Virtusa Corporation, a global provider of digital strategy, digital engineering, and IT services and solutions that help clients change and disrupt markets through innovation engineering, today announced the findings of detailed research that identifies trends that will drive emerging technology investments in 2020. The third annual Virtusa xLabs’ Trend Almanac details the top ten technology trends that will strategically align with business and technology investments.
The major trends, which Virtusa identified in collaboration with technology and business leaders, focus on the Financial Services, Insurance, and Life Sciences industries. Aligning investments to the most influential technology trends will help businesses to stay competitive and drive growth in 2020 and throughout the new decade.
The full report identifies three overriding themes:
* The democratization of emerging tech, reducing the investment, and skill needed to develop and capitalize on tech across infrastructure, applications, and data.
* The need for transparency, ethical practice, and good governance to balance the manic rush to explore and exploit "The New."
* A change in how companies manage tech-enabled innovation programs, ensuring that tech is seen as a means to drive better commercial outcomes, rather than being an end in itself.
“The Virtusa xLabs’ Trend Almanac exposes the new business imperatives that business and technology leaders need to invest in to remain competitive,” said Senthil Ravindran, EVP and global head of cloud transformation and digital innovation, Virtusa. “Digital transformation demands a new way of thinking and getting a jump start on the trends that will impact customers tomorrow. This Trend Almanac will be a key resource in helping businesses do just that.”
The top ten trends include:
Open Banking Goes Global: Open Banking is starting to become a global movement. To date, actual regulations and market changes have only occurred in Europe, even though, as a topic it has been on everybody's tongue. But the move by Australian regulators to implement substantial regulatory reforms this year, giving consumers greater control of their data, signals the paradigm shift to the API economy is well underway. We explore this trend and classify the current approaches to Open Banking across the world.
No Child's Play in the Sandbox. A new breed of regulatory sandbox is making waves. Thematic regulatory sandboxes are credited with taking a more focused approach to sandbox design, where the policy objectives, as well as the problems tackled by the sandbox, are clearly defined. This appeals to regulators as much as fintechs and big firms, who are looking to build engagement and accelerate promising innovations to markets in a controlled and safe environment.
Value Over Volume in Healthcare. Healthcare systems around the world are sinking under the weight of escalating costs. However, there are positive signs that a transition is underway from the reigning fee-for-service delivery model, which has contributed to the cost overhang in many countries, towards the value-based care model. Regulatory and technology forces are key factors that are driving this shift. In 2020, we believe this pivot to value-based care will gain further momentum.
Shop Now, Pay Later. Point of sale finance is getting red hot. In recent years, digital startup lenders have carved up the segment, leveraging the latest tech to introduce installment loans to the millennial market, but also thinking outside the box by devising new business models. Consumers are on board, as are retailers. Meanwhile, banks have mostly been onlookers, having decided not to develop their own customer-facing solutions. In 2020, we think banks will get into the game.
The End of All Disease? CRISPR (Clustered Regularly Interspaced Short Palindromic Repeats) is a breakthrough technology lauded for its extraordinary precision and ease of use. Since Doudna and Charpentier’s landmark paper was published in 2012, there has been a flurry of research activity and much progress as well as media interest in the field. CRISPR is now poised to move into the next phase in the journey from lab to market.
From Factory to App: Automobiles Take a New Route. Consumer adoption of “mobility as a service” (MaaS) is challenging the auto manufacturers' traditional approach to "mobility as an asset." Tech-enabled innovations, such as ride-sharing, last-mile micro-mobility solutions, and the rise of autonomous cars as a utility, are driving the growing popularity of MaaS offerings. In 2020, auto manufacturers will join this trend by creating new propositions around MaaS.
Ready, Set, Quantum! After decades in the wilderness, quantum computing is finally hitting its stride. Instead of being held back by hardware hurdles, in a surprising twist, enterprises have been powering ahead with innovations on “near- term” quantum machines. No longer is this esoteric field the domain of researchers alone, it is now being addressed by a broader set of players, helped along by greater access to tools and collaborations.
Corporate Innovation Hubs Grow Up. The reputation of corporate innovation hubs has taken a hit in recent years, causing businesses to rethink their operating model. This year, there will be a greater focus on empowering a network of affiliate labs in a federated model, which will enable labs to pursue innovation rather than incremental optimizations. With this model, there will be greater alignment between the business unit’s objectives, its funding, and the activities of the innovation program.
Self-Aware Infrastructure. In a digital world run by infrastructure, machine learning is weakening the dependence of human supervision. Progressively, smart infrastructure will be able to self-govern, self- optimize, and self-heal, resulting in highly optimized, fault-tolerant infrastructure. As cloud service providers continue to expand their footprint in the infrastructure market, we will see the first signs of self-aware infrastructure in 2020.
Machine Learning for All. In 2020, we believe there will be more efficient algorithms to automate Machine Learning (AutoML). This will spur the adoption of AutoML at the enterprise level, helping non-tech firms access the capabilities to build ML applications quickly. This democratization of machine learning will also make AI experts and data scientists more productive and advance the field of AI to new frontiers.
