Hedge Funds and money managers have come a long way from the days of handwritten financial models. In fact, stock and commodity exchanges report that more than 80 percent of today's trade decisions are computer driven. But a broader change is underway as Wall Street begins to embrace artificial intelligence. By combining AI with big data, researchers are taking advantage of unusual trading opportunities that, until recently, were too complex or expensive to implement. Some of the largest hedge funds are actively pouring resources into AI-driven analysis and competing to hire the best and brightest talent in the field.

Artificial intelligence, once restricted to NASA and sci-fi movies, is gradually becoming a prominent buzzword in the world of marketing technology. However, the widespread adoption of artificial intelligence in marketing is likely several years away as its application is not yet fully developed. But innovations taking place now are setting the stage for artificial intelligence and, more specifically, machine learning, to become a marketing standard in the near future. Many use the two terms of artificial intelligence and machine learning interchangeably; because they are so closely related, it is difficult to establish clear boundaries between them. While artificial intelligence refers to technology that has the cognitive capabilities to solve problems, machine learning allows marketers to learn and understand, among other things, how content is consumed, and helps them predict consumer behaviors based on data patterns and algorithms.

Volkswagen made international headlines this year when the company had to shell out 15 billion after a high-profile emissions scandal rocked the automaker and left its future uncertain. It's a prime example of the type of situation David Copps is trying to prevent with his Dallas-based AI business, Brainspace. "If they had known who said what and when early on in terms of all the emissions problems that they're having, they potentially could've saved 12 billion," Copps says. That's where he sets his sights with Brainspace. The company uses AI and machine learning to enable organizations to garner insights from the data they accumulate each business day, faster than ever before.

Seven out of ten corporate executives say they are making significantly more investments in artificial intelligence (AI) than just two years ago, according to Accenture's recent Technology Vision survey. And more than half say they plan to use machine learning and embedded AI solutions extensively. The race toward a digital future has begun and within the next five years, mastering the impact of this technology on future strategy will be a critical task for every CEO. Computational speed, machine learning and natural user interfaces have all advanced to the point where computers can do jobs that, previously, only humans could do. Intelligent digital labor is set to spark a radical change in labor dynamics, with research from market analyst firm, Gartner, suggesting that by 2030, virtual talent spending will exceed 10 percent of human staff costs.

"By 2020 customers will manage 85 percent of their relationship with an enterprise without interacting with a human." "Why Salespeople Need to Develop Machine Intelligence" Harvard Business Review The answer is yes . . . It depends on an organization's strategy for leveraging AI as a competitive advantage. As human and machine become more integrated in sales and marketing, companies exploring AI for sales are focused on where, when and how AI can replace the human element. This requires CEOs to work with company leadership to evaluate sales and marketing ecosystems that have become a patchwork of investments in sometimes outmoded, "aggregation-based" software platforms for lead generation, pipeline management and forecasting.