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The State of AI in 2020: 35 Stats to Know

Artificial intelligence (AI) is arguably the greatest driver of the digital customer experience (DCX). Enterprise use of the technology grew 270% over the last four years, according to Gartner. By 2022, the firm expects AI will create nearly $4 trillion in business value.
But how are organizations actually using AI to create new value and address problems? Who is responsible for overseeing AI budget and initiatives? Where are companies getting stuck? New research from Nemertes and Vanson Bourne gives a detailed look into the state of AI as we approach 2020:

AI Adoption and Budget

  • The top adoption plans for types of AI-enabled CX include personalization (used or planning to be used by 51% of companies), self-service (50%), predictive analytics (50%), and natural language processing (48%)
  • 31% of companies are not planning to use AI because they see no business value
  • 22% of companies interested in implementing AI have not done so because they have not completed an analysis of their technology yet
  • 82% of successful companies plan to increase their AI budget in 2020
  • Successful companies spend an average of $1,800 on chatbots per month
  • Successful companies spend 48% more on contact center licenses and subscriptions, and 30% more on DCX budgets
  • Almost all (99%) of organizations are using some form of AI within their contact center(s)
  • Organizations believe the top goals of using AI in the contact center are customer self-service (47%), resolving customer issues faster (44%), automating responses to customers complaints (41%), and predicting customer needs (41%) and/or behavior (38%)
  • 94% of companies believe that effective AI can transform contact center performance
  • 87% cited “improving/adopting AI within the contact center” as their top priority for 2019, indicating continued importance in 2020
  • 37% are using chatbots to interact with customers
  • 45% have invested in AI to enhance CRM initiatives
  • 59% of successful companies have a Chief Customer Officer who is responsible for overseeing the contact center, including AI decision-making

AI Challenges

  • Top ways companies are hurt by AI include not understanding written communications (22%), an inaccurate or poor data set (22%), not understanding verbal communications (20%), providing inaccurate data to agents (19%), and inaccurate transcriptions (7%)
  • Over one-third of contact center organizations find it challenging to provide an effective yet tailored approach to each contact (37%) and/or directing customers to the right channel (34%)
  • Most organizations using AI in the contact center are roughly 40-60% of the way through their rollout
  • 70% of organizations surveyed by Vanson Bourne feel they are currently not getting the most out of AI in their contact center(s)
  • For 58% of these respondents, the opinion is that chatbots are the only form of AI they are using effectively
  • A lack of specialized expertise (51%), experience (51%) and/or confidence with AI (41%) are cited as key barriers holding back organizations from attempting to integrate AI with their CRM solution
  • Lack of funding is a barrier for 42%, meaning that organizations are more likely to need more expertise or experience with AI than more money
  • Only 25% of respondents have fully implemented an AI strategy, with organizations far more likely (58%) to have one partially implemented
  • 40% of organizations feel they are held back from AI adoption due to protection/regulatory fears, and 37% due to a lack of understanding about the technology and/or lack of skills in-house to facilitate adoption

AI Applications and Goals

  • Top applications of AI in the contact center include smart routing (43%), resolving issues when company is closed (42%), resolving issues faster than an agent (39%), screen pops that help agents improve service (34%), and predictive service (30%)
  • The primary business goals for AI in DCX include reduced costs (60%), improved CX (58%) and increased revenue (49%). Increased revenue is the top goal for successful companies (73%) compared to all others
  • The greatest problems companies are trying to solve or opportunities they are looking to address with AI include improving CX (54%), using more self-service capabilities (40%), using agents more effectively (38%), reducing long customer hold times (29%), helping scale company growth (28%) and serving internal employees (27%)
  • Successful companies are using or planning to use intelligent routing more than the average organization, as well as self-service and sentiment analysis
  • 52% of companies currently use or plan to use intelligent routing by 2025, compared to 95% of successful companies
  • Successful companies are more likely to use skilled agents because their CX initiatives are getting more complex, and AI-enabled solutions like bots and intelligent self-service can handle the basics (39% of successful companies vs. 17% of all others)
  • The top uses of AI functions organization-wide include agent assistance (24%), inventory tracking (23%), product recommendations (22%), script compliance (22%), simple chatbot questions (20%), and intelligent call routing (19%)
  • The most popular types of analytics in use today are agent analytics (21%), sentiment analytics (20%), and predictive analytics (19%)
  • Predicting customer behavior (53%) and/or CRM (51%) are among the most beneficial use cases of AI for just over half of companies surveyed by Vanson Bourne
  • The top departments using AI are IT, customer service, security, and marketing
  • Measuring the Success of AI
  • 53% of high-performing companies measure the success of AI in their DCX initiatives, specifically by measuring revenue (58%), measuring cost (49%), and measuring CX (42%)
  • 47% of companies say AI is working well for both basic and advanced functions; 34% say it’s working well only for basic functions
  • The most common ways organizations surveyed by Vanson Bourne measure the success of AI is via customer satisfaction scores (62%), efficiency/productivity gains (60%), and financial results (50%)
  • How does your organization plan on using AI in 2020? If you want more, check out all of our resources on AI to learn more about everything from the most beneficial uses cases to quantifying the value of AI.
The author of this article, David Chavez, is a Vice President in the Office of the CTO at Avaya, responsible for Architecture and Consulting. Having 25 years of experience and holding 76 US patents, David is responsible for Avaya’s award-winning and market-leading IP communications architecture and the creator of the Avaya Aura(R) architecture. He has a B.S. in Computer Science and Mathematics from New Mexico State University and an M.S. in Mathematics from Colorado State University, with some executive education from Stanford Graduate School of Business.