The trend towards digital transformation of the enterprise, regardless of industry or sector, will accelerate in 2017 from the already significant levels seen last year. We identify the following seven digital technology trends as game changers for software-driven enterprises.
The crumbling of the barriers to entry for machine intelligence – driven by the availability of high-quality open-source software components; cloud platforms from all major providers; and the availability of wildly popular and high-quality introductory courses on MOOC platforms – will drive growing mainstream adoption of machine intelligence as a differentiating and foundational technology layer in the digital transformation stack for identifying and closing new revenue opportunities, customizing user experience, driving operational efficiencies, and predicting failures. Also expect to see acceptance and greater adoption of advanced machine learning techniques for delivering closed-loop actionable insights in domains such as the Industrial Internet of Things and cybersecurity.
The fully distributed, transparent, tamper-resistant, and auditable shared ledger technology known as blockchain is particularly powerful in settings where multiple parties need to reconcile without a central intermediary, or need to track provenance of assets across organizational boundaries, or need to establish and enforce contracts between untrusting parties and speed up reconciliation with a secure and verifiable audit trail. We will see real applications across domains such as supply chain, inventory tracking, core banking, insurance, healthcare, IoT, and identity solutions. Second-generation blockchain platforms will address security, privacy, performance, governance, and scalability concerns. Decentralized Applications (DApps) on blockchain will mature and will look attractive particularly in consumer-facing applications.
Data breaches, ransomware, and large-scale Internet of Things (IoT)-enabled Distributed Denial of Service (DDOS) attacks will continue to dominate enterprise security. Overall, we will see an increase in attacks on critical infrastructure pertaining to verticals such as healthcare, energy, transportation, banking, payment systems, and airlines. Malware and botnet code will be open-sourced, and will be offered as “services” on the dark web. Some of the things a CIO or CISO should do to defend the enterprise against such threats are: educate employees; go beyond passwords with multi-factor authentication; pay attention to smart devices and “things”; and use machine learning to power key defensive strategies.
Although the technology development of data lakes has come a long way, ISVs have been slow in winning trust from enterprises, as data lake tools are not yet mature enough for real enterprise use cases and there is a lack of seamless end-to-end integration between components. As this tooling matures, we expect to see an increasing trend of enterprise adoption of data lakes as their end-to-end BI and data warehouse solution. Data lakes will start providing data orchestration and workflow capabilities that will allow applications to identify and capture data-driven insights and call pre-registered actions within the application or on another related application, eventually integrating with BPM tools. Data Lakes as a Service (DLaaS) offerings will become popular with enterprises, especially for IoT and social data scenarios.
The very nature of Human-Machine Interaction (HMI) continues to evolve, with only the Human component remaining fixed; both the nature of the Machines and the modalities of the Interactions are in constant flux. Multi-modal HMI will grow and spread rapidly. Virtual Reality (VR) and Augmented Reality (AR) will expand beyond visual immersion to include multiple human senses and create a personalized interactive experience. Additional key features that we see emerging include: the use of artificial intelligence and machine learning; the use of multi-factor biometric authentication to establish user identity; and the seamless integrated interconnection of a large variety of diverse end-user devices.
Software engineering is undergoing a paradigm shift as software-driven businesses are taking center stage on the world platform. Overall, the software engineering trends clearly indicate movement towards intelligent, data-driven software engineering with high levels of automation and optimization. We will see tremendous focus and momentum on automation and optimization using machine learning and continuous engineering, architectural styles to support massive data and scale (Lambda and Microservices), and a shift towards functional programming and low-code/no-code platforms. On the process front, engineering practices (Inspect & Adapt, Agile) will enter into the business stack.
Some common cross-industry trends in the Internet of Things (IoT) are clear. Security of deployments will take center-stage. The need for ecosystem integration between various IoT systems and enterprise systems will accelerate the growth of APIs and connectors to reduce integration efforts. Standardization efforts will intensify and are likely to result in some consensus, at least within verticals. Platforms that integrate with multiple third-party IoT platforms and provide device management services across all of them will gain foothold with customers. Deployments will include edge computing facilities. All major platforms will continue to improve their real-time and offline analytics with deep learning technologies.
As a senior business leader, your primary interest is in understanding the nature and degree of impact that each technology trend will have on your end customers, and how you can optimally leverage the trend to successfully grow your business. The full report focuses on both aspects, providing for each trend a brief description and a set of three business questions to help you get started on your digital transformation journey.------------------------------------------------------------------------------------------------------------------------------------------------------------This piece is a summary of a much more comprehensive white paper, which may be downloaded from here
About the author
Dr. Siddhartha Chatterjee
Dr. Siddhartha Chatterjee (Sid) is the Chief Technology Officer at Persistent Systems, he is responsible for technology leadership both externally and internally. Prior to Persistent, Sid was with IBM for 13 years during which, he has held multiple technical, strategic, managerial, and executive positions across IBM Research, IBM Systems & Technology Group, and IBM Global Technology Services. He holds a B. Tech. (Honors) degree in Electronics and Electrical Communications Engineering from IIT, Kharagpur and a Ph.D. in Computer science from Carnegie Mellon University, Pittsburgh, U.S.
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