Generative AI Tops Leaders’ Investment Plans

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As AI-powered contact centre tools emerge from their early, experimental status and take an increasingly important role across all areas of contact centre operations, contact centre leaders are eager to tap into and maximize its potential.

A recent report by ICMI examines what contact centre practitioners are thinking about when it comes to AI-powered technology and its impact on their work.

The report, The State of AI in the contact centre, provides a snapshot in time about how organizations are using AI, the pain points they hope to address using AI, and the areas they’re targeting in the near term for AI. Brooke Phillips at NICE takes a quick look at what ICMI learned.

CX Tops the Priority List

The top priority across the board was to improve the customer experience, with updating technology and reducing costs coming in close behind:

  1. Improving the customer experience (75%)
  2. Improving agent systems, tools, and resources (53%)
  3. Optimizing workforce operations/productivity (52%)
  4. Reducing total cost of service (52%)
  5. Increasing first contact resolution (45%)

Rounding out the top 10 business priorities are increasing training effectiveness, improving employee engagement, improving or enhancing decision-making capabilities, expanding capacity (presumably without expanding payrolls), and boosting security.

Operations is Driving AI Decision-Making

AI is changing how customer-focused organizations plan to invest in technology. Given all of the hype surrounding ChatGPT, it should come as no surprise that generative AI tops leaders’ investment plans.

The survey found that most of the sought-after functionality enabled by generative AI and other AI-powered tools is going to be purchased as part of an integrated solution.

AI is already integrated into most contact centre solutions and is ready to deliver advanced functionality through those platforms almost immediately, making it imperative for leaders to evaluate existing tools and how they’re using AI.

Beyond IT and the executive team, operations is the group most frequently represented on the AI planning teams at our respondents’ organizations, followed by contact centre/CX, finance, and HR teams.

With contact centre teams, processes, and technology among the most deeply affected by the opportunity and challenges posed by AI-powered tools, contact centre leaders need to push hard to secure a seat at the AI decision-making table.

This representation in the decision-making process will only increase in importance as AI-powered tools continue to proliferate.

As contact centre planners evaluate their use of AI, they should be asking their teams and technology providers some important questions, including:

  • How will AI investments most improve agent experience and their ability to do a great job?
  • Where will these tools enable immediate and ongoing value creation across customer experience and engagement by improving agent experience and their ability to do a great job?
  • Is the contact centre already paying for AI-enabled capabilities that can be leveraged quickly to address goals and challenges?
  • How much new work and money is required to replicate and improve on the outcomes agents produce using existing tools?
  • How will data produced by existing systems be identified, collected, cleaned up, fed into these tools, shared, and used?

Looking Forward

According to the ICMI report, the top challenge in uncovering data insights is the data itself. That’s because AI can’t unlock the value promised for the contact centre without data—and a lot of it.

Respondents listed the number of data sources, the amount of data, and the variety of data types as their top three challenges to uncovering insights they can use to transform their operations.

Modern contact centre solutions are building and refining AI-driven models that use the data their solutions capture and analyze to support specific use cases across the breadth of contact centre applications—from sales effectiveness to CSAT and more.

Many of those models are trained using proprietary repositories of data from vendors’ entire installed base, rather than operating exclusively on individual customers’ real-time interaction data.

AI is being embedded into every tool and process agents use on the job. It’s helping contact centres manage and remediate customer complaints, automatically summarize customer interactions, and prompt agents in real-time on the next best action to take.

It’s enabling them to better serve vulnerable customers, uncover customer sentiment, and much more.

This blog post has been re-published by kind permission of NICE – View the Original Article

For more information about NICE - visit the NICE Website

About NICE

NICE NICE is a leading global enterprise software provider that enables organizations to improve customer experience and business results, ensure compliance and fight financial crime. Their mission is to help customers build and strengthen their reputation by uncovering customer insight, predicting human intent and taking the right action to improve their business.

Find out more about NICE

Call Centre Helper is not responsible for the content of these guest blog posts. The opinions expressed in this article are those of the author, and do not necessarily reflect those of Call Centre Helper.

Author: NICE

Published On: 16th Apr 2024
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