What could autonomous agents really mean for experience design?

Automation vs. distinction

When considering what agents will really mean for the average person and brand, the primary focus has to be on the customer experience. This encompasses friction points, time saved, and homogeneity, all of which significantly impact both the brand and the customer. Initially, their impact will be subtle, with improvements in efficiency often going unnoticed by the end user. Despite this gradual onset, it’s important to start considering what their use might really mean for everyday interactions and brand dynamics.

At Else we see two key areas where agent adoption could significantly impact both customer and brand experiences.

First, agents have the potential to revolutionise customer experience in several ways. From automating mundane tasks to save time to streamlining and personalising the purchase journey, agents can significantly enhance efficiency. However, there is a risk that over-automation could lead to the removal of positive moments along with the negative ones. Stripped-back experiences risk being much less memorable, or memorable for the wrong reasons. Take Amazon’s Go store concept; it was not the hit everyone expected. This was largely due to over-automating the customer experience. In removing all friction, they also removed feedback points, which undermines the sense of trust and understanding we need to gain psychological satisfaction from an experience.

Second, if businesses rely too heavily on agents to deliver experiences, there’s a risk of homogenisation. This means that diverse shopping experiences could become indistinguishable from one another. Imagine your grocery shopping feeling very similar to buying luxury items from Louis Vuitton if both experiences are handled by agents. This sameness can dilute brand identity and reduce the unique value propositions that distinguish one brand from another. There is a balance to strike between automation and distinctiveness that brands need to manage.

6 barriers to overcome to boost adoption

When new technology emerges, there’s often a slower uptake that eventually builds into an adoption curve. We expect AI to follow this pattern. When designing new experiences, it’s crucial to understand blockers to adoption from a customer perspective, so your design can counter or ease these challenges and promote use. We’ve identified six barriers that together complicate widespread acceptance:

1. Trust and credibility: Customers have trust issues regarding AI’s reliability and transparency, fearing these systems might not fully understand or accurately execute their preferences.
   
2. Control: There are concerns about loss of autonomy with AI integration. Customers want to have the final say and are reluctant to relinquish control, highlighting the need for a balance between automation and user involvement.
3. Lack of human interaction: Many customers prefer human elements in their interactions and might be hesitant to engage with AI-driven systems.
4. Product understanding: A lack of clarity about AI functionalities and benefits means the advantages need to be tangible for customers to see value in them.
5. Privacy and security: Customers fear data breaches and privacy violations, showing uncertainty about how their data will be used and protected.
6. Product performance: AI solutions that fail to deliver expected results can deter further adoption. Initial versions of AI tools may not perform well, leading to high expectations not being met. Ensuring seamless compatibility can enhance the user experience.

Crafting ownable moments

As agents increasingly automate interactions, there is a risk of brands becoming faceless through the removal of customer touchpoints. The challenge for companies lies in identifying and preserving points of positive friction in the customer experience and using these to create “ownable moments” that foster meaningful connections with customers. The balance comes from automating the right parts of the moments, whilst playing up others. 

Within customer experiences, there will always be opportunities to deploy agents to dial up the moments of positive friction to create an ownable moment. The opportunities from a customer perspective largely centre around personalisation through prioritisation, and using agents to deliver these moments where right now they may be delivered by customer service professionals. For example, currently supermarkets holding enough data on individuals can serve tailored product promotions via vouchers. If an agent was used to deliver these, the experience could be played up and although delivered through an AI, could feel more human.

Using AI systems to make customers a priority in a purchase journey or relationship is a way to deliver personalisation at scale, and in a way that feels more personal than getting a voucher. For example, agents could be used to play up celebration moments in a customer relationship like a milestone purchase and create an experience around this moment that leaves the customer feeling seen and valued. Another approach could be through adding new touchpoints into the journey to bring added value, like preparing a new order of regular items or making suggestions. These value-add moments would need to be designed to help customers overcome the barriers they face around trust, automating just enough to show value but leave room for control. 

Changing dynamics—The end of loyalty as we know it?

The interjection of agents into customer experiences has real potential to shift the power dynamic between brands and consumers, particularly where loyalty is concerned. Many businesses operate on the basis that customers won’t switch providers or change habits because it’s ‘too hard’. But the ease with which agents could optimise choices and change providers could bring an end to loyalty as we know it. Adding data portability to the equation swings the power further into customers’ hands – not only could they have a personal assistant programmed to find them the best deal for them, but that assistant could carry personal data as evidence of loyalty credentials. 

For instance, if your personal AI agent knew you hadn’t visited the gym in months, it might suggest cancelling the subscription. Right now this is a manual task, where you interact with a human who’s job is to use emotion to convince you to stay a member by offering discounts and dreams. But if that sales person is met with an AI agent, the tricks stop working. You could tell your AI to ignore all of the storytelling, or could tell it to only agree if discounts are offered. This totally changes the interaction, and what is needed from the business. 

Here’s where ownable moments could be inserted into the experience. Brands who have identified these opportunities have a chance to build meaningful relationships with customers, which should lead to longer term loyalty and are less prone to agent interaction. This itself could lead to a change in business models as brands turn to offering services around their products to provide the opportunities for connection. 

But what now?

At Else we’re already thinking beyond efficient and exploring ways to preserve the human element that makes experiences meaningful. How do we balance automation with ownable moments, or how do we use automation to develop ownable moments? We’re exploring how brands can stand out when they’re talking to agents instead of humans, and looking for an answer to guide the future of customer experience.