It’s about saving time.
Time is the precious resource of today’s world. It allows us to do human things, like talk to each other, play with our children, throw dinner parties, walk in a park, or even just watch a lake evaporate.
However, our time is consumed with information overload. The human brain was never supposed to manage a large amount of information. With exabytes (that’s one quintillion!) of information flying around in our heads, which we are increasingly reliant on for our global survival, it’s no wonder we created more intelligent computers to start keep all this stuff straight.
Welcome to the age of artificial intelligence; the sign that we gave up trying to keep track of the information overload. Why not let computers figure it all out? The truth for builders of technology in this day and age is you have to integrate artificial intelligence into your technology, or risk being obsolete within a few years.
The top 5 most interesting trends of AI integration in modern software tools are the following:
1. Predictive Analytics
2. Smart Search
3. Relevant Content
4. Growing Ecosystem
5. Machine Learning
Just ask yourself if the business tools you are using are addressing these customer expectations. Because if not, you might be in trouble.
Predictive Analytics
Questions You Need to Ask: Are we gathering analytics and using that to create predictions of the future?
By forecasting what is likely to happen, teams can put focus on the right tasks that support a likely outcome. Take your typical B2B sales team for instance. When integrated with sales activities, such as pipeline management and forecasting, the predictive analytics and machine learning behind these models benefit the sales team by helping steer the sales activities in the right places and free up the time of the sales team for more direct sales activities.
Real World Example: Microsoft’s Azure Machine Learning and Cortana Intelligence Suite. Enable analysts at Microsoft to make financial forecasts faster. https://www.microsoft.com/itshowcase/Article/Content/770/Predictive-analytics-improves-the-accuracy-of-forecasted-sales-revenue
Search Smart
Questions You Need to Ask: Do we use search as the primary way for users to find content or information? When we do use search, do we provide type ahead results and predictive text based on relevance?
Browsing takes too long. A user should be able to start typing in a word to find something and a type-ahead result should immediately appear. These type-ahead results are based on relevance (popular search terms, history, favorites, and recent terms).
Real World Example: Waze Search. It takes the most minimal input and instantly starts populating the most relevant locations near me based on a relevance algorithm.
It takes only four taps for Waze to predict “Peabody Museum” as the location the user was searching for when in Boston metro north area.
Relevant Content
Questions You Need to Ask: Is my technology able to provide relevant suggestions, meaningful actions based on the users’ preferences?
With the digitalization of media data from books, movies, podcasts, blogs, news, and content services piling up to the moon and back, there is just too much content to keep up with.
We don’t have the time to research thousands of possibilities every time we need to find content. By creating algorithms that take past history, preferences, and goals and then match them with content, documents, music and products, the user can get instant connection with relevant information or libraries of content.
Real World Example: Audible Recommendations.
Amazon’s Audible cuts through the clutter of millions of books and presents the most relevant results “Recommend” just for the user based on history, preferences, predictive analytics, popular selections and just in.
Growing Ecosystem
Questions You Need to Ask: What other technology is my tool connected to? What is our ecosystem? Is our ecosystem growing?
What makes next gen AI so powerful, is its ability to talk to other systems that know or have access to more stuff about you. In this day and age, we use various systems and services to provide us our unique “lifestyle stack” of technologies. The ability for a tool to “play nice” with other systems and tools is imperative. Integration is a must for survival in today’s technology ecosphere. In this world, users expect their digital services to be connected with the rest of the world and not to exist in silos.
Real World Example: Amazon Alexa. Along with the voice recognition intelligence, Alexa has an exploding ecosystem… to the tune of 1,900 3rd party services and counting (http://www.technewsworld.com/story/83775.html)
Machine Learning
Questions You Need to Ask: Are we tracking unique patterns and using that data to adjust in real time?
A human’s unique patterns, preferences and actions are something that machines have not traditionally been expected to learn. So, if a system could recognize these unique patterns on-the-fly, it could be almost human.
Real World Example: Google’s Deepmind. Just last year, a computer programmed for very nuanced learning beat the world champion in the ancient game of Go. (https://deepmind.com/blog/deepmind-round-up-2016/)
What the 5 AI Trends Mean for Your Technology
As consumers learn to expect these extremely efficient and useful features in all of their tools, it will become a critical point of differentiation for any technology. You might even say it’s a do-or-die imperative for every technology company to put in on their roadmap.
A new generation of business tools embedded with AI is on the horizon galloping forward at a blistering rate.
Jeff Williams is UX Design Lead at Xinnovation