This is a republication of an excerpt of the report “AI adoption is accelerating — now what?”, published by “Juniper”, with the title above.
health transformation matters
research institute, knowledge portal & advisory consulting
Joaquim Cardoso MSc
Chief Researcher, Editor & Advisor
December 29, 2022
Enterprises are further along adopting artificial intelligence to simplify operations through advanced, human-like function.
But without proper policy, governance and structure in place, do they risk creating a monster?
Juniper Networks, for the second year in a row, surveyed 700 people across different titles and industries to gauge sentiment and adoption levels of artificial intelligence (AI) in their organizations.
Last year, we found a wide gap between excitement surrounding AI’s promise and actual adoption.
Despite 95% of respondents believing it would benefit them, only 6% of C-level executives reported any level of AI adoption within their companies at the time.
This year, Juniper found that 63% of companies surveyed in our 2022 report say they are at least most of the way to their planned AI adoption goals.
Additionally, 145% more company leaders (27% in 2022 vs. 11% in 2021) say they’re looking in the future to deploy “fully enabled” AI use cases with widespread adoption, a shift away from only looking ahead at “limited” AI use cases.
Yet only 9% surveyed currently consider the governance and policy around their organization’s deployments “fully mature”.
Without governance comes the potential for irresponsibly developed AI, which could result in security breaches, unethical or biased AI, falling behind potential future legislation, or even simply ending up with an AI system that’s not fulfilling its intent, just to name a few possible risks
Part 1: AI use is growing and not slowing down [excerpt]
AI is on the rise throughout various industries and enterprises, with its use in networking reportedly more than doubling since last year’s survey.
Additionally, companies are reporting that AI is having a positive effect on decision-making for employees, as well as creating a better operational experience.
- 1.Most organizations say they are approaching, meeting and even going beyond their AI adoption goals
- 2.Dependence on AI is pervasive across organizations
- 3.Organizations are leveraging AI in a variety of ways
- 4.AI in networking infrastructure and capabilities has more than doubled in the past year
- 5.Nearly all respondents have seen improvements in the end user or network operations/IT teams’ experiences
- 6.Employee satisfaction is on the rise with AI solutions implemented for operational tasks
- 7. 2022 saw increased enthusiasm for full AI adoption, whereas 2021 revolved around limited use case
1.Most organizations say they are approaching, meeting and even going beyond their AI adoption goals
- 63% of organizations are at least “most of the way” to achieving planned goals for AI adoption
- 37% have not deployed AI
- or are mostly just in planning / early stages
2.Dependence on AI is pervasive across organizations
- Most AI/ML leaders (94%) indicate that organizations are at least moderately reliant on AI to perform tasks and assist in decision making,
- with few (6%) indicating they are “only a little reliant.”
- 94% of those using AI describe their organization’s level of reliance on AI as very to moderately reliant
3.Organizations are leveraging AI in a variety of ways
- Networking/Cloud is the business area receiving the most AI automation (55%);
- however, Operations (45%), Information Technology (44%), and Sales and Marketing (39%) are not far behind
4.AI in networking infrastructure and capabilities has more than doubled in the past year
- More than doubling the previous amount who indicated they have done so, AI/ML leaders at a vast majority of organizations (93%) say they have incorporated AI into their networking infrastructure and capabilities
5.Nearly all respondents have seen improvements in the end user or network operations/IT teams’ experiences
- The number of AI/ML leaders overall who indicate they have seen improvements in total has increased (100% vs. 97% YoY),
- with nearly half (45%) seeing improvements in user experience for end users and network operations/ IT teams
6.Employee satisfaction is on the rise with AI solutions implemented for operational tasks
- The positive impact of AI solutions being implemented to assist with operational tasks can be seen with nearly all (97%) AI/ML leaders agreeing that employee satisfaction has increased since doing so
7. 2022 saw increased enthusiasm for full AI adoption, whereas 2021 revolved around limited use case
- Even more AI/ML leaders are indicating their organizations have operational processes fully enabled by AI with widespread adoption (27% vs. 11% YoY),
- with more proofs of concept being tested and planned to scale as well
- The Juniper Networks survey was fielded to 700 executives with a minimum seniority of Senior Manager, who are moderately or significantly involved in AI/Machine Learning, using an online survey between March 29 th and April 10 th , 2022.
- For tracking purposes, results were compared to a Juniper Networks survey of 700 executives with a minimum seniority of Senior Manager, who are moderately or significantly involved in AI/Machine Learning, conducted in January 2021.
- The margin of error for the survey is +/- 3.7 percentage points at the 95% confidence level.
For methodology details, refer to the full version of the report.