GenAI Is Critical to Contact Center Success

Though the technology is less than two years old, generative artificial intelligence has already transformed many CRM processes and is poised to “redefine the contact center and customer service landscape,” Forrester Research says in a new report.

“Contact center leaders are poised to leverage genAI not just for efficiency, but as a strategic tool to enhance customer experiences and operational agility. With careful navigation and the right partnerships, contact center leaders can harness genAI to both adapt to the rapid pace of change and drive significant business growth.”

Contact center leaders first started experimenting with generative AI early last year, according to Christina McAllister, a Forrester senior analyst and one of the authors of the report. Many have advanced beyond the initial phases to take advantage of different opportunities, including better, more rigorous summaries and scoring of interactions and agent-facing capabilities like email creation and task completion.

But to fully achieve a successful AI-augmented future, contact centers will need to navigate through a number of larger trends.

The first is the shifting technology landscape, particularly as hyperscalers (tech giants like Amazon Web Services, Google, and Microsoft that provide cloud-based services) more aggressively go after the contact center market, with architectures becoming increasingly adaptable and open. In response, contact center leaders need to reconsider how they acquire and integrate new technology, as well as the cost of that technology, McAllister says. “More and more vendors are throwing their hats into the ring; we’re seeing a lot more overlap of capabilities.”

Contact center leaders also need to consider what they want a technology to deliver, whether the focus is growth, retention, or something else, McAllister says. “Moving to the cloud is not a business outcome on its own.”

Additionally, contact center leaders need to review knowledge management investments and practices. Today, many of those investments have not panned out.

The agent workspace also needs to evolve, according to McAllister. Forrester’s research shows that agents still spend a significant amount of their time during calls looking for information. Though now unified workspaces integrate data across channels, their insights and recommendations are still generic and do not cater to the needs of agents. In the future, McAllister expects the workspace to dynamically provide customer-specific recommendations, actionable insights, and automated workflows, eliminating the need to switch between systems.

Contact center leaders also need to look beyond today’s generative AI capabilities to the additional capabilities that will be available in the future, McAlllister says. To do this, they will need holistic data insights, cross-channel interactions, and diversified AI investments.

“There is some reluctance that we are seeing from buyers, because they don’t want to lock in their legacy technology stack if they’re not 100 percent sure where the vendor is headed and whether they are the most innovative going forward.”

McAllister advises clients to start with the technology that is critical to the contact center as the nucleus of the technology stack, then look at additional capabilities that can be integrated enterprise-wide.

A holistic AI strategy will be imperative, she says, noting that contact centers must embrace diverse AI techniques.

Rather than focusing solely on automating current interactions, contact center leaders also need to anticipate and shape future ones, using predictive analytics, demand forecasting, and next-best-experience recommendation engines.

AI will also be increasingly important in fraud detection, intelligent routing, and optimizing business outcomes.

Rather than simply using generative AI to automate customer interactions, leading contact centers should also use the technology to expand their capacity for more meaningful and deliberate interactions, according to McAllister. Doing so will enable contact centers to transition from cost centers to pivotal contributors of profit and value.

And in this new AI environment, data management-as-a-service could become a new market for data center vendors. McAllister says that earlier investments in data lakes and customer data platforms have failed to completely break data silos and improve data quality, often because data center executives lack the necessary expertise in enterprise-scale data management.