By 2018, 20% of business content will be authored by machines.
Technologies with the ability to proactively assemble and deliver information through automated composition engines are fostering a movement from human- to machine-generated business content. Data-based and analytical information can be turned into natural language writing using these emerging tools. Business content, such as shareholder reports, legal documents, market reports, press releases, articles and white papers, are all candidates for automated writing tools.
By 2018, six billion connected things will be requesting support.
In the era of digital business, when physical and digital lines are increasingly blurred, enterprises will need to begin viewing things as customers of services — and to treat them accordingly. Mechanisms will need to be developed for responding to significantly larger numbers of support requests communicated directly by things. Strategies will also need to be developed for responding to them that are distinctly different from traditional human-customer communication and problem-solving. Responding to service requests from things will spawn entire service industries, and innovative solutions will emerge to improve the efficiency of many types of enterprise.
By 2020, autonomous software agents outside of human control will participate in 5% of all economic transactions.
Algorithmically driven agents are already participating in our economy. However, while these agents are automated, they are not fully autonomous, because they are directly tethered to a robust collection of mechanisms controlled by humans — in the domains of our corporate, legal, economic and fiduciary systems. New autonomous software agents will hold value themselves, and function as the fundamental underpinning of a new economic paradigm that Gartner calls the programmable economy. The programmable economy has potential for great disruption to the existing financial services industry. We will see algorithms, often developed in a transparent, open-source fashion and set free on the blockchain, capable of banking, insurance, markets, exchanges, crowdfunding — and virtually all other types of financial instruments
By 2018, more than 3 million workers globally will be supervised by a robo-boss.
Robo-bosses will increasingly make decisions that previously could only have been made by human managers. Supervisory duties are increasingly shifting into monitoring worker accomplishment through measurements of performance that are directly tied to output and customer evaluation. Such measurements can be consumed more effectively and swiftly by smart machine managers tuned to learn based on staffing decisions and management incentives.
By year-end 2018, 20% of smart buildings will have suffered from digital vandalism.
Inadequate perimeter security will increasingly result in smart buildings being vulnerable to attack. With exploits ranging from defacing digital signage to plunging whole buildings into prolonged darkness, digital vandalism is a nuisance, rather than a threat. There are, nonetheless, economic, health and safety, and security consequences. The severity of these consequences depend on the target. Smart building components cannot be considered independently, but must be viewed as part of the larger organizational security process. Products must be built to offer acceptable levels of protection and hooks for integration into security monitoring and management systems.
By 2018, 45% of fastest-growing companies will have fewer employees than instances of smart machines.
The initial group of companies that will leverage smart machine technologies most effectively will be startups and other newer companies. The speed, cost savings, productivity improvements and ability to scale of smart technology for specific tasks offer dramatic advantages over the recruiting, hiring, training and growth demands of human labor. Some possible examples are a fully automated supermarket or a security firm offering drone-only surveillance services.
By 2018, customer digital assistant will recognize individuals by face and voice across channels and partners.
The last mile for multichannel and exceptional customer experiences will be seamless two-way engagement with customers and will mimic human conversations, with both listening and speaking, a sense of history, in-the-moment context, timing and tone, and the ability to respond, add to and continue with a thought or purpose at multiple occasions and places over time. Although facial and voice recognition technologies have been largely disparate across multiple channels, customers are willing to adopt these technologies and techniques to help them sift through increasing large amounts of information, choice and purchasing decisions. This signals an emerging demand for enterprises to deploy customer digital assistants to orchestrate these techniques and to help “glue” continual company and customer conversations.
By 2018, 2 million employees will be required to wear health and fitness tracking devices as a condition of employment.
The health and fitness of people employed in jobs that can be dangerous or physically demanding will increasingly be tracked by employers via wearable devices. Emergency responders, such as police officers, firefighters and paramedics, will likely comprise the largest group of employees required to monitor their health or fitness with wearables. The primary reason for wearing them is for their own safety. Their heart rates and respiration, and potentially their stress levels, could be remotely monitored and help could be sent immediately if needed. In addition to emergency responders, a portion of employees in other critical roles will be required to wear health and fitness monitors, including professional athletes, political leaders, airline pilots, industrial workers and remote field workers.
By 2020, smart agents will facilitate 40% of mobile interactions, and the postapp era will begin to dominate.
Smart agent technologies, in the form of virtual personal assistants (VPAs) and other agents, will monitor user content and behavior in conjunction with cloud-hosted neural networks to build and maintain data models from which the technology will draw inferences about people, content and contexts. Based on these information-gathering and model-building efforts, VPAs can predict users’ needs, build trust and ultimately act autonomously on the user’s behalf.
Through 2020, 95% of cloud security failures will be the customer’s fault
Security concerns remain the most common reason for avoiding the use of public cloud services. However, only a small percentage of the security incidents impacting enterprises using the cloud have been due to vulnerabilities that were the provider’s fault. This does not mean that organizations should assume that using a cloud means that whatever they do within that cloud will necessarily be secure. The characteristics of the parts of the cloud stack under customer control can make cloud computing a highly efficient way for naive users to leverage poor practices, which can easily result in widespread security or compliance failures.
The growing recognition of the enterprise’s responsibility for the appropriate use of the public cloud is reflected in the growing market for cloud control tools. By 2018, 50 percent of enterprises with more than 1,000 users will use cloud access security broker products to monitor and manage their use of SaaS and other forms of public cloud, reflecting the growing recognition that although clouds are usually secure, the secure use of public clouds requires explicit effort on the part of the cloud customer.