, AI quickly becomes a tool gimmick with no strategic effect.
This is exactly where OKRs (Objectives & Key Results) come into play.
They help you to turn vague intentions into measurable progress
2️⃣ Why goals often remain vague in everyday life
There are three typical reasons why goals are rarely formulated clearly.
Wishful thinking instead of a goal system
Many goals arise spontaneously:
"We should use more AI."
This is an idea, but not a goal.
A goal must always contain three things:
- Direction
- Measurability
- time period
Tool focus instead of result focus
Many companies start with:
- ChatGPT
- Claude
- Gemini
- Midjourney
- Automation platforms
But tools are only tools.
The central question must always be:
What result do we want to improve?
Lack of target methodology
Many organizations work without a clear target system.
OKRs offer a simple structure here.
3️⃣ The basic OKR principle
OKRs consist of two elements.
Objective
A qualitative objective that provides direction.
Example:
Our marketing generates predictable qualified leads via AI-supported content production.
Key results
Measurable results.
For example:
- 30% more qualified leads
- Increase content production from 4 to 12 articles per month
- Reduce production time per article by 40
The simple OKR formula
Objective:
We want [improvement or change]
Key Results:
- Metric 1: from X → Y
- Metric 2: from X → Y
- Metric 3: from X → Y
4️⃣ AI as OKR co-pilot
Large language models can help enormously with target definition.
Especially for three tasks:
1️⃣ Specify goals
2️⃣ Develop metrics
3️⃣ Critically examine target systems
In this article, we deliberately use three different AI systems:
- Google Gemini
- ChatGPT
- Anthropic Claude
And we look at how each tool can be used in the OKR process.
5️⃣ Step 1: Collecting ideas with Google Gemini
Gemini is particularly suitable for:
- strategic brainstorming
- Idea generation
- Perspectives
Imagine the following scenario:
A consulting company with 20 employees wants to use AI.
The initial goal is:
"We want to make greater use of AI in the company."
That's too vague.
So we start with Gemini.
Prompt example for Gemini
We are a consulting company with 20 employees. Our goal is to use AI sensibly in the company. Help us to derive possible strategic corporate objectives from this. Formulate 5 possible objectives using the OKR method and suggest possible key results for each.
Typical Gemini response
Gemini often generates multiple perspectives:
Example Objective 1
AI increases the productivity of our consultants.
Key Results:
- Reduce research time per project by 40
- Reduce proposal preparation from 3 hours to 1 hour
- Accelerate project preparation by 30%
Example Objective 2
AI improves the scalability of our marketing.
Key Results:
- Produce 3× more content per month
- Generate 50 % more organic leads
- 20% more website traffic
Why Gemini is strong here
Gemini is particularly suitable for:
- Breadth of ideas
- prospects
- strategic options
You quickly get
- several possible target directions
- different KPIs
- inspiration
Gemini works here like a strategy workshop partner.
6️⃣ Step 2: Structure OKRs with ChatGPT
Once several target directions exist, they need to be structured.
This is where ChatGPT comes into play.
ChatGPT is particularly strong at:
- Structure
- Clarity
- frameworks
- Formulation
Prompt example for ChatGPT
We are a consulting company with 20 employees. We want to achieve the following strategic goal: AI should make our consulting processes more efficient. Create a clear OKR set for a period of 90 days. The objective should be formulated in an inspiring way. The key results must be measurable.
Example result
Objective:
AI significantly increases the operational efficiency of our consulting team.
Key results:
1️⃣ Reduce proposal preparation from an average of 3 hours to 1 hour
2️⃣ Reduce research time per project by 40%
3️⃣ 80% of consultants actively use AI at least twice a week
4️⃣ Reduce project preparation per customer from 5 hours to 2 hours
Why ChatGPT is particularly good here
ChatGPT helps very well with
- clear structure
- Clearly formulated OKRs
- logically structured target systems
It acts like a strategy consultant that creates order.
7️⃣ Step 3: Critical analysis with Claude
Now comes the most important step:
The critical examination of the OKRs.
Many OKRs look good at first glance - but are difficult to measure in practice.
Claude is particularly strong at:
- Analyzing
- criticism
- suggestions for improvement
- logical weaknesses
Prompt example for Claude
Critically evaluate this OKR set.
Objective: AI significantly increases the operational
efficiency of our consulting team.
Key results:
- Reduce proposal preparation from 3 hours to 1 hour
- Reduce research time per project by 40 % - 80 % of
consultants use AI twice a week
- Reduce project preparation from 5 hours to 2 hours
Please check:
1. are these key results really measurable?
2. where could implementation problems arise?
3. what improvements would you suggest?
Example Claude analysis
Claude could answer:
Problem 1
"80% of consultants use AI twice a week"
Problem:
- Usage is difficult to measure
- No clear tracking method
Improvement:
80% of consultants document at least two AI-supported work steps in the internal project tool every week.
Problem 2
"Reduce research time by 40 %"
Problem:
Improvement:
Reduce average research time per project from 2.5 hours to 1.5 hours.
Why Claude is strong here
Claude works excellently as a:
critical sparring partner.
It helps with:
- Weak points
- Measurability
- Implementation
8️⃣ The combined AI workflow
The best approach is not one tool.
But a workflow consisting of several systems.
Step 1
Gemini → Ideas and perspectives
Step 2
ChatGPT → Formulate structured OKRs
Step 3
Claude → Critical analysis and improvement
This process often only takes 20-30 minutes.
A strategy workshop would normally take several hours.
9️⃣ Immediately actionable steps
If you want to develop OKRs with AI, start like this:
Step 1
List your current goals or wishes.
For example:
- more leads
- more efficient processes
- better content
- less administrative work
Step 2
Use Gemini for ideas.
Prompt:
Formulate possible OKR objectives from these strategic
wishes.
Step 3
Use ChatGPT for structure.
Prompt:
Create a clear OKR set for 90 days.
Step 4
Use Claude for criticism.
Prompt:
Check these OKRs for measurability and feasibility.
Step 5
Define baselines:
- Current state
- target value
- Time period
1️⃣0️⃣ Conclusion: Which tool is best for OKRs?
All three systems have different strengths.
Google Gemini
Strengths:
- Strategic brainstorming
- Perspectives
- Diversity of ideas
Ideal for:
early phase of goal definition
ChatGPT
Strengths:
- Structure
- frameworks
- Clear formulations
Ideal for
concrete OKR formulation
Claude
Strengths:
- critical analysis
- logical thinking
- Recognize weak points
Ideal for:
Quality inspection of OKRs
The optimal AI process
The best approach is a combination:
Gemini → Ideas
ChatGPT → Structure
Claude → Criticism
The result is a vague wish:
"We want to use AI."
A measurable target system such as:
Objective:
AI increases the operational efficiency of our consulting team.
Key Results:
- Proposal preparation time of 3 hours → 1 hour
- Research time of 2.5 hours → 1.5 hours
- 80% of consultants document two AI applications per week
And this is where the real competitive advantage arises:
Not through AI tools - but through clear goals.
🚀 Next step
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