7 Eye Opening Generative AI Statistics From Microsoft Survey

Generative AI is slowly but surely becoming an integral part of businesses. Sadly, business leaders lack a clearly defined strategy to deploy the technology across the whole enterprise successfully with Microsoft Survey. These are the findings from Microsoft's latest survey, which included 31,000 employees from more than 31 countries. The survey was published inside Microsoft Work Trend Index report.

Are you interested in learning more about the key findings from the survey? If yes, then this article is for you. In this article, you will learn about seven shocking generative AI statistics about generative AI from a Microsoft survey.

7 Eye Opening Generative AI Statistics From Microsoft Survey

Here are seven eye opening generative AI statistics from Microsoft survey.

1. 79% of Business Leaders Think That Using AI Is A Must To Stay Competitive

Business leaders realize the importance of generative AI. That is why four out of five (79%) business leaders think that generative AI is pivotal for their business success. It can give your business a competitive advantage over your competitors. Microsoft has already deployed their coi-pilot at large scale enterprises such as BP, Amgen, Koch Industries. Expect this trend to continue in the near future as more and more businesses deploy these generative AI tools.

2. 78% of Office Workers Use Their Own AI Tools

Microsoft survey also points towards a strong demand for generative AI tools amongst employees. According to a Microsoft survey, 75% of survey respondents said that they use generative AI tools on their job. This translates into double the number of survey respondents using generative AI tools in the last six months.

That is not all, 78% of office workers said that they are using their own AI tools. Just like the bring your own device trend, this is leading to a new trend called bring your own artificial intelligence. This can have many security implications for businesses as these tools don’t have the guardrails required to ensure safe use.

3. 60% of Leaders Believe That Organization Leadership Lacks The Vision To Roll Out AI Across The Organization

Despite growing interests among employees, most large scale enterprises are still reluctant when it comes to jumping on the generative AI bandwagon. This is partly due to the lack of leadership vision. Microsoft survey shows that 60% of business leaders said that their organization lacks the vision to roll out generative AI across the enterprise. Most businesses don’t even have a clearly defined artificial intelligence implementation strategy.

Colette Stallbaumer, general manager of Copilot and Cofounder of Work Lab at Microsoft eluded to this fact in his pre recorded briefing when he said, “While leaders agree using AI is a business imperative, and many say they won’t even hire someone without AI skills, they also believe that their companies lack a vision and plan to implement AI broadly; they’re stuck in AI inertia.”

4. 34% of Respondents Use Generative AI Tools When It Is Integrated Into Existing Productivity Apps

Even though artificial intelligence can come in different shapes and sizes, generative AI is the focus of all the attention these days. According to a Gartner survey, the most common way employees interact with generative AI technology is when it is deeply integrated with productivity apps or apps they use to perform their day to day tasks. More than one in three (34%) respondents use generative AI when it is integrated with productivity apps.

5. 25% of Respondents Use Generative AI Tools With Prompt Engineering

Another way users are using to interact with generative AI tools is prompt engineering. With 25% respondents saying that they are using prompt engineering to get the desired output from generative AI tools.This percentage will increase in years to come as more employees get better at prompt engineering. Since it is a new domain, very few possess the prompt engineering prowess required to get the best output from these generative AI tools.

6. 21% of Respondents Are More Interested In Training Their Own Generative AI Models

Large scale enterprises who have the resources and expertise to develop their own large language models are doing it. They also have access to tons of data, which they are using to train their internally created AI models. They invest heavily in boosting their hardware infrastructure such as buy dedicated servers or buy virtual private server to train the large language model. 21% of survey respondents shared their interest in training their bespoke generative AI models.

Creating and training large language models requires resources but also has its advantages too. It gives you more control over the quality of data that is being used for training the large language model. Additionally, businesses can also customize it to meet their specific business needs. More and more businesses have realized that using a general purpose model won’t cut it for fulfilling specific business use cases. That is why they are investing in developing highly specific models in house instead of relying on third party solutions.

7. 19% Are Using Standalone Generative AI Tools Such as ChatGPT and Gemini

Probably the biggest surprise from the Microsoft survey came when only 19% of users said that they are currently using standalone generative AI tools such as ChatGPT and Gemini. We expect this number to be much higher. The primary reason for this low number is the shift towards co-pilots and integration of generative AI tools in productivity and other apps employees use on a day to day basis.

Leinar Ramos, who is the senior director analyst at Gartner advises businesses to keep an eye on the costs. According to him, “As organizations scale AI, they need to consider the total cost of ownership of their projects, as well as the wide spectrum of benefits beyond productivity improvement.”

With 59% of survey respondents saying that they are not sure how to quantify the productivity gains from employee use of generative AI tools, there would be more emphasis on cost-benefit analysis. You do not want the cost to grow out of proportion while the productivity gains are low.

Which of these generative AI statistics shocked you the most and why? Share it with us in the comments section below.