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While it is true that the adoption of artificial intelligence Delivering tangible results across applications for all kinds of enterprises, there is a downside: AI’s full potential is not realized due to a lack of human expertise to optimize it for business purposes.
A new global research project conducted by Juniper Networks and Wakefield Research and released on June 15 shows an increase in AI adoption over the past 12 months, but a shortage of human talent is holding back much of a good implementation. Board Policy involving AI continues to lack maturity, the report said, and this is also a stumbling block. Both factors are necessary to responsibly manage the growth of AI when considering privacy issues, regulatory compliance, hacking and AI terrorism, the study said.
“IT people may know how to develop and build the data and the solutions so that they are secure and scalable, but we don’t necessarily have the subject matter expertise to do the actual analytics, which are usually in the business functions,” Juniper CIO Sharon Mandell, who helped guide the investigation, told VentureBeat. “I think you’re seeing this trend more and more where we want to make sure it’s there. We want to help them with analytics tools that we can be pretty sure will do the job for them. And we want to set them up so that the data is high-quality and well-designed so that they don’t spend all their time preparing data, which isn’t necessarily their skills.
“We want them to focus on analytics. As a result, if the AI is embedded in the tool, put it on the edge of your organization. If it’s not centrally managed, and as with many things, you need to maintain visibility, understand how it’s used, and how it’s secured. That way you really get the value you had in mind.”
The research indicates that the difference between the substantial increase in AI deployment in the enterprise and the immaturity of AI governance and policy is huge, Mandell said.
“It will be critical for governance to step up the pace so that the positives of AI deployment overshadow existing fears about whether AI can be effectively controlled. This is a challenge that is not unique to AI, but to all emerging technologies,” said Mandell.
A few key points from the study:
- While Juniper’s 2021 report previously only showed 6% of C-level leaders had adopted AI-powered solutions in their organizations, this year 63% of business leaders surveyed said they have achieved at least “the majority” of their planned AI adoption goals.
- IT leaders don’t see AI in the place of people. About half of IT leaders (55%) say AI will empower employees to focus on being more innovative, acquire new skills (50%) and increase engagement (47%).
- Nearly all AI/ML leaders (95%) agree that cybersecurity is a critical part of maintaining and securing an enterprise AI solution.
- Cybersecurity has become significantly more critical as the most critical area for AI adoption: 29% said cybersecurity was most critical for AI adoption in 2022, up from 14% in 2021.
- Nearly all IT leaders (96%) say AI will help reduce risk and increase quality across their organization in the next 12 months, with networks/cloud (25%), IT infrastructure (21%) and supply chain (15% ) because business functions believed they had the greatest potential to benefit from the implementation of AI.
Hire the right people to exploit and develop capabilities is a top area for investment for optimizing AI, Mandell said. IT leaders rank three areas as the best AI investment options (21% each): hiring the right people to operate and develop AI capabilities; refresher training de AI models† and expanding the capabilities of the current AI tool to new business units, the report said.
AI is eventually taking automation to perform tasks akin to humans and many of Juniper’s own customers are leveraging cloud AI in their networks to reduce support tickets, freeing IT teams from the rut of tactical hassles to really focus on improving the end-user experiences,” Juniper Chief AI Officer Bob Friday said in a media advisory. “But with all the positives, more than ever, enterprises need to responsibly manage AI growth with good governance to stay ahead of regulations and minimize potential negative impacts.
“In Europe, for example, we see that regulators are starting to classify certain AI use cases as risky and require CE certification,” he said. “AI regulation is changing rapidly and business leaders need to make AI governance a strategic priority.”
The survey surveyed 700 senior leaders around the world who were directly involved in their organization’s AI and/or machine learning (ML) plans or implementations.
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