Five 2024 AI Trends for the Contact Centre and Beyond

As we venture into 2024, artificial intelligence (AI) for the contact centre, customer experience (CX) and other business applications continues to evolve rapidly.

When used effectively, AI has the power to redefine the way businesses interact with their customers and manage internal processes.

From balancing the scales between speed and responsibility in AI deployment to integrating AI into everyday workflows, these trends highlight the growing sophistication of AI applications and their increasing impact on business operations.

Let’s explore how these developments not only enhance operational efficiency and CX, but also drive significant business value, positioning AI as an indispensable tool for the modern enterprise.

1. Teams Will Balance Responsibility and Speed With AI

In 2023, generative AI emerged as a major force, profoundly impacting technology and business practices. Initially, companies rushed to integrate generative AI, but they’re now shifting towards more thoughtful, strategic approaches. This evolution is only going to progress in 2024.

CallMiner’s 2023 CX Landscape Report revealed that 45% of CX and contact centre leaders are concerned about AI’s security risks.

43% fear it could spread misinformation, and 41% worry about AI producing biased or inappropriate responses in customer interactions. Only 6% have no concerns.

Despite these fears, the momentum of AI adoption is unlikely to wane in 2024, especially in CX applications.

Yet business leaders are realizing that generative AI isn’t a catch-all solution. Instead, it works best in specific scenarios, often alongside other AI methods, to fulfil properly defined business objectives.

The companies that excel will be those that find a balance between the rapid deployment of AI and maintaining responsibility and security.

This approach will enable them to provide the greatest value to their customers and enhance their financial performance — without unnecessary risk.

2. Organizations Will Seek Out Mature AI Applications

The AI applications that will have the most utility for users will be the ones that fit into their day-to-day workflows.

In other words, people will not go out of their way to adopt AI if they don’t find an immediate benefit from using it.

This reality will enhance the value of purpose-built AI applications for specific business segments and industries, including customer service, that prioritize day-to-day agent workflows.

In fact, enterprise execs surveyed by Menlo Ventures in late 2023 cited “unproven return on investment” as the most significant barrier to generative AI adoption.

The firm says, “Startups that deliver context-aware, data-rich workflows will be the ones that finally unlock buyers and—ultimately — the larger enterprise market.”

This doesn’t just apply to generative AI — other types of AI will need workflows that are inherently useful on a day-to-day basis.

Organizations may not know where to start with open-ended AI applications; instead technology providers will have to work harder to increase AI’s utility across the entire business.

3. Starting With the Basics Will Produce the Most Success With AI

Shiny object syndrome with early-stage AI applications can prove distracting for enterprises looking for ROI from AI.

In 2024, organizations will take a “back to basics” approach, looking at some of the areas in their business where automation and AI can help them produce the most effective gains.

For example, in the contact centre, quality assurance (QA) is an often-overlooked area of investment for AI.

Typical QA analysts can often only listen to 3 to 5 random calls per agent, per month — less than 1% of overall interactions. Instead of repetitive tasks like call listening, AI systems can analyse 100% of customer interactions across all channels — dramatically increasing the scale of the QA function and driving more accurate results.

Further, the automation of time-consuming, mundane tasks will free up human employees to spend time doing more meaningful work.

While these applications may not be the most ‘shiny’, they will generate the most value for enterprises in the shortest period of time.

4. Cross-Functional Use of AI-Generated Data Will Improve

According to the CX Landscape Report cited above, 68% say the CX data they collect is often not harnessed to their organization’s best advantage, and 50% lack effective communication between departments.

While many teams have not realized the power of applying customer insights across lines of business, 2024 will unlock new opportunities.

The hype of generative AI is a good thing for general awareness of other AI systems that may have been at work within an organization for years.

CX teams can take advantage of this heightened awareness to provide reporting and analytics to other teams across the business.

For example, premier health system and renowned academic centre, University of Pittsburgh Medical Center (UPMC), shares CX data gathered in the patient access centre with the marketing team to drive more effective campaigns for specific cohorts of patients.

We’ll see more cross-functional applications of this type of data as the popularity of AI grows even further.

5. AI Outcomes Will Become Easier to Measure

Unproven ROI will become a thing of the past if organizations can think more critically about applying AI to measurable outcomes.

It sounds simple, but very few organizations maximize their AI systems’ ROI by following simple steps like:

Deciding on a Project Charter

Starting small with a task, like partially automating QA, can produce instant productivity gains and lead to measurable outcomes such as improving compliance.

Aligning AI Goals With Business KPIs

For example, if your contact centre team wanted to reduce average handle times (AHTs), an AI system like conversation intelligence could analyse the root cause of outliers in this KPI (for example, what are the trends causing long calls). From there, teams can act on specific improvements.

Evaluate Early Wins to Decide on Expansion Opportunities

Early wins like those described in the examples above can be a powerful indicator for business leaders on the ROI of AI systems.

After a successful charter and initial projects, leaders are more likely to invest in AI to help achieve other departmental goals and business KPIs.

These five trends paint a picture of an increasingly mature and strategic approach to AI in the contact centre and broader business contexts.

In the year ahead, companies will continue to move beyond the initial allure of generative AI to embrace practical, impactful applications that yield measurable results.

By focusing on mature AI applications, adopting a basics-first approach, using AI-generated data across business functions, and establishing clear metrics to measure AI outcomes, businesses are poised to unlock unprecedented value from their AI investments in 2024 and beyond.

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

For more information about CallMiner - visit the CallMiner Website

About CallMiner

CallMiner is the leading cloud-based customer interaction analytics solution for extracting business intelligence and improving agent performance across all contact channels.

Find out more about CallMiner

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: CallMiner