This article examines the importance of artificial intelligence (AI) integration in companies and provides recommendations for tracking and evaluating the effectiveness of such integration.
AI Adoption: Metrics
Speed of Onboarding
Using AI tools like code explanation makes it easier for newcomers to understand code developers, speeding up the onboarding process. This can lead to significant cost savings for the company.
Employee satisfaction and turnover
AI assistants allow developers to focus on more important tasks , avoiding routine work. This helps reduce burnout and increase employee satisfaction, reducing employee turnover.
Team productivity
Instead of simple metrics such as the number of lines of code, comprehensive metrics should be used metrics like DORA metrics and frameworks for evaluating the performance of engineering teams. The impact of AI on these metrics depends on many factors, but is usually positive.
Code stability and review speed
AI assistants can help find vulnerabilities in code , reducing the cognitive load on the reviewer and the risks associated with the human factor. This saves time and money on code review.
Product Metrics
Metrics such as customer acquisition cost, LTV, NPS, and customer churn will help measure the impact of AI integration on the end user and the company's bottom line. However, noticeable changes may appear only after a certain time.
Glossary
- IBM is an American multinational technology corporation specializing in computer hardware and software, cloud solutions and consulting services.
- SoftServe is a leading Ukrainian company that provides IT services and develops software for various industries.
- Microsoft is an American multinational technology corporation that produces software, computers, gaming devices and other consumer electronic devices.
- OpenAI is an artificial intelligence research company known for models such as GPT-3 and DALL-E.
- Google is an American multinational technology corporation specializing in Internet-related services and products, including AI technologies and cloud computing.
Links
- IBM survey
- SoftServe Research
- Harness Research
- Microsoft research on using Copilot
- Statistics on time spent on code reviews
Answers to questions
What are the key metrics to track to assess the effectiveness of AI integration in a company?
How can artificial intelligence accelerate the onboarding process of new developers?
How does the implementation of artificial intelligence affect employee satisfaction and turnover rates?
What metrics best reflect the increase in productivity of the development team after the integration of artificial intelligence?
How does the use of artificial intelligence affect the stability of the code and the speed of its review?
Hashtags
Save a link to this article
Discussion of the topic – Measure the effectiveness of AI integration in the company: metrics and steps to success
Artificial intelligence (AI) is rapidly being integrated into the work processes of IT companies. This material will reveal how to measure the effectiveness of an AI implementation and what key metrics to track to maximize returns.
Latest comments
8 comments
Write a comment
Your email address will not be published. Required fields are checked *
Максим
Colleagues, the integration of AI in our company is really cool! 🚀 It made my work much easier and accelerated the development of projects. Now I can focus on more complex tasks, while artificial intelligence takes care of the monotonous routine work.
Катерина
Maxim, I completely agree! 💯 One of the key advantages of AI for me was the ease of onboarding new developers. With code explanation tools, it's now much easier for them to understand our code and documentation. This significantly saves time and increases productivity.
Петро
Indeed, the implementation of AI has already begun to bear fruit. 🍎 According to statistics, the use of artificial intelligence in SoftServe increased the productivity of teams by 45% and reduced project development time by almost a third. Impressive results!
Олег
I can't disagree with you, colleagues! 👍 AI has become a real helper in my work. It helps me generate source code, test programs, and even debug. This allows to significantly increase the efficiency of development. 🔥
Віктор
Um, allow me to express some skepticism. 🧐 I don't think that AI is so important and useful. This is just another trend that will soon pass. I prefer traditional methods of work and do not believe in all these newfangled things.
Катерина
Viktor, I understand your concern, but let's look at the numbers. A large UK bank with over 10,000 engineers has seen AI save £7m a year just from speeding up onboarding of new staff. Such results are hard to ignore. 💰
Максим
Viktor, AI also helps to improve the level of employee satisfaction and reduce staff turnover. 👷♂️ According to research, more than half of developers cite burnout as the main reason for layoffs, and AI can take over routine tasks, which will reduce the burden on people.
Олег
I would also like to share my experience. 📖 I recently worked on a complex project where I applied AI to generate code and fix bugs. This saved me dozens of hours of code writing and testing. And time, as you know, is money for the company. Therefore, I consider the integration of AI to be a very effective solution.