Gap Widens Between Leaders, Those Struggling to Scale AI Amid COVID-19

Shifting spending priorities in the pandemic could put enterprises that are struggling with scaling AI even further behind, a survey finds.

Terri Coles, Contributor

September 23, 2020

3 Min Read
AI robot pressing on dollar sign
Getty Images

The ongoing COVID-19 pandemic is widening the enterprise artificial intelligence development gap as companies decide to redirect their efforts — and investments.

That’s one of the findings of a recent survey of nearly 1,000 companies about enterprise efforts to scale AI applications.

Consulting firm Capgemini surveyed the organizations about the short-term impact of COVID-19 on AI investments. The survey also serves as an update to one done in 2017, the firm said in a release.

Investment in artificial intelligence research and initiatives is changing at some companies in 2020, though those changes are heavily dependent on how a given company’s AI deployment efforts were progressing pre-pandemic.

Enterprises that were further behind on efforts to scale AI applications throughout their operations are more likely to be pulling back on AI spending. However, 40% of companies surveyed have continued — or even sped up — their AI investment during the pandemic, Capgemini found.

Progress but Struggles with Scale

For the report, Capgemini surveyed 950 organizations with at least $1 billion in annual revenue and ongoing AI initiatives.

AI-related firms raised $18.5 billion in investment by 2019, according to the National Venture Capital Association. Globally, AI investment is expected to top $232 billion by 2025 as an increasing number of industries get involved, according to a KPMG report.

That money is beginning to translate into advancing initiatives. More than 50% of the companies surveyed by Capgemini have moved beyond pilots and proof of concept, the research found — compared with about a third three years earlier. Since 2017, there has been a 17% increase in organizations able to deploy AI use cases, Capgemini found.

Additionally, 78% of organizations already deploying AI are continuing with their planned-on progress on their initiatives. Of the companies surveyed, 21% are actually accelerating their initiatives despite the pandemic and the economic situation.

AI Haves vs. Have-Nots

But the Capgemini survey also found signs of a widening gap between the organizations that can afford to keep AI investment steady and those that are struggling. Of those organizations that are having trouble, 43% have pulled investments. Another 16% have suspended AI initiatives entirely in the current uncertain business environment.

And even aside from coronavirus-related challenges, most organizations are still struggling with deploying AI applications at scale. Only 13% of enterprises have rolled out multiple AI applications across multiple teams, Capgemini found, and 72% of companies in the research sample that began AI pilots before 2019 have been unable to deploy even one application thus far.

However, the companies that have found success in their AI efforts are maintaining or even increasing the pace, despite the fiscal and organizational challenges presented by COVID-19 this year.

Of those enterprises that have scaled multiple AI applications across their operations, 78% plan to hold the pace, Capgemini found — and more than a fifth increased the pace of development.

In particular, life sciences seem set to continue with AI investment, with only 38% of companies in that field suspending or pulling investments. This is likely a representation of the importance of this sector amid a pandemic, but also of its success with scaling AI applications so far — 27% of life sciences enterprises surveyed by Capgemini had successfully deployed use cases in production and were continuing to scale AI throughout their organizations.

About the Author(s)

Terri Coles


Terri Coles is a freelance reporter based in St. John's, Newfoundland. She has worked for more than 15 years in digital media and communications, with experience in writing, editing, reporting, interviewing, content writing, copywriting, media relations, and social media. In addition to covering artificial intelligence, machine learning, big data, and other topics for IT Pro Today, she writes about health, politics, policy, and trends for several different publications.

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