2 customisable OKR examples for Ai Research Team

What are Ai Research Team OKRs?

The Objective and Key Results (OKR) framework is a simple goal-setting methodology that was introduced at Intel by Andy Grove in the 70s. It became popular after John Doerr introduced it to Google in the 90s, and it's now used by teams of all sizes to set and track ambitious goals at scale.

Creating impactful OKRs can be a daunting task, especially for newcomers. Shifting your focus from projects to outcomes is key to successful planning.

We have curated a selection of OKR examples specifically for Ai Research Team to assist you. Feel free to explore the templates below for inspiration in setting your own goals.

If you want to learn more about the framework, you can read our OKR guide online.

Building your own Ai Research Team OKRs with AI

While we have some examples available, it's likely that you'll have specific scenarios that aren't covered here. You can use our free AI generator below or our more complete goal-setting system to generate your own OKRs.

Feel free to explore our tools:

Use our free OKR generator
Use Tability, a complete platform to set and track OKRs and initiatives, including a GPT-4 powered goal generator

Our customisable Ai Research Team OKRs examples

We've added many examples of Ai Research Team Objectives and Key Results, but we did not stop there. Understanding the difference between OKRs and projects is important, so we also added examples of strategic initiatives that relate to the OKRs.

Hope you'll find this helpful!

1. OKRs to identify and assess AI tools available in the market

Identify and assess AI tools available in the market
Evaluate 10 potential AI tools against predefined criteria by the end of Q2
Research and select 10 AI tools for review
Assign scores to each tool based on criteria
Define specific criteria for evaluation
Compile a detailed report illustrating the pros and cons of each examined tool
Identify and examine each tool's features
Compile detailed comparison report
Analyze pros and cons of each tool
Conduct 20 market interviews to determine popular AI tools amongst industry experts
Draft comprehensive, insightful interview questions
Conduct, record and analyze the interviews
Identify and target 20 industry experts in AI

Implement this OKR

2. OKRs to establish our simple AI startup using open-source tools

Establish our simple AI startup using open-source tools
Develop a basic AI model using chosen open-source tool by end of week 8
Develop and test a basic AI model using the selected tool
Start learning and mastering the selected tool
Choose a suitable open-source tool for AI model development
Acquire first 10 users to test our AI model and gather feedback by week 12
Reach out and onboard first 10 users for testing
Set up a feedback collection system
Identify target audience for AI model testing
Identify and assess 5 suitable open-source tools for AI development by week 4

open-source-tools user-feedback ai-developer user-experience-researcher ai-development-team user-experience-team

Implement this OKR

Ai Research Team OKR best practices to boost success

Generally speaking, your objectives should be ambitious yet achievable, and your key results should be measurable and time-bound (using the SMART framework can be helpful). It is also recommended to list strategic initiatives under your key results, as it'll help you avoid the common mistake of listing projects in your KRs.

Here are a couple of best practices extracted from our OKR implementation guide 👇

Tip #1: Limit the number of key results

Having too many OKRs is the #1 mistake that teams make when adopting the framework. The problem with tracking too many competing goals is that it will be hard for your team to know what really matters.

We recommend having 3-4 objectives, and 3-4 key results per objective. A platform like Tability can run audits on your data to help you identify the plans that have too many goals.

Tability's audit dashboard will highlight opportunities to improve OKRs

Tip #2: Commit to weekly OKR check-ins

Setting good goals can be challenging, but without regular check-ins, your team will struggle to make progress. We recommend that you track your OKRs weekly to get the full benefits from the framework.

Being able to see trends for your key results will also keep yourself honest.

Tability's check-ins will save you hours and increase transparency

Tip #3: No more than 2 yellow statuses in a row

Yes, this is another tip for goal-tracking instead of goal-setting (but you'll get plenty of OKR examples above). But, once you have your goals defined, it will be your ability to keep the right sense of urgency that will make the difference.

As a rule of thumb, it's best to avoid having more than 2 yellow/at risk statuses in a row.

Make a call on the 3rd update. You should be either back on track, or off track. This sounds harsh but it's the best way to signal risks early enough to fix things.

How to turn your Ai Research Team OKRs in a strategy map

Your quarterly OKRs should be tracked weekly in order to get all the benefits of the OKRs framework. Reviewing progress periodically has several advantages:

It brings the goals back to the top of the mind
It will highlight poorly set OKRs
It will surface execution risks
It improves transparency and accountability

Spreadsheets are enough to get started. Then, once you need to scale you can use a proper OKR platform to make things easier.

Tability's Strategy Map makes it easy to see all your org's OKRs

If you're not yet set on a tool, you can check out the 5 best OKR tracking templates guide to find the best way to monitor progress during the quarter.

More Ai Research Team OKR templates

We have more templates to help you draft your team goals and OKRs.

OKRs resources

Here are a list of resources to help you adopt the Objectives and Key Results framework.

To learn: What is the meaning of OKRs
Blog posts: ODT Blog
Success metrics: KPIs examples

Create more examples in our app

You can use Tability to create OKRs with AI – and keep yourself accountable 👀

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