The topics of large language models (LLM) and generative AI have officially made the leap from the basement to the boardroom. We are past questioning if these technologies will change how we work; the questions now up for debate are how and when.
For data science and analytics teams, generative AI may provide a reprieve; teams are managing increased demands on their time and attention as the field grows and gains traction. With the advent of generative AI, the patterns and insights hidden within data can be discovered more quickly, and there is hope that repetitive tasks can be automated, freeing up valuable resources to tackle more complex challenges.
To gain insight into how companies are currently using generative AI and how they plan to use it in the future, Alteryx completed a pulse survey of 300 data leaders across four countries. The results reveal where we are and what is to come.
Even experimental use of generative AI shows benefits
Of the almost 40% of respondents who are currently using generative AI in their organization, the majority (53%) rank their maturity as “exploring” or “experimenting” with generative AI, and 13% rate their maturity as “optimizing” or “innovating.”
Even with most generative AI projects in the early stages, 89% of companies currently using generative AI reported seeing either substantial (34%) or modest (55%) benefits of the technology.
What benefits are they seeing? The top three benefits reported were:
- Increased market competitiveness (52%)
- Improved security (49%)
- Enhanced performance or functionality of their products (45%)
Organizations reported using generative AI most for:
- Content generation (46%)
- Analytics insights summary (43%)
- Analytics insights generation (32%)
- Code development (31%)
- Process documentation (27%)
The clear benefits of generative AI may explain why companies not currently using generative AI are interested in doing so soon; 49% plan to do so in the next year.
On an individual level, respondents reported personal benefits to using generative AI – 70% “believe that generative AI could help reduce the repetitive, mundane parts” of their jobs.
The data dilemma: Tackling the perceived risks of generative AI
Both organizations using generative AI and those not yet using it reported data as the largest challenge with using the technology. For organizations currently using generative AI, 3 of the top 4 concerns were related to data: data ownership (29%), data privacy (28%), and IP ownership (28%).
The concerns for organizations not using generative AI were similar, with data privacy concerns coming in at 47% and a lack of trust in the results produced by generative AI at 43%. As the benefits of generative AI are clear, companies that are serious about seeing those benefits should have a risk mitigation plan in place.
What are the main reasons you have not yet implemented generative AI in your organization?
Responses to the survey may be able to provide guidance on how to do that, through trusted vendors and human oversight. 70% of generative AI users reported that they trusted AI to “deliver initial, rapid results that I can review and modify to completion,” and 64% of all respondents said they believe that generative AI can be used now with human oversight of output.
Using generative AI with strong human guidance may be enough to put organizations at ease, but if that’s not the case, interacting with trusted vendors may be another layer of security; 71% of respondents agreed with the statement that “the risks associated with generative AI can be managed by using the technology within existing approved and trusted vendors.”
To what extent do you agree or disagree with the following statements?
AI adoption: One leader makes all the difference
What is the biggest difference between companies using and not using generative AI? A leader driving forward adoption. A shocking 98% of organizations currently using generative AI reported having a singular leader responsible for driving generative AI strategy in their organization. Even more interesting, 75% of those with a singular leader reported that decisions about generative AI in their organization are made by the right people. Adding to this, 34% of companies not using generative AI stated that one of the main reasons why is because there is “no one to take the lead with implementation.”
Who has the most influence driving forward generative AI strategy within your organization?
Who should that leader be? It varies, but the largest percentage of companies (30%) reported their CEO as the person in the organization with the most influence, followed by the head of IT (25%) and Chief Data/Analytics Officer (22%). Of the departments using generative AI, IT was the highest reported at 54%, followed by data science (38%) and customer service (36%).
Generative AI users are excited by and trusting of the tools
When it comes to the future of generative AI, users think the future is bright.
Respondents using generative AI at work are also using the technology outside of work, with 81% reporting that they use generative AI in personal or recreational applications, and 69% state they would “always trust the answers given by generative AI.”
To what extent do you agree or disagree with the following statement: I would always trust the answers given by generative AI.
While 77% of users believe generative AI could replace entire roles or functions within an organization like theirs, the majority are still optimistic and excited about the future of generative AI: 68% of users are excited about the future of generative AI and 69% of users are interested in the future of generative AI.
To what extent do you agree or disagree with the following statements?
Generative AI: The next steps
The dawn of generative AI is upon us, and it’s poised to revolutionize the way we work. Though the pulse survey indicates that many companies are still in the nascent stages of adoption, there’s a growing awareness of the benefits, and early adopters are already reaping the rewards. To convert skeptics into believers, it will be crucial to minimize risk by establishing robust processes and organizational structures that facilitate the use of generative AI. Additionally, partnering with trusted vendors and incorporating human oversight may help ease data and IP ownership concerns.
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