As one of the hottest technologies of recent years, artificial intelligence (AI) has started penetrating both the US public and the private sectors--though to differing degrees. While the private sector seems bullish on AI, the public sector's approach appears tempered with more caution--a Deloitte survey of select early adopters of AI shows high concern around the potential risks of AI among public sector organizations (see the sidebar "About the survey"). They give a peek into how public sector organizations are approaching AI; and how the approaches, in many cases, differ from those of their private sector counterparts. AI is not completely new to the public sector. The first AI contract was awarded in 1985 by the US Social Security Administration,1 but the technology still wasn't advanced enough to become common in the following decades.

Most early adopters face AI skill gaps and are looking for expertise to boost their capabilities. According to Deloitte's global study of AI early adopters, 68 percent report a moderate-to-extreme AI skills gap.1 What are the "most wanted" roles to fill these gaps? According to AI early adopters, the top four most-needed positions are "AI builders" who are involved in creating AI solutions: Beyond these AI builders, adopters are seeking "AI translators" who bridge the divide between the business and technical staff--both at the front and back end of building AI solutions: When we compare companies with relatively little AI experience (they've built five or fewer production systems) with those possessing extensive AI experience (they've built 20 or more production systems), we observe an interesting shift in "most wanted" roles (see chart). Early on, AI researchers are the most sought-after, with about a third of the less-experienced rating them a top-two needed role. Business leaders rank near the bottom.

Deloitte Global predicts that in 2019, companies will accelerate their usage of cloud-based1 artificial intelligence2 (AI) software and services. Among companies that adopt AI technology, 70 percent will obtain AI capabilities through cloud-based enterprise software, and 65 percent will create AI applications using cloud-based development services.3 Further, Deloitte Global predicts that by 2020, penetration rates of enterprise software with integrated AI and cloud-based AI platforms will reach an estimated 87 percent and 83 percent, respectively, among companies that use AI software. Cloud will drive more full-scale AI implementations, better return on investment (ROI) from AI, and higher AI spending. Importantly, we'll see the democratization of AI capabilities--and benefits--that had heretofore been the preserve only of early adopters.

Source: Deloitte analysis based on Deloitte's "State of AI Enterprise, 2nd Edition" survey of 1,900 AI early adopters in seven countries. Note: Percentages may not add up to 100 due to a small number of respondents who answered, "Don't know." AI adoption and spending have been on a global tear over the past several years. In 2019, 37 percent of enterprises say they have deployed AI--an increase of 270 percent from four years ago.1 IDC estimates 2019 global spending on AI to be $35.8 billion, an amount that could more than double to $79.2 billion by 2022.2 In an era when everyone seems to be jockeying for an edge and looking for ways to ward off disruption, AI can be a powerful tool.

With leaders increasingly seeing artificial intelligence (AI) as helping to drive the next great economic expansion, a fear of missing out is spreading around the globe. Numerous nations have developed AI strategies to advance their capabilities, through investment, incentives, talent development, and risk management. As AI's importance to the next generation of technology grows, many leaders are worried that they will be left behind and not share in the gains. There is a growing realization of AI's importance, including its ability to provide competitive advantage and change work for the better. A majority of global early adopters say that AI technologies are especially important to their business success today--a belief that is increasing. A majority also say they are using AI technologies to move ahead of their competition, and that AI empowers their workforce. AI success depends on getting the execution right. Organizations often must excel at a wide range of practices to ensure AI success, including developing a strategy, pursuing the right use cases, building a data foundation, and cultivating a strong ability to experiment. These capabilities are critical now because, as AI becomes even easier to consume, the window for competitive differentiation will likely shrink. Early adopters from different countries display varying levels of AI maturity. Enthusiasm and experience vary among early adopters from different countries. Some are pursuing AI vigorously, while others are taking a more cautious approach.

Attempting an epic hike or road trip across unfamiliar territory without an expert guide, detailed map or plenty of supplies will certainly run the risk of failure. So why would you approach an investment in AI without the right strategy and a prescriptive approach? The urge to make the move to AI is strong and justifiable. According to research cited in MIT Sloan's global study of AI early adopters, almost 85 percent believe AI will allow their companies to obtain or sustain a competitive advantage.In many cases, market leadership is at stake. At the core is the ability to unlock the value exponentially growing amount of data.

This is according to Deloitte's technology, media and telecommunications (TMT) predictions 2019 report. "While AI's initial benefits accrued mainly to early adopters with strong IT infrastructures and deep pockets, those early adopters have now rolled out cloud-based AI services that are bringing AI to the masses," according to the report's author Jeff Loucks, executive director of Deloitte's Centre for TMT. Deloitte Global predicts that in 2019, companies will accelerate their usage of cloud-based AI software and services. Among companies that adopt AI technology, 70% will obtain AI capabilities through cloud-based enterprise software, and 65% will create AI applications using cloud-based development services. It also predicts that by 2020, penetration rates of enterprise software with integrated AI and cloud-based AI platforms will reach an estimated 87% and 83%, respectively, among companies that use AI software.

Deloitte Global predicts that in 2019, companies will accelerate their usage of cloud-based1 artificial intelligence2 (AI) software and services. Among companies that adopt AI technology, 70 percent will obtain AI capabilities through cloud-based enterprise software, and 65 percent will create AI applications using cloud-based development services.3 Further, Deloitte Global predicts that by 2020, penetration rates of enterprise software with integrated AI and cloud-based AI platforms will reach an estimated 87 percent and 83 percent, respectively, among companies that use AI software. Cloud will drive more full-scale AI implementations, better return on investment (ROI) from AI, and higher AI spending. Importantly, we'll see the democratization of AI capabilities--and benefits--that had heretofore been the preserve only of early adopters.

The uptake of artificial intelligence in business has been sluggish. However nearly half of the CIOs surveyed by Gartner said they have plans to implement the technology and those that already had shared some key AI lessons. "Despite huge levels of interest in AI technologies, current implementations remain at quite low levels," said Whit Andrews, research vice president and distinguished analyst at Gartner. "However, there is potential for strong growth as CIOs begin piloting AI programs through a combination of buy, build and outsource efforts." Gartner outlined four lessons that have emerged from AI pioneers in their report, Lessons From Early AI Projects.