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Artificial intelligence has captured the imagination and attention of people globally. But in the business world, the rate of adoption of AI has lagged behind the level of interest through 2019.
Even though we hear that most business leaders believe AI provides a competitive advantage, some industry watchers peg enterprise adoption at less than 20 percent.
But as we enter 2020, we’re spotting an uptick, not only in interest but in AI adoption. And a recent global survey commissioned by IBM reaffirms that uptick.
The survey, From Roadblock to Scale: The Global Sprint Towards AI, polled more than 4,500 technology decision makers. We wanted to gauge the current and future states of AI deployment across the U.S., Europe and China to better understand the landscape and the challenges. As you’ll see, it’s about to change dramatically.
“Advances in data discovery and management, skills training and artificial intelligence knowledge are driving the rate of AI adoption faster than many predicted.”
Results from the Roadblock to Scale survey indicate that while there is still work to be done, advances in data discovery and management, skills training and artificial intelligence knowledge are driving the rate of AI adoption faster than many predicted.
For example, 45 percent of the respondents from large companies (1,000-plus employees) said they adopted AI, while 29 percent of small- and medium-sized businesses (fewer than 1,000 employees) responding said they adopted the technology.
These numbers are significantly higher than some industry watchers estimated to date. Some of the more telling data points of the survey include the following:
Major roadblocks are still holding companies back from the benefits of AI. Among respondents, 37 percent cite limited AI expertise or knowledge as a hindrance to successful AI adoption at their business, with increasing data complexities and siloed data (31 percent) and lack of tools for developing AI models (26 percent) following close behind.
Trust is part of the bedrock of AI’s deployment. Globally, 78 percent of respondents across all countries surveyed say it is very or critically important they can trust that their AI’s output is fair, safe and reliable. Moreover, being able to explain how AI arrived at a decision is universally important (83 percent of global respondents).
Companies now deploying AI technologies are more likely to use a hybrid cloud (38 percent adopted) or hybrid multicloud (17 percent adopted), as data feeds AI success. And, data is everywhere, on all clouds.
Based on our interactions and the results of this study, we expect to see organizations not only adopt AI — but scale it across their enterprises by building and developing their own AI or putting readymade AI applications to work.
For example, according to the survey, 40 percent of respondents now deploying AI said they are developing proof of concepts for specific AI-based or AI-assisted projects, and 40 percent are using pre-built AI applications such as chatbots and virtual agents.
I see the excitement building with clients every day. Consider just a couple of recent examples.
Legal software developer LegalMation leverages IBM Watson and our natural language processing technology to help attorneys automate some of the most mundane litigation tasks, speeding, the written discovery process from multiple hours to a few minutes, for example.
Wunderman Thompson Data, the global digital agency, uses Watson Studio and Watson Machine Learning to access, analyze and run models on terabytes of data stored across its hybrid multicloud environment. As part of its work with Watson Machine Learning, Wunderman is also using IBM AutoAI to automate models to analyze literally tens of thousands of features across the company’s datasets.
“Last year was a productive year for AI, but 2020 is shaping up to bring an exciting new level of commitment and with it, exciting new outcomes for all involved.”
When I look at insights from the report, conducted by the firm Morning Consult, and think about my interactions with clients, the roadblocks to AI adoption have been a prime concern. They’re the reason we’ve worked to lower the barriers of entry and make AI more accessible to businesses.
It’s why we launched the Data Science Elite Team in 2018, a global group of experienced technical professionals who help companies solve real problems with AI.
It’s what drove us to introduce innovations like Watson OpenScale to help mitigate bias in AI models; Watson AutoAI, which uses AI to build AI models; and it’s what led us to create the first-of-its-kind container-based data analytics platform, Cloud Pak for Data, which lets people run Watson on any cloud.
Last year was a productive year for AI, but 2020 is shaping up to bring an exciting new level of commitment and with it, exciting new outcomes for all involved.
Republished with permission, this article first appeared on IBM’s THINK Blog.
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