As artificial intelligence continues to reshape industries, leaders around the world are navigating the challenge of how to create clear and consistent regulations that balance innovation with safety. In September, representatives from technology companies, institutions, and researchers issued an open letter to European policymakers, warning that fragmented and inconsistent rules risk depriving the EU of two cornerstones of AI innovation: “open” and “multimodal” models. Open models are free and available to everyone to use, modify, and build on, which spreads social and economic opportunity. The latest multimodal models operate fluidly across text, images, and speech and will enable the next wave of breakthroughs in AI.
Multimodal AI represents a significant leap forward from traditional AI systems. Conventional AI typically focuses on one modality at a time, for example, a text-based chatbot processes only text, and a voice assistant like Siri primarily processes voice inputs. Multimodal AI systems process and respond across multiple formats simultaneously — integrating text, voice, images, and gestures to deliver more intuitive user experiences that feel more natural and human.
President of TELUS Digital Solutions.
Transforming customer experience through multiple touchpoints
Multimodal AI is revolutionizing customer experience, offering transformative possibilities for how brands and customers interact. At their core, these systems have evolved how customers can engage with brands by offering unmatched flexibility in communication methods. They also boost efficiency by leveraging how humans naturally process information, letting users input data the fastest way they can, through speech, and delivering responses in formats that best suit their preferences or needs.
A customer may, for example, begin their interaction through voice commands while driving, seamlessly switch to text upon entering a quiet environment and receive visual confirmations throughout their journey. This adaptability creates a more natural and comfortable experience while maintaining conversational context across different modes of interaction.
With voice interfaces providing much-needed alternatives for individuals with visual impairments and text and visual outputs serving those with hearing difficulties, multimodal systems are helping to remove barriers and promote inclusivity, broadening access to everyday tasks and interactions with brands.
By synthesizing various forms of input, multimodal AI systems are building a more comprehensive understanding of user intent and context, resulting in more accurate and relevant responses. This deeper level of understanding significantly reduces friction in customer interactions and leads to improved overall satisfaction. Notably, multimodal AI’s ability to process multiple types of input also simultaneously leads to enhanced contextual intelligence.
In the retail sector, for instance, multimodal AI is revolutionizing online and in-store consumer experiences. Leading retailers are using the technology to help customers search for products more easily using a combination of voice queries and images. For example, shoppers can use smartphones to photograph a piece of furniture and then verbally specify modifications such as, “show me this in blue” or “find similar items at a lower price point.”
Smart mirrors with multimodal AI are another innovative retail application. They respond to voice commands and gestures, enable customers to “try on” clothes virtually in their reflections, requesting different sizes or colors, and receive product recommendations. These use cases demonstrate how powerful multimodal AI can be in blending the best of digital and physical retail applications.
Best practices for implementing multimodal AI
For organizations looking to implement multimodal AI solutions, several best practices should be considered:
Seamless Integration: The key to successful multimodal implementation lies in creating smooth transitions between different modes of interaction. Users should be able to switch between voice, text, and visual interfaces without disrupting their experience or losing context.
User-Centric Design: Organizations need to understand the preferences of their specific user base to deliver the best experience. This insight should guide the choice of modalities, ensuring the technology serves real user needs rather than being implemented for its own sake.
Contextual Data Utilization: Effective multimodal systems should leverage available contextual data, including location information, interaction history, and user preferences, to deliver more personalized experiences. However, this must be balanced with strong privacy protections, informed user consent, and transparent data collection and usage policies.
Accessibility First: Rather than treating accessibility as an afterthought, organizations should place it at the core of their multimodal AI strategy. This approach not only serves users with different abilities but often leads to better solutions for all users.
Continuous Improvement: The field of multimodal AI is rapidly evolving, making it essential for organizations to update and refine their systems regularly. This includes incorporating customer feedback, adapting to new technological capabilities, and maintaining robust security measures.
Leverage Third-Party Expertise: Partnering with an expert provider can help organizations navigate the complexities of multimodal AI implementation. These providers bring specialized expertise, ensuring seamless integration, responsible innovation, and adherence to regulatory standards. These collaborations can accelerate deployment while maximizing the technology’s impact on customer experiences.
Looking ahead: the future of CX
As generative AI (GenAI) continues to evolve, multimodal AI is unlocking new opportunities for brands to win customers, build loyalty, and drive higher engagement. Offering seamless and personalized experiences enables brands to attract new customers while strengthening relationships with existing ones, encouraging repeat business and increased spending. This technology enables brands to create more meaningful and impactful customer interactions across the entire customer journey.
For multimodal AI to thrive, technology leaders need to have confidence in consistent rules that balance safety with innovation. Europe has the opportunity to create a regulatory framework that addresses potential risks while unlocking the full potential of this transformative technology.
We’ve compiled a list of the best customer database software.
This article was produced as part of TechRadarPro’s Expert Insights channel where we feature the best and brightest minds in the technology industry today. The views expressed here are those of the author and are not necessarily those of TechRadarPro or Future plc. If you are interested in contributing find out more here: https://www.techradar.com/news/submit-your-story-to-techradar-pro
