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Wakefield Research: AI Adoption Expands Tenfold

June 27, 2022

Findings of a global research project showed an increase in enterprise artificial intelligence (AI) adoption over the last 12 months is yielding tangible benefits to organizations. However, a shortage of human talent still exists and governance policies continue to lack in maturity – both of which are needed to responsibly manage AI’s growth when considering privacy issues, regulation compliance, hacking and AI terrorism.

Juniper partnered with Wakefield Research to conduct a survey of 700 senior IT leaders around the world with direct involvement in their organization’s AI and/or machine learning (ML) plans or deployments. The survey gauges sentiment around the value of AI, the perceived maturity of deployments and where challenges still exist.

This year’s survey found that enterprises have largely moved past proof-of-concepts and limited trials of AI and are now implementing AI across their organizations, thanks to pandemic-related digital acceleration and the maturation of AI tools available. While Juniper’s 2021 report previously showed only 6% of C-level leaders had adopted AI-powered solutions across their organizations (citing technological, skillset and governance challenges), this year, 63% of company leaders surveyed say they are at least “most of the way” to their planned AI adoption goals.

Still, only 9% of IT leaders consider their AI governance and policies, such as establishing a company-wide AI leader or responsible AI standards and processes, to be “fully mature.” At the same time, more leaders see governance as a priority: 95% agree having proper AI governance in place is important to stay ahead of future legislation, up from 87% in 2021. Despite leadership recognizing the importance of AI governance and having policies in place to manage, govern and maintain, almost half of respondents (48%) think more needs to be done to effectively govern AI.

Sharon Mandell, SVP and CIO, Juniper Networks said, “The disparity the data shows between the substantial increase in AI implementation in the enterprise and the immaturity of AI governance and policies is staggering. It will be critical for governance to pick up pace so that the positives of AI deployment overshadow existing fears of whether AI can be effectively controlled. This is a challenge not unique to AI, but all emerging technologies.”

According to Akshay Sharma, CTO, Kovair Software, and former Gartner Analyst who advised Cisco, and Juniper on SDN: Software Defined Networks and NFV: Network Function Virtualization, “We agree with the Wakefield Research findings that AI/ML coupled with Closed Loop Automation solutions, will lead to Intent-based Networking and Elastic provision of Applications and Storage in the new HCI: Hyper-Converged Infrastructure. These solutions will be delivered using innovative Hyperautomation Platforms supporting the orchestrated use of multiple technologies, tools or platforms like DevSecOps orchestration solutions, iPaaS: integration Platform as a Service, Workflow Process software, Database-as-a-Service (DBaaS) solutions and other types of decision support tools, like AI/ML applied to real-time Data Lakes, and DBaaS solutions, which Kovair uniquely enables. Additionally, this will require Cloud-based Service Mesh solutions, with security, resiliency and process compliance engineered in.”

The research also found:

Despite growing dependence on AI, IT leaders do not see AI replacing humans, but rather allowing employees to save time and focus on more strategic and nuanced tasks. Around half of IT leaders say AI will allow employees to focus on being more innovative (55%), gain new skills (50%) and increase their engagement (47%).

Almost all AI/ML leaders (95%) agree cybersecurity is a critical component to maintaining and securing an enterprise AI solution. Cybersecurity substantially increased in importance as the most critical area for AI adoption: 29% said cybersecurity was the most critical to AI adoption in 2022, versus 14% in 2021.

Almost all IT leaders (96%) say that in the next 12 months, AI will assist in reducing risk and increasing quality within their organization, with Networking/Cloud (25%), IT Infrastructure (21%) and Supply Chain (15%) as the business functions thought to have the greatest potential to derive benefits from implementing AI.

Hiring the right people to operate and develop capabilities is a top area for investment for optimizing AI. IT leaders rank three areas as the top investment options (21% each): hiring the right people to operate and develop AI capabilities; further training the AI models; and expanding the capabilities of the current AI tool into new business units. Last year, 26% of respondents ranked hiring people to develop AI capabilities within an organization as their top investment priority for optimizing AI capabilities in their organizations, compared to the 11% who said their top priority was to train end-users to interact effectively with the tools themselves.

Bob Friday, Chief AI Officer, Juniper Networks said, “AI is ultimately designed to perform tasks on par with humans but at higher scale via automation. Many of Juniper’s own customers are leveraging cloud AI in their networks to dramatically cut support tickets, which frees up IT teams from the drudgery of tactical issues, allowing them to focus on improving end users’ experiences. But with all the positives, enterprises need to responsibly manage AI’s growth with proper governance to stay ahead of regulation and minimize potential negative impacts. In Europe, for instance, we are seeing regulators starting to classify certain AI use cases as risky and requiring CE certification. AI regulation is changing quickly and business leaders must make AI governance a strategic priority.”

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