Enthusiasm Runs High for AI, but Many Are Still on Learning Curve

Majority of business leaders see potential, but implementation takes time

No longer a futurist's daydream, artificial intelligence (AI) is attracting significant investment and growing quickly. According to a December 2018 estimate from tech research firm Tractica, the direct and indirect application of AI software generated $5.4 billion in worldwide revenues in 2017, and is forecast to produce a whopping $105.8 billion by 2025.

Business leaders are enthusiastic about AI's potential to make their organizations more efficient. Ninety percent of global senior executives surveyed by the Economist Intelligence Unit (EIU) in 2018 said they expected AI to positively impact growth, and 86% of respondents said that it would impact productivity.

While the enthusiasm is there, the implementation of AI technologies does require some time to get started. A PwC report from December 2018 found that only 27% of companies surveyed had already implemented AI in multiple areas, while 20% planned to deploy it across their enterprises in 2019. Another 16% of respondents said they had pilot projects using AI within discrete areas.

Data from UBM suggests that tech professionals are in the early phases of getting AI off the ground—and were still in a bit of a learning curve. The April 2018 survey of 182 tech professionals in North America involved in tech purchases for their employers found that 30% had plans to learn from the success and failure of early adopters in the next 12 months, 26% had plans to get advice from third-party experts and 23% of respondents planned to train existing staff in the upcoming year.

An Investment Worth Making

AI promises to free up employees to focus on higher-value work without being stuck doing the same, repetitive tasks. Christian Monberg, CTO of Zeta Global, cites how data analysts can use AI to make informed business decisions. For example, instead of running SQL queries all day, data analysts can look at the graphs to determine brand engagement over time, or even conduct frequency analyses to understand how to optimize journeys for individuals across channels.

To convince stakeholders that AI is worth their time, Raj Balasundaram, vice president of solutions and strategic services at Emarsys, takes a step-by-step approach. "We map out [the stakeholders'] entire journey and say, ‘Your bottlenecks are here and here.' We can reduce the time they're spending [on certain activities] by replacing them with algorithms and machine learning," he said.

Marketing Departments Gear Up

So far, marketing and advertising have been among the top early applications of AI. A 2018 survey of business executives worldwide by Accenture, SAS and Intel found that marketing functions were some of the most popular areas for deploying AI. More than 70% of respondents said they had deployed AI for external communications work, and 66% said it was currently being used in the marketing/sales department. In his job as chief product officer at MadisonLogic, Sonjoy Ganguly sees marketers using AI in four main areas: segmentation, messaging, media activation and analytics. A July 2018 study by Adobe and Econsultancy had similar conclusions.

As AI continues to evolve, marketers are raising their expectations for what it can do. On the agenda are better understanding of what customers need and connecting the online and in-store experience.