According to a report by the developer of the Alteryx analytics platform conducted among 300 data managers from Australia, the United Kingdom, Canada, and the United States, around 40% of data analytics managers use generative AI in their work.
Survey respondents’ companies use it in content generation (46%), analytics information summary generation (43%), and analytics information generation (32%). 31% use it to develop codeand 27%, to process documentation.
In view of the results, it can be established that companies are curious about AI but most do not use it in their daily activities and processes. 53% claim to be exploring or experimenting with it, yes. But only 13% have AI models already in use and are working on optimizing them. Meanwhile, 34% indicate that they are formalizing its use, moving from pilot programs to the production of a generative AI solution.
Of those who use it to some extent, the majority see it as beneficial: 55% say that it has provided them with some model benefits, and 34% achieved notable benefits thanks to it. Among these benefits is greater competitiveness in the market (52%), improved security (49%) and better performance or operation of their products (45%). Another 10% did not find any benefit with its use, and another 1% indicated that it is still early to be able to make any affirmations in this regard.
On many occasions, it only takes one business manager to adopt generative AI as a preferred project and encourage the rest of the company to adopt it. In 98% of cases, companies report that a single person in charge was responsible for driving their generative AI strategy.
Of these, in 30% of the cases it was the CEO, and in 25%, the person in charge of IT. In 22%, it was done by the person in charge of data or analytics. (firstaiduc.com) Meanwhile, among the companies that do not use generative AI, 35% say they have no one who can lead their implementation.
Security is one of the main barriers to the adoption of generative AI. Also its effectiveness, and the data protection rules. Among companies that have not yet adopted it, 47% say they have not done so due to data privacy concerns, another 43% due to a lack of confidence in the results the system returns, 39% due to a lack of experience and 34% for not having anyone on the staff who can be in charge of implementing it.
Among the companies that already use generative AI in their work and processes, the main concerns are the data ownership (29%), data privacy (28%) and intellectual property (28%).
One way to fix or end some of these problems is human supervision (64%). And 70% believe that a high level of trust among workers already using generative AI can deliver quick results that can be reviewed and modified to complete.
Another 71% believe that risks related to generative AI can be addressed using the technology in environments and frameworks configured by trusted software vendors.
