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AI in the workplace: Why adoption remains low

The stats speak for themselves.

Allie Nawrat

Technologist

AI workplace
Credit: Dina Mukhutdinova via Twenty20.

Unleash Your Technology AI has huge potential to transform work for the better.

  • Although companies largely view AI positively, the actual adoption of this technology remains slow.
  • How can companies correct this discrepancy to the benefit of themselves and their employees?

Artificial Intelligence (AI) can be used in the workplace to automate boring, repetitive tasks that have become part of workers’ daily grind.

A survey of 700 individuals by Juniper Networks found that 95% thought their organization would benefit from embedding AI into their daily operations, products, and services. Also, 88% said they wanted to use AI as much as possible in their organization.

All of the survey respondents were involved in an organization’s implementation of AI and machine learning (ML) and were based in North America, Europe, and Asia Pacific.

However, there is a disconnect between the theory and the reality. With only 6% of the 163 C suite leaders surveyed reporting adoption of AI-powered solutions within their organization.

Also, only 22% of all 700 respondents said they used AI to automate or aid decision-making by their employees.

However, of those that had implemented AI in their organizations, 74% said it made their employees happier, 82% said AI brought productivity, and 71% noted the link between AI and the business’s operational efficiency.

So, given the positives that AI brings for companies and their staff, why is AI not being fully embraced in the workplace?

[Read more: 92% of Fortune 500 companies aren’t leveraging AI in recruitment, research says]

Explaining the workplace AI gap

The respondents told Juniper Networks that the reason for the disconnect was that many organizations were still figuring out the benefits of AI and ML, and that there were several challenges related to the practicalities of adopting these next-generation technologies.

The barriers these individuals reported included data and integration issues with their existing technology stacks – this is something that will require additional investment to be seamless.

40% of respondents noted that managing the convergence of AI with other technologies was a major challenge, while 58% noted that developing AI models and data sets that could be used across the company was a major issue.

Another issue is that the workforce is not yet fully on board on the advantages that AI tech brings to their daily lives.

While 73% of respondents said their organizations were struggling to prepare their workforce for AI integration, 41% also noted the challenge of training employees to work with AI systems, and 31% stated they were struggling to recruit workers already AI and ML trained.

The third, and final barrier, noted by Juniper was challenges in AI governance.

While 87% of C suite executives agreed that organizations needed to implement AI governance to mitigate risks, only 20% saw governance of AI as a key priority for their company. Just 6% said they had an AI lead overseeing the strategy and governance of AI adoption.

How to correct this AI gap

While companies reported they were mainly focused on bringing in AI-trained talent, Juniper advises that it is important that employers also make sure that the rest of their workforce understand AI and how it is being used in the organization.

To do this, companies need to invest in digital upskilling of their employees sooner rather than later.

Juniper Networks warns “the cost of inaction will be much worse”.

Juniper Networks also calls on companies to immediately work on policies and procedures for AI governance in order to mitigate risk. They recommend that companies “delegate responsibility and ensure it is cross-functional and covers the entire AI ecosystem and toolset”, “clarify the use of AI within your organization” and “have consistent standards and ethics across the enterprise”.

Sharon Mandell, Juniper Networks’ senior vice-president and chief information officer, concluded: “For AI, there is no doubt that there is light at the end of the challenge-filled tunnel and significant potential to generate even more meaningful and incredible outcomes than we’ve seen so far.

“By focusing on upskilling their workforce, investing in strong infrastructure—including data, cloud and networking capabilities—and implementing enterprise-wide AI governance, organizations are preparing for the digital workforce of tomorrow.”

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