CX disruptions
Recently I was invited to present on the topic of AI powered CX. It’s a topic close to our hearts here at Time Under Tension, as we’ve been busy building generative AI experiences for our clients. This email breaks down the topics covered, exploring how generative AI is disrupting both CX and the design process.
The changing CX landscape
Earlier this week Perplexity (often lauded as the “Google-killer”) launched Shop with Perplexity, giving a glimpse into how retail customer experiences are being re-shaped by generative AI, and the speed at which things are changing too.
You don’t have to look too far to find examples of new customer experiences being enabled by generative AI. Bunnings recently launched their AI shopping assistant, which helps with DIY tasks and finding products. Shopify introduced Shop.app, a conversational product browsing experience (Xmas shopping anyone?). And Salesforce announced Agentforce, making AI agents that assist customers with sales and service a reality.
The evolving CX design workflow
Customer Experience isn’t the only thing generative AI is changing; the way these experiences are designed and deployed is also being rapidly disrupted.
The Double Diamond design framework, introduced by the British Design Council in 2005, is still widely used (in various forms) today as a design-led approach to go from Challenge to Outcome. The framework provided structure for building solutions by using tools and methods to explore ideas and refine them through the Discover, Define, Develop, and Deliver stages.
But is this tried and tested approach becoming defunct?
Double Diamond design framework (credit: British Design Council)
In a generative AI world, the process, of going from Challenge to Outcome, is being heavily disrupted and accelerated by new age tools and capabilities. Below highlights some of the ways these disruptions are unfolding (note, the tools mentioned below are representative of a plethora of emerging tools available today).
AI tools disrupting the CX design workflow
Deep Dive
Discover with AI
The Discovery process involves a lot of qualitative and quantitative research to understand the issue and how they impact people.
Typically user research is a lengthy and costly part of the Discovery process. Tools like Yabble and Synthetic Users (shown below) use AI to develop surveys and run those surveys on panels of synthetic users, delivering valuable insights within seconds, instead of days.
A Synthetic User interview - from survey creation to synthesised report in seconds
Other research tools like Consensus, Perplexity and Waldo are enabling similar benefits, reducing desktop research tasks from days to minutes.
Define with AI
With a deeper knowledge of the issue and user pains, the challenge is then refined in the Define stage, creating a clear problem to solve.
Large Language Models like ChatGPT and Google Gemini are proving highly valuable in the process, being able to synthesise vast quantities of data and help uncover key insights that are often buried.
Whilst tools like Midjourney and Ideamap.ai (shown below) are making the ideation process more visual and fast becoming part of the designers tool set.
Figma has been developing a roadmap of new AI capabilities in this space too, with Canva launching Magic (AI) Design features and Adobe announcing Project Concept too.
Deliver with AI
When it comes to Delivering, being agile and launching fast and frequently is key to adapting with user needs and feedback.
Established coding tool GitHub has introduced Copilot, which the development community has embraced to speed up and improve the quality of code; with a range of new age tools like Vercel and Cursor (shown below) introducing new ways of coding and deploying at speed with AI.
The future CX design workflow
The integration of generative AI into CX design is not just enhancing traditional methodologies, but fundamentally transforming them. AI tools are accelerating each phase - from discovery to delivery - enabling us to delve deeper into user insights, iterate solutions with unprecedented speed, and deploy experiences that are both personalised and scalable.
This evolution prompts a pivotal and exciting question: as AI continues to reshape the design landscape, what does the future CX design workflow look like?
