Progress in the battle to leverage AI for CX

Artificial intelligence in customer experience

The challenges of building a suitable internal business culture and getting maximum value from investments are still troubling around a third of the customer experience experts surveyed in the latest AI in CX research.

Progress seen in obtaining buy-in and maximizing returns from AI in CX

As with all CX investments, AI has to compete for attention against other business priorities. Usually, as resources are limited, approval is dictated by which project will bring more returns.

Interestingly there seems to be progress in this area. Research respondents in the Artificial Intelligence In Customer Experience: 2020 Report saw the challenges of linking ROI to AI CX initiatives and gaining stakeholder buy-in shrink in significance by almost 10 per cent year-on-year.

It is possible there is a correlation between these elements, as when CX practitioners become more proficient in identifying returns from CX initiatives they are also more equipped to obtain buy-in. It appears practitioners are improving at spotting the CX benefits of AI systems, although, struggles remain in maximizing the returns seen from AI systems.

Some of the respondents are overcoming this challenge by building cross-departmental teams to drive the success of AI investments and mobilize the business at large. Without the alignment and support of the end-to-end business, AI in CX projects are likely to fail completely or will never reach their full potential. This lack of alignment occurs when legacy corporate thinking is not rooted in transformation in the name of customer-centricity. In these organizations, staff members often fail to identify the critical importance of CX as change leaders fight against resistance in the business to evolve and unlock significantly more value for customers.

Cultural alignment can be encouraged by highlighting the reasons behind the AI project and the business benefits up for grabs. Our research respondents are achieving this by using customer success metrics clearly linked to financial goals that boards and senior stakeholders will respect (uplift in sales, greater revenue per customer, cost reduction or lower cost to serve).

Conversely, practitioners should be careful not to overpromise. Realistic expectations should be set with these metrics, to minimize the chances of brands being blinded by the excitement of using AI only to be disappointed later on.

Maintaining life-after-pilot

To help AI systems fulfil their maximum potential in the face of other corporate distractions shouting for staff attention, CX practitioners may have to fight to prevent a “launch and forget” approach from taking hold in the company culture.

Tracking the trajectory of the AI in CX project with success metrics will optimize rollout by illuminating areas for improvement, identifying successes to celebrate, and supporting the project’s momentum to sustain life-after-pilot, when the initial interest and novelty has waned.

To access the full range of expert insights around the variety of digital CX topics covered, access CX Network’s Artificial Intelligence In Customer Experience: 2020 Report here.