Looking forward – 2025 and beyond

As we have seen, there has been a 6x increase in brands incorporating RCS into their omnichannel messaging strategies to leverage its suitability for two-way conversational interactions. We see this trend gaining momentum and predict combinations of RCS paired with SMS, Voice, Email, and messaging apps like WhatsApp that already have a mature set of business features to become the norm.

Businesses in regions with limited carrier support for RCS will be lobbying for accelerated adoption and this will have a knock-on effect on volumes across the globe during 2025. 

2025 will also see an increase in the use of AI with RCS. Unlike SMS, chatbots delivered over RCS can include interactive features like structured conversation flows, images and carousels, GIFs, suggested replies and actions, and the option to transfer to a human when required.

Integrations with platforms like Google’s Vertex AI can provide these chatbots with the power to tap into real-time analytics and data mining operations that will enable verified users to access detailed information just by sending an RCS message.

Businesses that are lower on the scale of CX maturity now have a blueprint for the changes that they need to make to rapidly evolve.

Clean, structured data remains crucial to effective customer interactions. To achieve the levels of personalization that they aspire to and to truly benefit from AI, these brands must prioritize the strategic use of first-party data, with a focus on precision and ensuring security and privacy standards.

The final piece of the CX puzzle is the infrastructure and technology necessary to support cohesive and secure conversational experiences for customers across channels and use cases. Integrating a CDP and CRM to collect and unify data, and then syncing it with a journey builder to manage all the customer touchpoints, both human and AI, is the proven recipe for achieving CX maturity.

And what is next for brands that are already CX mature?

Having mastered the fundamentals of conversational CX, the next step is to make customer journeys even richer and more interactive. Conversations that can effortlessly incorporate text, voice, video and multi-media are key to connecting with new generations used to signaling their feelings by sharing a gif or a meme.

Many businesses have invested in AI projects but a lot of them have not yet seen a return on their outlay. This is due to a combination of factors – firstly they have taken a scatter-gun approach and have been inserting AI into a variety of workflows and customer touchpoints without enough thought and analysis going into where it would add real value.

Even brands that have run successful pilots have stalled when it comes to scaling them to enterprise levels. The complexity of incorporating AI infrastructure into existing systems, the levels of cross departmental collaboration required, and the challenges of securing the data used in enterprise level machine learning has caused these projects to become bogged down. 

The successful AI projects that we have seen have all followed a similar pathway. A single use case is identified that balances simplicity with tangible benefits to the business. Once the concept has been proven it is put into production and assimilated into the organization. The successful template can then be applied to other more complex use cases. 

 As the honeymoon phase of AI experimentation ends business leaders will increasingly want to see tangible ROI and a solid business case for future AI investments. In 2025 we will see businesses concentrate on outcomes and practical applications for AI across their entire organizations.

Luckily the industry is now in a position to satisfy these evolving requirements with the general availability of agentic AI that can act autonomously to achieve goals without requiring human guidance. By understanding the goal of the user and their context, the AI can adapt to solve complex, multi-step problems.

The use cases where agentic AI can deliver solid ROI are almost limitless. Imagine AI-powered agents that can not only answer complex queries, but also manage transactions, and interact conversationally to recommend solutions and products based on vast amounts of proprietary and first party data.