Robo-advisors have more than 50 billion in assets under management. And the industry saw more than 200% growth in 2015, according to Aite Group. On Thursday, online automated investment advisor Wealthfront announced a complete redesign to its interface. The biggest change: It will begin incorporating artificial intelligence into its financial services. In addition to looking for hidden fees and cash drag, Wealthfront's AI will track your account activity and automatically apply that behavior to the advice the company gives you.

The stakes are large in the Natural Language Processing (NLP) market: It's the high ground in the battle for control of the data economy and the key to turning silicon into gold, according to a report issued this quarter from market intelligence firm Tractica. Report authors Bruce Daley, the Principal Analyst, and Clint Wheelock, the Managing Director, cite as an example the upcoming Facebook virtual digital assistant Moneypenny. Noting that Facebook already turns an average daily revenue of 11.96 per active user, they surmise that if the same number of active daily users adopt Moneypenny and generate just an additional 1 in additional ad revenue, the program would add 1 billion to the company's annual top line and almost as much to its bottom line. With these and other tantalizing economic prospects at hand, is it any wonder that big names from Amazon to Apple and from Google to Microsoft – not to mention IBM, Nuance, AT&T, and others – are driving further research into NLP and acquiring companies specializing in the space? This month saw another Natural Language Processing acquisition take place, as well-known CRM vendor SugarCRM purchased Contastic's NLP technology.

So I have a dashboard with reports I can interact with to understand why something happens, and that typically reduces the numbers of manual steps before I can make a decision and take some actions. Whether it's IoT, big data or analytics, companies have a lot more data to base their decisions on, and data-driven decision making sounds obvious. More positively, Avanade's new study of smart technologies says business leaders globally expect to be using digital assistants and automated intelligence for problem solving, analysing data, collaborating and making decisions – and they also expect them to increase revenues by more than a third. Certainly, early adopters that Accenture has spoken to who are using machine learning to improve the way they manage customer service, financial resources and risk and compliance, in sales and marketing and in developing new areas of business found "significant, even exponential, business gains" in costs, revenue and customer performance, by using a mix of what Oberoi calls "perceptual intelligence" using natural language and voice biometrics, advanced analytics and business decision support .

Business intelligence has gone from static reports that tell you what happened, to interactive dashboards where you can drill into information to try and understand why it happened. New big data sources, including Internet of Things (IoT) devices, are pushing businesses from those reactive analytics – whether you look back once a month to spot trends or once a day to check for problems – to proactive analytics that give you alerts and real-time dashboards. That makes better use of operational data, which is more useful while it's still current, before conditions change. "There's a demand for real-time dashboards," says Herain Oberoi from Microsoft's Cortana Analytics team. "A lot of businesses want to get the pulse of their business. But dashboards show things that have already happened."

Artificial Intelligence (AI) is making progress in great strides, or at least it appears so! Almost no week passes by without some major announcements of new challenges solved by AI technology or new products powered by AI. Indeed many quantifiable factors attest an unprecedented level of activity: capital investments, number of academic papers, number of products involving AI technology, they all are on a steep rise in the past five years. Computers are already very capable at some specialized tasks that require reasoning and other abilities that we typically associate with intelligence. For example, computers can play a decent game of chess or can help us order our holiday photos. Despite this genuine progress, we are still a long way from human level intelligence because our best artificial intelligence systems are not general purpose. They cannot quickly adapt to novel tasks the way most humans can do.

Google CEO Sundar Pichai thinks we're hurtling towards a future where you'll rely on artificial intelligence more than your smartphone. "In the long run, we're evolving in computing from a'mobile-first' to an'AI-first' world," he said on Alphabet's Q1 earnings call. Google has long used a ton of AI and machine learning in its core products. Investment and research in those areas allows it to serve you the best search results depending on your context (like giving you live sports scores if you search the name of a team during a game), warn you about traffic or the weather, and even write emails for you. And, for now, finding ways to become more like a smart assistant on your smartphone is a big focus.

Many of my patients and friends have turned to online dating sites like Match.com and eHarmony.com A few find something "real," but most tell me they are disappointed that the dates they go on feel like meetings with strangers and leave them feeling empty. One reason for this may be that the Internet encourages people to present only the "best" of themselves. Match.com and eHarmony profiles naturally tend to highlight the glossy, happy and successful side of singles. Tinder is a dating app that connects people who immediately find each other attractive--based on the best "selfies" they can generate.

During Build 2016 this year, Microsoft pitched a world of connected devices and sensors all speaking through cloud-backed machine learning models to developers. Microsoft is betting on a future that involves developers utilizing sensors that link to a vast pool of intelligent data to return immediate real-world benefits. Practicing what the company preaches, Microsoft's Solution Architect and Technical Manager of Microsoft Research, Kenji Takeda talks about how Cortana Intelligence suite is being used to secure safe drinking water for thousands of villages in rural Africa and Asia. A team consisting of Dr. Robert Hope of the REACH initiative, and machine learning experts David Clifton, an associate professor, and graduate student Farah Colchester have come together to try and secure safe and healthy water sources for 5 million poor people in Asia and Africa. The REACH program utilizes a series of mobile sensors connected to cloud computing to monitor water wells to secure a safe supply of water in more rural areas.

In this presentation, I am looking forward to sharing some thoughts on how Marketing will change when it's no longer humans in charge, but computers. Cortana and Siri are just the start, but already they should be influencing changes in strategy. Technology, Data and Actionable Insight will give more competitive advantage opportunities than ever before; it's time to sit up and pay attention.

Predictive analytics allows Netflix to surface and finesse recommendations. This kind of clustering algorithm is continually improving suggestions, allowing users to make the most of their subscription. Under Armour is one of the many companies to have worked with IBM's Watson. The sports apparel company combines user data from its Record app with third-party data and research on fitness, nutrition etc. The result is the ability for the brand to offer up relevant (personalized) training and lifecycle advice based on aggregated wisdom. A 32-year-old woman who is training for a 5km race could use the app to create a personalized training and meal plan based on her size, goals, lifestyle.