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Artificial intelligence has become one of the biggest technological developments in business in recent years, but the field is still largely shrouded in uncertainty. While expectations run sky-high, what are businesses actually doing now? A aims to demystify AI in business and take stock of current industry adoption. Download lagu tahun ini terbiasa. The report is based on a global survey of more than 3,000 executives and in-depth interviews with more than 30 technology experts and executives. Its goal is to present a realistic baseline that allows companies to compare their AI efforts and ambitions and to provide guidance for things to come.

The gap between ambition and execution is large at most companies. Only about one in five companies has incorporated AI into some offerings or processes. Only one in 20 has extensively incorporated AI into offerings or processes.

The research also reveals large gaps between leaders—companies that understand and have adopted AI—and laggards in every industry. One sizable difference is their understanding of, and approach to, AI data and training. For many, the differences will likely magnify over the next five years, but nearly all companies still have the ability to establish competitive advantage and shape value creation from AI in their sectors. The high expectations for AI cross geographies, industries, and companies, regardless of size. While most executives have not yet seen substantial effects from AI on their offerings and processes, they clearly expect to in the next five years. (See Exhibit 1.) Most organizations foresee sizable effects on IT, operations and manufacturing, supply chain management, and customer-facing activities.

Business-process-outsourcing companies, for example, expect many of the jobs that moved to low-labor-cost countries in recent years to be automated. However, they also expect AI to lead to new activities and sources of employment. Executives at industrial companies expect the largest effect in operations and manufacturing. In connection with its new A350 program, for example, Airbus is using AI to speed and improve production. The company has combined data from past production programs, continuing input from the A350 program, fuzzy matching, and a self-learning algorithm to identify patterns in production problems. In some areas, the system matches about 70% of seemingly unrelated production disruptions to solutions used previously—in near-real time. Expectations aside, the gap between ambition and execution is large at most companies.

Three-quarters of executives believe that AI will enable their companies to move into new businesses. And almost 85% believe AI will allow their companies to obtain or sustain a competitive advantage. But while more than 60% of respondents said that a strategy for AI is urgent for their organizations, only half of those said that their organizations have a strategy in place. The largest companies (those with more than 100,000 employees) are the most likely to have an AI strategy, but only half have one. There are also large gaps between leaders and laggards. Among leaders, three-quarters have identified business cases for AI. About 80% say that senior leaders are onboard.