4/6: How AI is shaping the future of product experiences across industries
Explore how AI is reshaping the industry of healthcare, travel, autonomous vehicle technology, marketing/creative content and eCommerce.
Browse full 6 part series written by Dilip Jagadeesh and Kristina Rakestraw
AI is reshaping the industry of healthcare, travel, autonomous vehicle technology, marketing/creative content and eCommerce. It is the hidden force that makes everyday interactions more intuitive, efficient and delightful.
Gartner, a consulting firm offering business executives actionable insights, refers to AI as not “ just a technology or a business case — it is a key part of a society in which people and machines work together” (Source) and we happen to agree. Some of the benefits of generative AI include “faster product development, enhanced customer experience and improved employee productivity, but the specifics depend on the use case” (Source). Gartner acknowledges some of the concerns we have around the risks AI poses with “a wide array of thread actions” and the fact it is “not designed to be compliant with General Data Protection Regulation” or “other copyright laws” and therefore can lead to experiences that lack transparency and accuracy, introduce bias, raise copyright protection issues, introduce concerns with cybersecurity or pose serious environmental concerns.
As we zoom out, it’s amazing to observe how AI is reshaping the industry of healthcare, travel, autonomous vehicle technology, marketing/creative content and eCommerce. Its influence goes way beyond chatbots and voice assistance — we see it as the hidden force that makes everyday interactions more intuitive, efficient and delightful. Let’s explore some examples in an effort to inspire you to realize what is possible. So that we can then start to imagine what has not yet been realized.
Healthcare
AI is being leveraged in the healthcare industry for early disease detection and more accessible and cost-effective mental health services.
It is playing a role in patient care and research through predictive analytics — an approach that utilizes patient data to predict health risks and outcomes which enables more timely intervention and personalized treatment plans. For example, IBM Watson Health uses AI to analyze medical data and predict health trends, aiding in early disease detection and personalized medicine.
In the field of mental health, we are seeing AI driven chatbots being used for cognitive behavioral therapy with algorithms to predict mental health crises. It is an essential tool in enabling more people to access cost-effective care. For example, Woebot is an AI-powered chatbot that provides mental health support by offering conversation and cognitive behavioral techniques to those in need at a fraction the cost of a therapist. We believe that everyone deserves access to therapy so this is very near and dear to our hearts.
Travel
AI is revolutionizing the way we plan and experience travel by offering personalized travel recommendations and streamlining booking.
For example, AI tools can analyze your travel preferences and past trip details to suggest destinations and activities tailored to you. This helps speed up mundane tasks and can transform the way you explore new places. I mean who doesn’t enjoy a good trip recommendation from someone who knows you well?
In addition to itinerary planning, AI can break down language barriers through real-time translation which can allow for relatively seamless communication in a global context. Much less awkward than looking flustered carrying around a book, dictionary or trying to type things into your phone. This technology is particularly transformative in customer support and international team collaborations.
For example, Google Translate’s real-time conversation feature is a perfect example of AI being used for language translation. It listens to spoken words in one language and instantly translates them to another. It recognizes speech patterns, accents, and dialects, converting them into text and translating them in real-time, making cross-language communication more accessible and effective.
Autonomous Vehicle Technology
AI is reshaping the future of transportation whereby vehicles are using sophisticated AI algorithms to navigate roads, avoid obstacles, and make real-time decisions, improving both safety and convenience.
A prime example is Tesla’s Autopilot system that uses AI to process data from cameras and sensors to navigate roads and traffic. The AI evaluates real-time information like speed, distance from other vehicles, and road conditions to make split-second decisions, ensuring a safe and smooth driving experience.
Marketing and creative content
Generative AI models are revolutionizing creation of content by enabling generation of text, images, videos, and even music. These models learn from vast datasets and can produce original content that aligns with chosen parameters.
Let’s dig in a bit on the range of what it can generate.
🖊️ Copy writers can use GPT-4 to write articles, create marketing copy and even script videos and podcasts. For example, tools like Jasper AI assist in generating blog posts or ad copy, significantly reducing the time and effort required in content writing.
🎨 Graphic and marketing designers leverage tools like Midjourney and DALL-E to create images and artwork from textual descriptions, offering a new realm of graphic design possibilities.
For example, Canva uses AI to suggest design layouts and elements, helping people create professional-looking designs without needing extensive graphic design skills.
🎞️Video editors can lean on AI models to help with editing, adding effects and even generating video content based on textual inputs. For example Runway ML offers AI-powered tools for video editing, enabling creators to automate tedious editing tasks and focus on creative storytelling.
🎸 Musicians can compose music or create soundtracks by learning from existing musical pieces, styles, and genres. For example, AIVA, an AI music composer, creates unique compositions used in games, movies, and as background scores for various content.
🎬 Film or podcast makers can use AI voice generators to create realistic voiceovers for videos, podcasts, or virtual assistants. For example, Descript’s Overdub feature allows content creators to generate natural-sounding voice overs in their own voice to fix the recorded speech.
eCommerce
eCommerce industries are leveraging AI to create hyper-personalized shopping experiences by tailoring the product recommendations and shopping experiences to individual preferences. This approach leverages AI algorithms to analyze a shopper’s past behavior, preferences and interactions to offer highly personalized product suggestions and shopping experiences.
