We're in the midst of a rapid uptake of AI in the enterprise across the board, but there are big differences in the results and the workflows in these AI practices. For its latest "State of AI in the Enterprise" report, Deloitte looked for the commonalities that mark successful AI practices, as well as the practices associated with lower achievement. For its fourth annual AI report, titled "Becoming an AI-fueled organization," Deloitte surveyed 2,875 executives from 11 countries in the Americas, EMEA, and APAC to determine how they're using AI, what kinds of results they're getting, and their underlying practices. Deloitte grouped the companies into four main groups, based on the volume of AI projects and their success rate. Transformers, which accounted for 28% of survey respondents, were characterized by high outcomes and a high number of AI deployments, while Pathseekers, which accounted for 26% of respondents, reporting high outcomes, but a low number of deployments.

Deloitte has launched the Deloitte Center for AI Computing, designed to accelerate the development of artificial intelligence offerings for its clients. The center is built on NVIDIA's DGX A100 systems to create a supercomputing architecture that will help Deloitte's clients in their efforts to become AI-fueled organizations. The accelerated computing platforms feature NVIDIA graphics processing unit technology, along with its networking and software for advanced data processing, analytics and AI by bringing massive parallel processing capability and speed to deep learning, machine learning and data science workloads, the company said. Deloitte's State of AI in the Enterprise survey found that more than half of respondents reported spending more than $20 million over the past year on AI technology and talent. Nearly all adopters said they were using AI to improve efficiency, while mature adopters are also harnessing the technologies to boost differentiation.

To stay competitive and relevant in their industries, enterprises increasingly need to become AI-driven. AI is a new key to improving business processes, making better decisions, monetizing data, increasing security and more. The growing importance of AI in the enterprise is a point that industry observers now emphasize. Just consider this view from the global consulting firm Deloitte: "As AI technologies standardize across industries, becoming an AI-fueled organization will likely be table stakes for survival. And that means rethinking the way humans and machines interact within working environments."1

For some organizations, harnessing artificial intelligence's full potential begins tentatively with explorations of select enterprise opportunities and a few potential use cases. While testing the waters this way may deliver valuable insights, it likely won't be enough to make your company a market maker (rather than a fast follower). To become a true AI-fueled organization, a company may need to fundamentally rethink the way humans and machines interact within working environments. Executives should also consider deploying machine learning and other cognitive tools systematically across every core business process and enterprise operation to support data-driven decision-making. Likewise, AI could drive new offerings and business models. These are not minor steps, but as AI technologies standardize rapidly across industries, becoming an AI-fueled organization will likely be more than a strategy for success--it could be table stakes for survival. In his new book The AI Advantage, Deloitte Analytics senior adviser Thomas H. Davenport describes three stages in the journey that companies can take toward achieving full utilization of artificial intelligence.1 In the first stage, which Davenport calls assisted intelligence, companies harness large-scale data programs, the power of the cloud, and science-based approaches to make data-driven business decisions. Today, companies at the vanguard of the AI revolution are already working toward the next stage--augmented intelligence--in which machine learning (ML) capabilities layered on top of existing information management systems work to augment human analytical competencies. According to Davenport, in the coming years, more companies will progress toward autonomous intelligence, the third AI utilization stage, in which processes are digitized and automated to a degree whereby machines, bots, and systems can directly act upon intelligence derived from them. The journey from the assisted to augmented intelligence stages, and then on to fully autonomous intelligence, is part of a growing trend in which companies transform themselves into "AI-fueled organizations."

Artificial intelligence (AI) has reached a crescendo in business conversation. The technology is on the tip of the tongue for so many--from early stage start-ups to established global enterprises--because the technology is a powerful addition to any company. According to one report, 61 percent of companies implemented AI in their business in 2017. For most of these businesses, the technology works in the background to make sense of the massive stores of data the companies collect: The AI assists (by managing the data) and augments (by augmenting human analytical competencies). To become an AI-fueled organization--one that has a clear edge over competition--the AI should also become autonomous (by taking action without human intervention).

For some organizations, harnessing artificial intelligence's (AI's) full potential begins tentatively with explorations of select enterprise opportunities and a few potential use cases. While testing the waters this way may deliver valuable insights, it likely won't be enough to make your company a market maker. To become a true AI-fueled organization, a company may need to fundamentally rethink the way humans and machines interact within working environments. Executives must consider how to deploy machine learning and other cognitive tools systematically across every core business process and enterprise operation to support data-driven decision-making. In the end, the whole company must be open to AI driving new offerings and business models.

For some organizations, harnessing artificial intelligence's full potential begins tentatively with explorations of select enterprise opportunities and a few potential use cases. While testing the waters this way may deliver valuable insights, it likely won't be enough to make your company a market maker (rather than a fast follower). To become a true AI-fueled organization, a company may need to fundamentally rethink the way humans and machines interact within working environments. Executives should also consider deploying machine learning and other cognitive tools systematically across every core business process and enterprise operation to support data-driven decision-making. Likewise, AI could drive new offerings and business models. These are not minor steps, but as AI technologies standardize rapidly across industries, becoming an AI-fueled organization will likely be more than a strategy for success--it could be table stakes for survival. In his new book The AI Advantage, Deloitte Analytics senior adviser Thomas H. Davenport describes three stages in the journey that companies can take toward achieving full utilization of artificial intelligence.1 In the first stage, which Davenport calls assisted intelligence, companies harness large-scale data programs, the power of the cloud, and science-based approaches to make data-driven business decisions. Today, companies at the vanguard of the AI revolution are already working toward the next stage--augmented intelligence--in which machine learning (ML) capabilities layered on top of existing information management systems work to augment human analytical competencies. According to Davenport, in the coming years, more companies will progress toward autonomous intelligence, the third AI utilization stage, in which processes are digitized and automated to a degree whereby machines, bots, and systems can directly act upon intelligence derived from them. The journey from the assisted to augmented intelligence stages, and then on to fully autonomous intelligence, is part of a growing trend in which companies transform themselves into "AI-fueled organizations."