Artificial intelligence has caused a real hype. Many companies also hope for enormous advantages from large language models (LLMs), but encounter various obstacles when introducing them.
• Artificial intelligence promises many advantages
• Companies are still often hesitant to introduce AI
• Reasons for the reluctance are very diverse
None other than tech visionary and Tesla boss Elon Musk said AI had the potential to become the “most disruptive force in history.” As he explained in a speech to British politicians, he even assumes that this technology will eventually make all jobs obsolete. So it’s no wonder that many companies want to quickly advance the introduction of AI and take advantage of its advantages. These could include: automating repetitive tasks, improving data analysis, reducing human errors and better and faster decision making.
AI introduction is stalling
But there are still numerous obstacles that are slowing down companies in their planned use of AI. A survey of 120 senior decision-makers in the field of AI/machine learning carried out in the USA at the end of 2023 by the research and media company Foundry and the technology consulting company Searce showed that not even 40 percent of companies had successfully implemented an AI project, reports US broadcaster “CNBC”.
According to this survey, concerns about cybersecurity are one of the biggest barriers to AI adoption. A full 58 percent of those surveyed see this as a main obstacle. Not unreasonably, as Jake Williams, who teaches at cybersecurity research firm IANS Research, confirmed: “AI applications, particularly those that use large language models, introduce a whole new set of vulnerabilities that are rarely noticed by most application developers and security auditors be understood,” he is quoted as saying by CNBC. That’s why the expert believes “that we will see specific security training and certifications for AI in the coming years” to create a better understanding of the risks.
Lack of talent
But there are also numerous other barriers that prevent companies from moving as quickly as they would like to adopt generative AI, said Vrinda Khurjekar, senior director of technology consulting firm Searce, which conducted the survey. There is simply a lack of sufficiently trained staff to start and successfully carry out AI projects: Many companies have “difficulties in attracting and retaining top talent,” says Khurjeker. In his opinion, what is needed is early investment in recruiting talent and implementing training programs so that existing employees can improve their AI skills.
AI models still immature
In addition, the language models are not yet fully developed and would sometimes provide results that are not based on real data. “AI models, in particular [generative] AI models are still at an early stage in their life cycle,” explains Khurjekar, pointing out the difficulties that arise: “Hallucinations in the results are real, and in industries where accuracy is very important, such as healthcare and in financial services, this is prompting early adopters to proceed with great caution.”
Regulation still unclear
Khurjekar cites the uncertainty surrounding AI guidelines as a further drag. “As AI adoption is still in its infancy, regulators are still assessing its impact,” he said. Given this uncertainty, many companies in highly regulated industries want to wait and see what regulators decide.”
The need for state AI regulation has been recognized in Washington, but it will probably be some time before there are corresponding laws. The Senate’s “AI Insight Forum” took place on September 13th on this topic. As Reuters reports, there was general agreement among the more than 60 participating senators that government regulation of AI was necessary. Nevertheless, Republican Senator Mike Rounds warned that it would take some time for Congress to act. In addition to the lawmakers, 22 tech leaders, including Elon Musk, also attended the closed meeting on Capitol Hill. During this discussion, the Tesla CEO described AI as “a double-edged sword,” which is why he advocated for a regulator to ensure “that companies take actions that are safe and in the public interest.”
Reluctance in Germany too
Companies in Germany are also reluctant to introduce AI, for reasons very similar to those in the USA. A survey by the Federal Statistical Office in November shows that only about one in eight German companies uses artificial intelligence.
When asked about the reasons for not using AI, lack of knowledge (72 percent) was cited most frequently. However, there are also concerns about incompatibility with existing devices, software and systems (54 percent), difficulties with the availability or quality of data (53 percent), lack of clarity about the legal consequences (51 percent), and concerns about maintaining data protection and privacy (48 percent) as well as costs (41 percent).
Editorial team finanzen.net
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