Wakefield Research: AI Adoption Expands Tenfold
June 27, 2022
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.
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.”
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.”