{"id":34000,"date":"2023-11-25T03:00:00","date_gmt":"2023-11-25T11:00:00","guid":{"rendered":"https:\/\/insidebigdata.com\/?p=34000"},"modified":"2023-11-22T10:45:32","modified_gmt":"2023-11-22T18:45:32","slug":"oreilly-releases-2023-generative-ai-in-the-enterprise-report","status":"publish","type":"post","link":"https:\/\/insidebigdata.com\/2023\/11\/25\/oreilly-releases-2023-generative-ai-in-the-enterprise-report\/","title":{"rendered":"O\u2019Reilly Releases 2023 Generative AI in the Enterprise Report"},"content":{"rendered":"\n

New Global Survey Findings Uncover Top Trends in Generative AI Adoption, Barriers to Its Use,\u00a0 and Preferred Models in the Enterprise<\/em><\/p>\n\n\n

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O\u2019Reilly<\/a>, the source for insight-driven learning in\u00a0technology and business, released the findings of a global survey of more than 2,800\u00a0 technology professionals on the realities of generative AI in the enterprise. The Generative AI in \u00a0the Enterprise<\/a> <\/em>report explores how companies use generative AI, the bottlenecks holding back\u00a0 adoption, and the skills gaps that should be addressed to move these technologies forward. The\u00a0 full report is now available for free download.\u00a0\u00a0<\/p>\n\n\n\n

“Generative AI is a gateway to a new era of opportunity for businesses, with the potential to\u00a0 drive growth, optimize operations, and deliver exceptional customer experiences that set them\u00a0 apart from the competition,” said Mary Treseler, chief content officer at O’Reilly. \u201cBut without the\u00a0 proper talent in place to manage it, this rapidly evolving technology can quickly outpace\u00a0 enterprise resources. As this groundbreaking report unveils, we are far from reaching the peak of\u00a0 what generative AI can achieve, and organizations still have time to invest in the critical skills\u00a0 development required to be at the forefront of the AI revolution.\u201d\u00a0\u00a0<\/em><\/p>\n\n\n\n

Fastest technology adoption on record\u2014and it\u2019s just getting started <\/strong><\/p>\n\n\n\n

Generative AI has seen a more rapid adoption than any other technology in recent history. Two thirds (67%) of those surveyed report that their companies are currently using generative AI, and  over a third of this group (38%) report that their companies have been working with AI for less  than a year. While some firms like Gartner have proposed that AI might be at the top of its hype  cycle, the results of the survey suggest there\u2019s a lot more headroom. As generative AI  technology evolves, training models and developing complex applications on top of these  models is becoming easier, and many open-source models\u2014leveraged by 16% of those  surveyed\u2014require fewer resources to run. Also fueling the rush to adoption are the generations  of tooling released within just a single year. Tools that automate complex prompts, tools that  allow for archiving and indexing prompts for reuse, and vector databases for document retrieval  are more common, helping put generative AI within reach for more organizations.  <\/p>\n\n\n\n

Barriers and risks <\/strong><\/p>\n\n\n\n

Despite widespread adoption of generative AI, many companies are still in the early stages.  While 18% of respondents report having applications in production, there remain multiple  bottlenecks for enterprises looking to implement these technologies. The top constraint  respondents cited is identifying appropriate use cases (53%), and the second is a combination of  legal issues, risk, and compliance (38%). <\/p>\n\n\n\n

Accelerated integration of generative AI has also created a demand for technology workers  with the expertise to move efforts along, with AI programming (66%), data analysis (59%), and  operations for AI\/ML (54%) the most-needed skills. General AI literacy (52%) is also critical, as  users have learned when encountering the hallucinations generative AI tools sometimes exhibit.<\/p>\n\n\n\n

In terms of risk, O\u2019Reilly asked those whose companies are working with AI what they\u2019re testing  for. The top five responses were unexpected outcomes (49%), security vulnerabilities (48%),  safety and reliability (46%), fairness, bias, and ethics (46%), and privacy (46%).  <\/p>\n\n\n\n

Generative AI in action <\/strong><\/p>\n\n\n\n

O\u2019Reilly\u2019s report found that 54% of AI users believe generative AI tools will lead to greater overall  productivity, with only 4% pointing to lower head counts. Where generative AI is currently being  used, the survey found that the most common application is programming (77%), using tools like  <\/p>\n\n\n\n

GitHub Copilot or ChatGPT. Data analysis (70%) and customer-facing applications (65%) round  out the top three use cases for generative AI in the enterprise right now, with additional nods to  the technology\u2019s help in generating marketing (47%) and other forms of copy (56%). <\/p>\n\n\n\n

Other key findings include:\u00a0\u00a0<\/p>\n\n\n\n