According to a Gartner report issued on Tuesday, 45% of firms are presently testing generative AI, while 10% have such technologies in use. During a webinar last month to examine the commercial costs and dangers of generative AI, 1,419 executives were polled.
In the recent survey, around 78% said that the advantages of generative AI exceeded its risks, compared to the 68% who felt the same way in the prior survey.
According to Gartner, 22% of firms are expanding their generative AI investments across at least three different functions, with 45% of businesses doing so overall. Software development saw the biggest investment in or adoption of generative AI, at 21%, followed by marketing and customer service, at 19% and 16%, respectively.
Gartner’s group chief of research and an acclaimed analyst, "Organizations are not just talking about generative AI – they're investing time, money, and resources to move it forward and drive business outcomes."
"Executives are taking a bolder stance on generative AI as they see the profound ways that it can drive innovation, optimization, and disruption[…]Business and IT leaders understand that the 'wait and see' approach is riskier than investing," said Karamouzis.
Why is ‘Having a Doubt’ Necessary
In order to grow their businesses companies must have a framework in place to ensure that they are adopting generative AI responsibly and ethically.
According to Kathy Baxter, Salesforce.com's principal architect of Responsible AI, skepticism should also be extended to technologies that can tell whether AI has been deployed.
Baxter further added that technology has now become ‘democratized,’ allowing anyone to have access to generative AI without many restrictions. However, despite the fact that many firms are making an attempt to screen out harmful information and are still investing in such initiatives, there is still a lack of knowledge regarding "how big a grain of salt" one should apply to AI-generated content.
Baxter noted that even AI detecting tools can make mistakes occasionally yet may be taken as always accurate in an interview with ZDNET, stressing that users accept all of this stuff as fact even if it is false. When generative AI and the tools that go along with it are employed in some fields, like education, these impressions could be detrimental since students might be falsely accused of employing AI in their work.
She further raised concerns over such risks, urging individuals and organizations to use generative AI with ‘enough skepticism.’
She further highlighted the need for sufficient restrictions to ensure the safety and accuracy of AI. This will also help in case deployments are rolled out along with mitigation tools, she added. These can involve fault detection and reporting features, and mechanisms to collect and provide human feedback.
Moreover, she emphasized the significance of the data used to train AI models and added that grounding AI is equally essential. But as she pointed out, not many businesses practice proper data hygiene.