For Example, Myntra’s My Fashion GPT is a leading fashion e-commerce platform that has implemented an AI-driven feature called My Fashion GPT. This tool recommends personalized fashion items based on the shopper’s intent (occasion, trend) and preferences using a model trained to recommend outfits and accessories. This interaction not only mimics a real world interaction with fashion stylists but also helps enhance the shopping experience by speeding up the task of and weeding out the noise. I mean, who wouldn’t want a person shopper to help pick things out and tell you if something makes you look ridiculous?
AI is shaping how we build software experiences
AI is not only having an impact on the experiences that companies offer customers, it is also enhancing the creation of those experiences. Throughout development of software, AI is no longer just a tool for writing code but a way to review it. It looks for any issues before the code is deemed complete, optimizes it to ensure code is written in a clean and efficient manner and suggests best practices and improvements.
This is particularly valuable for new programmers as it helps enhance code quality, fosters learning and saves time from other more experienced developers.
For example, Github Copilot acts like a virtual pair programmer. Powered by OpenAI’s Codex, it suggests whole lines or blocks of code as a developer types, effectively predicting the next part of the code based on the current context. This feature not only speeds up the coding process but also helps in brainstorming solutions to complex problems. As developers use Copilot they are exposed to a variety of coding styles and patterns which can be a significant learning experience towards understanding how different problems can be approached and solved in multiple ways. GitHub Copilot adapts to the coding style of the user, making its suggestions more personalized over time. The tool becomes more effective and intuitive the more it is used.
AI is shaping how customers engage
Faster and more relevant customer support
AI is significantly improving customer support by providing faster and more accurate responses through AI models that are trained on previous interactions, decisions and knowledge bases. They are able to understand complex customer queries and offer relevant solutions or route the person to the most helpful support team. This not only saves time to resolution but it also creates a more satisfying customer experience.
For example, Wealthsimple is a financial company that offers online investing and financial services and uses AI in a robo-advisor service for automated investing. Customers can ask questions about their finances and it offers advice for managing their money based on their financial data. Leveraging the customer’s unique financial goals and risk tolerance, it can manage their entire financial portfolio. No more mixing your emotions with the stock market.
Contextual guidance where and when you need it most
AI’s ability to provide relevant and timely contextual nudges is a game-changer. Based on current and past behavior, it can offer personalized suggestions and proactive recommendations to help bring awareness of tools or information to help you accomplish your tasks and make decisions. For example, AI is being used on many eCommerce sites to suggest additional items based on past purchases, currently viewed items or items in a virtual shopping cart. Bank of America’s online bill experience “notes pattern breaks” such as the “system remembers the pattern of payments you’ve made in the past and posts an alert if you substantially increase your payment to a vendor.” Source: Harvard Business Review
Designing for inclusivity
Over the last decade, there has been a notable shift in building inclusive product experiences by prioritizing investments in experiences that serve a range of abilities. With recent breakthroughs in AI, there is increased opportunity to reach more people with diverse abilities and preferences.
In Kat Holmes book Mismatch, she mentions how “the people who design the touchpoints of society determine who can participate and who’s left out” and that “design shapes our ability to access, participate in, and contribute to the world” (Source). As designers, we have the power to design things in a way that break the cycle of exclusion that impacts society by causing harm to those who are not able to participate and therefore don’t have a sense of belonging. “We shape our tools and therefore our tools shape us” (Source).
So how can AI help us shape a more inclusive environment? Oh, in so many ways such as improving image recognition, predictive text and autocompose and chart interpretations are some of the many ways.
AI in image recognition and description helps people with visual impairments fully understand visual content. For example, Social media platforms like Facebook and Instagram use AI to generate alternative text for images, providing a richer understanding of visual posts. While “inexpensive cameras in mobile phones, fast wireless connections, and social media products like Instagram and Facebook” make it “easy to capture and share photography” as a way to communicate” with the ability to easily add alt text descriptions on all photos, many don’t add alternative text. Automatic alternative text (AAT) was built to “bridge this gap, and the impact it’s had on those who need it is immeasurable.” (Source)
Even though predictive text and autocompose are existing in current products, they are getting more efficient with AI systems that can learn from previous responses from the same person, context and relationship between different people. For example, Gmail just launched six new AI-powered features to help save time such as drafting emails with a simple prompt, smart compose, smart reply, tabbed inbox, summary cards and nudging. Source
In the field of Data science and data visualization, AI is helping reduce the barriers of comprehension complex data — especially with chart interpretation. AI algorithms can analyze and translate these visual data representations into simple, comprehensible text. For example, Microsoft’s Power BI provides plain-language summaries of data visualizations and can take a complex chart and describe its trends, outliers, and key points in plain talk. This not only makes data more accessible to a broader audience but also aids in quicker decision-making for those who may not have extensive experience in data analysis.
This is only the beginning
The future of experience design is being reshaped by AI. We are moving towards interfaces that are not just reactive but also proactive, adapting to our needs and preferences throughout time. The possibilities are limitless, and what we see today is just the beginning.
As we look to the future, emerging AI technologies promise even more profound changes in experience design. We’re entering an era where interfaces will be more than just tools — they will be intelligent collaborators throughout our daily life. As we help shape the future of products that leverage AI, let’s be mindful of our role in it all.
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