The future of HR is both digital and human as HR leaders focus on optimizing the combination of human and automated work. This is driving a new priority for HR: one which requires leaders and teams to develop a fluency in artificial intelligence while they re-imagine HR to be more personal, human and intuitive. As we enter 2019, it's the combination of AI and human intelligence that will transform work and workers as we know it. For many companies the first pilots of artificial intelligence are in talent acquisition, as this is the area where companies see significant, measurable, and immediate results in reducing time to hire, increasing productivity for recruiters, and delivering an enhanced candidate experience that is seamless, simple, and intuitive. One company that has delivered on this is DBS Bank.

What goes into making plants taste good? For scientists in MIT's Media Lab, it takes a combination of botany, machine-learning algorithms, and some good old-fashioned chemistry. Using all of the above, researchers in the Media Lab's Open Agriculture Initiative report that they have created basil plants that are likely more delicious than any you have ever tasted. No genetic modification is involved: The researchers used computer algorithms to determine the optimal growing conditions to maximize the concentration of flavorful molecules known as volatile compounds. But that is just the beginning for the new field of "cyber agriculture," says Caleb Harper, a principal research scientist in MIT's Media Lab and director of the OpenAg group.

The future of HR is both digital and human as HR leaders focus on optimizing the combination of human and automated work. This is driving a new priority for HR: one which requires leaders and teams to develop a fluency in artificial intelligence while they re-imagine HR to be more personal, human and intuitive. As we enter 2019, it's the combination of AI and human intelligence that will transform work and workers as we know it. For many companies the first pilots of artificial intelligence are in talent acquisition, as this is the area where companies see significant, measurable, and immediate results in reducing time to hire, increasing productivity for recruiters, and delivering an enhanced candidate experience that is seamless, simple, and intuitive. One company that has delivered on this is DBS Bank.

Together, these led to an effi- ciency- and automation-driven model that made banking more transactional and technology-centric. Banks focused on faster and more convenient transactional services for their end consumers via ATMs, e-cards and telephonic services. Social, mobile, analytics and cloud technologies (the SMAC stack) fueled a second wave of change that is just now taking shape. The role of technology has rapidly changed from a monolithic enabler of efficiency to an engine for personalized and ubiquitous provisioning of banking services for digi- tally connected customers. We now see the emergence of another disruption, known as Digital 2.0, which will leave an altered banking landscape in its wake.

In a world that operates on billions of digits every day, humans are too slow and inattentive. To adapt, we must automate the processing of millions of complex transactions on a daily basis, at speeds fast enough to satisfy impatient digital users. This adaptation requires a massive level of digital transformation that can support operations, business processes and decision-making speeds faster than is humanly possible. Historically, digital technologies get faster, cheaper, more powerful and smaller every couple of years. We operate in human time, a biological cadence influenced by the physical environment, our well-documented physical, mental and emotional limitations, and the universe that we live in.

Artificial intelligence and machine learning systems are made up of code and algorithms, and as such, they work as fast as computers can process them. Often this means massive amounts of learning can be accomplished every second without stop 24x7x365. Code doesn't need to take weekends off, holidays, or sick time. It can recognize complex patterns, potentials, areas of improvement, and problems in real-time or digital-time. Given these available computing capabilities and speeds, what are executives to do with AI and machine learning, when we live and operate in relatively slow human-time, and work within organizations that work at an even slower pace of organizational-time.

But as artificial intelligence (AI) advances and machines take over everything from driving our cars, diagnosing disease and managing our finances, profound questions emerge about the future of work and how organizations compete. Business leaders today have two options: be swallowed up by the ongoing machine revolution or ride the wave to enhanced profitability and better business. Cognizant is sharing its take on AI's far-reaching commercial and societal impact with WEF attendees in a by-invitation session moderated by Malcolm Frank, Cognizant's EVP of Strategy and Marketing and co-author of the forthcoming book What To Do When Machines Do Everything.