Solving the AI Gap: What’s Needed to Boost Sluggish AI Adoption
While many business leaders are curious about AI and see its use as potentially beneficial to their operations, most are not rushing like lemmings into the abyss of AI adoption.
That’s the conclusion of a new 36-page global survey on enterprise AI use and exploration trends from Juniper Networks, which identifies three top challenges to greater AI adoption in business as well as strategies to help companies meet those challenges.
The report, “AI is Set to Accelerate: Is Your Organization Ready?,” says that two-thirds of the 700 business leaders who responded see AI as a top priority in their FY21 strategic plans. But despite that optimism, many business leaders are still being shackled by fear, uncertainty and doubt (FUD) when it comes to diving in to adopt AI, the report continues.
Calling that chasm “The AI Gap,” the Juniper report says that 95% of the 700 respondents believe that their organizations would benefit from embedding AI into their daily operations, products and services, but that only 6% (163) of C-level leaders have actually adopted AI-powered applications or projects across their organizations.
For business leaders, the concerns about diving headfirst into AI revolve around the sizable requirements and costs for big compute power, data storage, data integrity, data security, networking and cloud investments to make it all work, the survey says.
Some 73% of the respondents said they are also struggling with the idea of preparing and expanding their workforce to bring in AI, the report states. C-level respondents say it’s more of a priority to hire people to develop AI capabilities within an organization than it is to train end users to operate the tools themselves.
The third AI adoption challenge identified by the report are AI governance needs and requirements, which are still being identified and established.
Interestingly, though, despite those worries, 71% of the respondents said they believe that AI will have its biggest impacts on operational efficiencies inside their organizations in the future, while 87% said they see AI over the next 12 months reducing risks and increasing quality inside their companies.
Jeff Aaron, the vice president of enterprise marketing at Juniper Networks, said the survey’s insights from the respondents are not what he expected.
“I’m surprised to see so many respondents identify these challenges with AI,” Aaron told EnterpriseAI. “If done right, this technology shouldn’t make it hard on the end user. I don’t want to have to be an iOS or Android developer in order to use my smartphone. Same goes for any AI technology.”
And though fear around AI still exists, it’s clear that excitement and willingness to utilize AI more and more will lead to more deployments and trials in the future, said Aaron.
“But getting there is still feeling challenging to many IT leaders who may not know where to start in ensuring an organization is set up to deploy AI in a way that’s going to generate the desired outcomes,” he said.
IT and network operations are an important place where AI can start to make a huge difference for companies and over-committed IT teams, said Aaron.
“We have reached a fever pitch where the amount of data we and our devices generate, the number of IT trouble tickets taking folks away from higher level tasks, the massive scale of just how many ‘things’ depend on a functioning network, is leading to levels of operational complexity that we as humans simply can’t keep up with,” he said. “We need the help of machines.”
The survey was conducted not just to assess enterprises’ readiness for AI, but to understand the role AI is playing in IT, said Aaron. That includes outcomes being delivered to CIOs, where it ranks in terms of CIO priorities and overall readiness for enterprises to adopt AIOps, virtual network assistants and similar technologies.
“As the report shows, AI for IT is still full of challenges and pitfalls if not managed correctly,” said Aaron. “The report provides a better springboard for us to be true partners with organizations looking to take this stuff on, not have it be just a mere transaction.”
The Juniper survey was conducted in January 2021. The survey questions were sent via email to respondents with a link to a web portal which they used to fill out the survey. The respondents included 700 IT decision makers with direct involvement in their organization’s AI and/or machine learning plans or actual deployments to assesses the attitudes, perceptions and concerns of the technology, according to the company.
Some 399 of the respondents were in North America, while 201 were in Europe and 100 were in the Asia-Pacific region. Twenty-nine percent of the respondents were in technology, media or telecom, while 17.6% were in consumer markets. Some 19% were in industrial and manufacturing, 12% were in financial services, 11% were in health industries and 9% were in energy businesses.