Gartner’s Report on Top 10 Strategic Technology Trends for 2020

Originally Appearing in Gartner, 21 October 2019

Strategic technology trends have the potential both to create opportunity and to drive significant disruption. Enterprise architecture and technology innovation leaders must evaluate these top trends to determine how combinations of trends can power their innovation strategies.

Key Findings
Strategic technology trends have significant potential to create and respond to disruption and to power both transformation and optimization initiatives.
Artificial intelligence (AI) is a foundational catalyst for advanced process automation and human augmentation and engagement.
Physical environments including factories, offices and cities will become “smart spaces” within which people will interact through multiple touchpoints and sensory channels for an increasingly ambient experience.
Dealing with privacy, digital ethics and security challenges generated by AI, the Internet of Things (IoT)/edge, and other evolving technologies will become critical to maintain trust and avoid legal entanglements.

Recommendations
Enterprise architecture and technology innovation leaders must:
Center their innovation efforts on people and use tools such as personas, journey maps, technology radars, and roadmaps to evaluate opportunities, challenges and time frames for adoption.
Build an overarching view across functional and process silos and exploit a complementary set of tools including RPA, iBPMS, DTO, application development, and AI domains that guide how the tools are used and the systems they create are integrated.
Embrace multiexperience and implement development platforms and design principles to support conversational, immersive and increasingly ambient experiences.
Establish governance principles, policies, best practices and technology architectures to increase transparency and trust regarding data and the use of AI.

Strategic Planning Assumptions
By 2022, 70% of enterprises will be experimenting with immersive technologies for consumer and enterprise use, and 25% will have deployed them to production.
By 2022, 35% of large businesses in the training and simulation industry will evaluate and adopt immersive solutions, up from less than 1% in 2019.
By 2021, at least one-third of enterprises will have deployed a multiexperience development platform to support mobile, web, conversational and augmented reality development.
By 2024 75% of large enterprises will be using at least four low-code development tools for both IT application development and citizen development initiatives.
By 2022, at least 40% of new application development projects will have artificial intelligence co-developers on the team.
By 2021, automation of data science tasks will enable citizen data scientists to produce a higher volume of advanced analysis than specialized data scientists.
By 2025, a scarcity of data scientists will no longer hinder the adoption of data science and machine learning in organizations.
By 2022, 30% of organizations using AI for decision making will contend with shadow AI as the biggest risk to effective and ethical decisions.
Through 2023, 30% of IT organizations will extend BYOD policies with “bring your own enhancement” (BYOE) to address augmented humans in the workforce.
By 2020, we expect that companies that are digitally trustworthy will generate 20% more online profit than those that aren’t.
By 2020, we expect that 4% of network-based mobile communications service providers (CSPs) globally will launch the 5G network commercially.
By 2024, most cloud service platforms will provide at least some services that execute at the point of need.
By 2023, blockchain will be scalable technically, and will support trusted private transactions with the necessary data confidentiality.
Through 2022, over 75% of data governance initiatives will not adequately consider AI’s potential security risks and their implications, resulting in quantifiable financial loss.
Through 2022, 30% of all AI cyberattacks will leverage training-data poisoning, AI model theft or adversarial samples to attack AI-powered systems.

Shamima Paurobally