AI Still Needs Human Insight to Shape the Retail Experience

In 2024, the most forward-thinking and innovative retail organizations will recognize that it's a must to blend intelligent human insight and artificial intelligence (AI). It will become clear that unless an organization can find a way to unify the two across virtually every aspect of their business, it will suffer the consequences across both the employee experience (EX) and customer experience (CX).

When it comes to AI, here are some trends retail leaders should consider:

The Rise of Closed AI Applications

For business use, different types of AI will be more relevant for different applications across business operations. Within the contact center, one trend is becoming very clear — the emergence of closed AI applications.

Closed AI applications are designed for immediate use and don’t require extensive training or integration to provide value to your business. These include specialized tasks like customer conversation transcription, summarization, and sentiment analysis.

Unlike open or so-called bespoke AI systems which require agency and integration into specific business systems, closed AI can be readily implemented out of the box and can increase the accessibility and adoption of AI. In a world where extensive training is required to provide restricted business value, or operationalization is required to allow AI to have limited agency for specific tasks, this marks a distinct shift to where AI becomes less of a project and more of a task you can turn on for a specific function. This bifurcation of AI capabilities will be important for retail leaders and contact centers to understand.

Keeping the Human in the Middle

The "human in the middle" concept typically refers to a scenario where a human is inserted into a process or system that otherwise relies on automation or machine-to-machine communication. This concept can also refer to scenarios where AI augments and assists human engagements, such as when AI assists a contact center agent with an issue that requires additional information and sets a follow-up task. Think automated engagement management where a human oversees the process and can take over and make overriding decisions if necessary.

Financial Pressures on Chatbot Vendors

Once differentiated by the quality of their AI, pure-play chatbot vendors now find themselves in a very crowded space, fighting with multiple 800-pound gorillas with vast large language model (LLM) capabilities. AI models and machine learning are also becoming increasingly commoditized. We’re finding that many of these pure-play vendors are now transitioning into mere interfaces for other LLMs from Amazon.com, Google, Microsoft, OpenAI, or Hugging Face. As AI models continue to be commoditized, traditional chatbot vendors face substantial financial pressures in a market where differentiation becomes decreasingly reliant on the AI technology itself.

The bottom line? The future sits on the shoulders of those who embrace AI and its immense potential to revolutionize the retail industry, but also never lose sight of the irreplaceable value of human insight.

Rob McDougall is the CEO of Upstream Works Software, a company which provides enterprise-ready and agent-first omnichannel contact center desktop solutions that improve agent and customer experiences.