The remarkable productivity gains facilitated by generative AI, combined with their unprecedented accessibility, have resulted in historic adoption rates.
As usage of these powerful tools continues to expand, organizations face mounting challenges related to data security, privacy, and regulatory compliance. To better understand how enterprises are approaching generative AI adoption and governance, we surveyed 530 working professionals across five industries — banking + financial services, insurance, biotech + life sciences, manufacturing, and healthcare. Here’s what we learned.
NOTE: To dig deeper into the data, download the full report here.
Key Findings
After analyzing the data, we gleaned some really interesting insights, including:
- 91% of respondents stated they are familiar with generative AI and 64% reported using generative AI tools at work on at least a weekly basis.
- 68% of respondents reported being either fully or partially restricted from using generative AI tools at work.
- ~8% of enterprise employees are circumventing restrictions, continuing to use generative AI tools despite company policies limiting or preventing access.
- Data privacy and security is the number one factor preventing or deterring workers from using generative AI, with 47% of respondents citing concerns in this area.
- 63% of respondents reported that they would be comfortable sharing at least some personal or proprietary information with generative AI tools, regardless of company policy.
Let’s go deeper.
Adoption of Generative AI
The first thing we wanted to understand is usage — are employees actively leveraging generative AI? And if so, how often?
According to our data, we found that only 9% of respondents were unfamiliar with generative AI, and that 64% of employees working in regulated industries are using generative AI weekly or more.
This confirms what we assumed to be true – generative AI is pervasive. Most people know what it is, and well over half of enterprise workers are using it weekly. And as generative AI adoption continues to rise, these are statistics we predict will also rise in turn.
Benefits of Generative AI
Over 90% of respondents agreed that generative AI is at least somewhat valuable in helping with their work, with 59% of respondents reporting that it is extremely valuable. When it comes to roles, workers in finance were most likely to state that generative AI is extremely valuable (67%), followed by IT (51%), and then sales and marketing (48%).
It’s clear that the majority of employees find generative AI beneficial — which is leading to adoption across all regulated and non-regulated industries.
Barriers to Generative AI Adoption
When we asked if employees were fully, partially, or not prevented from using generative AI, 25% of all respondents reported being fully prevented. When we broke the data down further we found that:
- Healthcare (49%) and Manufacturing (57%) organizations were the least likely to have restrictions related to generative AI.
- Workers in Banking + Financial Services (36%) and Insurance (36%) were the most likely to be fully restricted by their employers.
The biggest factor that was reported to deter or prevent using generative AI at work? Concerns about data privacy and security.
Data Privacy
Related to data privacy, 63% of respondents reported that they would be comfortable sharing at least some personal or proprietary information — and 29% reported that they would share any personal or proprietary information.
Sharing sensitive information with LLMs is a major security concern for organizations, and these numbers highlight the importance of a robust security posture regarding generative AI.
Policies and Processes Related to Generative AI
In order to safeguard critical data, companies in regulated industries have started to create policies and processes that outline how employees can and can’t interact with generative AI models.
According to our study, more than half of organizations have either informal or well-defined policies regarding the use of generative AI.
Some industries were more likely to have well-defined policies than others. In order of most likely to have a well-defined policy to least likely, the industry breakdown was as follows:
- Banking + Financial (50%)
- Insurance (43%)
- Biotech + Life Sciences (40%)
- Manufacturing (20%)
- Healthcare (20%)
Processes to Support the Adherence to Policy
Policies are important — but we wanted to understand if companies were also relying on additional training and resources when enabling their employees to use generative AI.
Of all the industries surveyed, we found that Banking + Financial Services employees were most likely to have received at least some training or resources for using generative AI (77%). Workers in Manufacturing (41%) and Healthcare (40%) were the least likely.
Future Outlook of Generative AI
The adoption of generative AI is showing no signs of slowing down. Overall, 83% of respondents across industries and job functions believe that generative AI could become an essential tool for their work over the next 3-5 years. In order to address the very real data security and privacy challenges associated with the usage of generative AI, organizations must establish a comprehensive security posture. A multi-layered approach that integrates policy, process, and technology is critical to creating a secure environment.
Liminal is the technology security layer for organizations looking to leverage generative AI. Talk to the team at Liminal to learn more.
If you’re interested in reading through the research results in more detail, download the ebook here.