MIT Technology Review Insights: What’s Next for AI?MIT Technology Review Insights: What’s Next for AI?
Data sharing offers a solution that might be a surprising choice in this era of security and privacy concerns.
September 22, 2021
Sponsored by Genesys
In recent years, artificial intelligence (AI) has migrated from academic labs to the business world with the promise of practical applications. AI initiatives have demonstrated a reliable payoff for many sectors, and continued growth is a sure bet. The “MIT Technology Review: Global AI Agenda” offers insights into where that growth will likely occur for North America based on a global survey of business executives.
Across multiple sectors, the value and practicality have been established for AI, streamlining operational processes and increasing productivity. By the end of 2019, more than 85% of North American survey respondents reported they had launched AI initiatives, with 61% reporting efficiency and cost reductions as the biggest gain.
Tucked within the survey’s data are signs AI initiatives are expanding to include use cases that likely will yield greater revenue growth. Customer service is the most frequently targeted business function in North American firms, with 55% ranking it as the top priority. Current trends in contact center technology support that statistic. The increased use of AI-powered bots and predictive routing improves key performance metrics—leading to significant cost savings.
For many contact centers, an even bigger return on investment is tantalizingly close. The great paradox of AI is that as technology advances, the resulting applications become more human-like. Using AI to classify behavior patterns and predict the next best step in the customer journey enables proactive outreach at the right moment with the right information or offer. The result is a more personalized customer experience delivered at scale to drive sales conversions and increase revenue opportunities. For example, within the first six weeks after implementing an AI-powered predictive engagement tool, Ethiopian Airlines saw a 49% increase in website conversions.
With revenue growth potential in mind, it’s no surprise that sales and marketing poised the rapid expansion of AI initiatives, with an expected increase from 30% to 60%. The sector thrives on relationships, so integrating AI use cases that deliver a personalized experience is a natural fit.
But AI-powered personalization requires data – a lot of data – to understand and predict customer behavior. This dilemma presents a challenge for many organizations. Nearly half of survey respondents identified data quantity, quality, or availability as a top issue. Data sharing offers a solution that might be a surprising choice in this era of security and privacy concerns. Almost a quarter of respondents in North America say they’re very willing to share data with third parties to achieve value with AI. Another 52% described themselves as somewhat willing.
A move toward third-party data sharing would be a big shift in business practices, one that would only be possible with security and privacy protections. But AI has a way of changing the landscape. If it continues to deliver value, that shift seems feasible.
Read the full report here for more information on real-world AI use cases and scalability challenges: MIT Technology Review: Global AI Agenda.
