Artificial intelligence (AI) has always seemed a bit futuristic. The ability of machines to tap massive amounts of data and use algorithms to “think” and ‘adapt” on the fly has been an alluring, if t somewhat elusive, concept.
However, over the past few years, advances in digital technology have begun to redefine the AI landscape and usher in real-world capabilities. “We are seeing the technology take off in a big way,” says Satya Ramaswamy, vice president and global head of digital enterprise for Tata Consultancy Services (TCS).
The impact of AI is already rippling through several key areas: predictive analytics, speech processing, image processing, chatbots, virtual assistants, augmented reality (AR) and virtual reality (VR), robotics, cyber-security and more. In fact, artificial intelligence and its associated technologies—machine learning, cognitive computing and deep learning business applications—are steadily transforming the business and IT landscape, along with enterprise requirements.
Lee Beardmore, chief technology officer at Capgemini, says that organizations must ultimately “understand how to create models that are relevant to the business domain.”
The march to AI requires new thinking, new skills and a focus on change management. While there are enormous opportunities to operate a business faster, better and smarter, it’s also possible to invest enormous amounts of time and money in initiatives that don’t deliver the desired ROI. What’s more, there are cyber-security and privacy issues to address.
“To some extent, it comes down to the limits of our imaginations as to how we can apply AI engines to our problem domains,” Beardmore says.
After a series of fits and starts, artificial intelligence business applications have steadily moved into the mainstream of business and society. Speech processing systems such as Siri, Cortana, Alexa and Google Now have introduced remarkable capabilities and features. Image processing is transforming everything from advertising to automobiles, from web searches to banking apps on smartphones. And analytics has advanced to the point at which machines can make decisions about everything from credit worthiness to potential fraud or hacking.
Within the AI space, organizations must experiment, but they also must look for opportunities to put AI to work. “There’s a need to be innovative and look for actual problems to solve using the technology,” TCS ‘ Ramaswamy says, adding that the focus should ultimately be on “value.”
Using AI to Gain Greater Insights Into Data
One organization that has harnessed the power of AI is the Memorial Sloan-Kettering Cancer Center in New York City, the world’s oldest and largest private cancer center, which offers state-of-the art facilities and treatments. The center has turned to IBM Watson technology to gain greater insights into data. Doctors and researchers at the facility must keep up with medical literature, a task that could require hundreds of hours per week.
“Watson’s capability to analyze huge volumes of data and reduce it to critical decision points is absolutely essential to improve our ability to deliver effective therapies and disseminate them to the world,” says Craig Thompson, president and CEO of MSKCC.
The upshot? The cognitive computing system—which digests both structured and unstructured data and text from treatment guides, published research and a variety of other sources—delivers evidence-based suggestions to support oncologists’ decisions. It combines patient data with massive volumes of medical literature, including journal articles, physicians’ notes, NCCN (National Comprehensive Center Network) guidelines and best practices. And it continues to evolve as new oncology techniques, treatments and evidence are developed.
In the end, the system presents “wisdom” that essentially serves as a “wise counselor” to help guide decisions for doctors and other experts, notes Larry Norton, medical director and deputy physician-in-chief for breast cancer programs.
The system ultimately delivers a more personalized approach to medicine and treatment methods, including the ability to work more effectively with specific populations or groups. It also considers various other factors, including how other conditions and health issues impact treatment. The computer’s ability to understand language means that the right information is available faster—all while the universe of information expands.