Adopt these 10 strategic technologies in 2020

Research and advisory company Gartner released a report on the top 10 strategic technology trends predicted for 2020. Using this predictive information, technology innovation leaders can plan strategies for the new year and where to focus their efforts for technological and AI adoption.

The full report from Gartner weighs in at a hefty 52 pages with insights from analysts David Cearley, Brian Burke, David Smith, Nick Jones, Arun Chandrasekaran, and CK Lu. Interested individuals can download their free copy.

What are the 10 highlighted technologies? Let’s take a dive into each of them and how they can potentially change the enterprise landscape.

Hyperautomation

Automation requires the use of tools each with their own narrowly defined specific purpose. By using these tools in combination technology can become nearly entire automatic and adaptive.

The two most important components are robotic process automation (RPA) and intelligent business management suites (iBPMSs). RPAs connect legacy systems with modern systems and iBPMSs manage long-running processes. These two technologies will be used and deployed together to create sophisticated, automatic models.

SEE ALSO: Can you trust a robot more than your manager? Oracle study says 64% already do

Multiexperience

The way that users interact with the digital world is changing and opening up to a multisensory experience. Also referred to as ambient experience, Multiexperience refers to the future of multisensory and multitouchpoint technology.

Immerse experiences such as virtual reality and augmented reality are becoming more commonplace. According to Gartner, these have potential in the realm beyond entertaining apps like Pokémon GO. For instance, VR and MR can help improve product design and visualization, field service and operations, and training simulation.

Perhaps in a few years, you will encounter a job training program that is entirely virtual reality.

Democratization

Democratization and citizen access give all people the potential to access technical expertise. This levels the playing field and forgoes expensive training classes that many people, including non-experts, are unable to access.

The future of the citizen developer may include the ability to develop with zero code or code knowledge. Assisted development tools may become mainstream, enabling all people to potentially experiment with machine learning and AI.

As for AI specialists, Gartner predicts that by 2022, at least 40% of new application development projects will have AI co-developers on the team.

Human augmentation

Human enhancement is nothing new, as anyone with glasses, a prosthetic limb, a smart watch, a pacemaker, or orthodontic braces will tell you. However, the future opens up new speculative doors for cognitive and physical augmentation.

For instance, it may be possible in the future to detect your glucose levels via smart contact lenses. Wearables will also likely become more commonplace and extend their functionalities, perhaps by enhancing abilities like hearing or sense of smell.

The controversial and ethical side of this include gene and cell therapies and genetic engineering. Time will tell how human rights are potentially impacted by these loaded topics.

Transparency and traceability

Ethics in AI and information privacy are growing concerns for both individuals and businesses alike. People want more active control over their data and personal information.

The six key elements of trust are ethics, integrity, openness, accountability, competence, and consistency. Especially with the EU’s GDPR, businesses should be mindful regarding data transparency in the upcoming years.

Empowered edge

The future of edge devices includes simple embedded devices, edge input/output devices, edge computing devices, and complex embedded edge devices. Edge devices will increase in sophistication.

Edge computing includes tech on the Internet of Things. According to a 2018 IoT Analytics report, there are currently seven billion IoT devices and the number is accelerating. Looking into the future, it is possible that by 2023, there will be over 20 times as many smart devices at the edge of the network.

Distributed cloud

Cloud computing and hybrid scenarios aren’t going anywhere in 2020. From Gartner:

Distributed cloud allows data centers to be located anywhere. This solves both technical issues like latency and also regulatory challenges like data sovereignty. It also offers the benefits of a public cloud service alongside the benefits of a private, local cloud.

Gartner predicts distributed cloud computing will happen in three separate phases and that by 2024, “most cloud platforms will provide at least some services that execute at the point of need”.

Autonomous things

Both semi and fully autonomous technologies such as drones will likely continue to grow in use in 2020 and beyond. While currently many autonomous devices are limited to private use, it is likely they will become more common in the public sphere.

What else may become autonomous in the future? Gartner predicts autonomous tech may impact agriculture, self-driving cars, shipping companies, and search and rescue.

SEE ALSO: Women in tech: “A lack of ethics in tech and digital transformation”

Practical blockchain

By now, most people are aware of the potential use cases for blockchain or are familiar with how its most successful endeavor, Bitcoin, works. Blockchain and the use of smart contracts distribute trust and allow for everyone with access to the blockchain to access the same information and trace assets back to their origin.

Just some of the future potentials for blockchain may include a blockchain-based voting system, a self-sovereign digital identity, or cryptocurrency payments and remittance services.

Gartner predicts that blockchain will be scalable by the year 2023.

AI security

While AI is powerful and helpful for many businesses, it also opens up a large number of security holes. Security is evolving fast, and risk management experts have to keep up with new kinds of attacks, previously never seen before. AI and ML tools such as DeepExploit and identity deception tools pose a serious threat.

Gartner predicts that through 2022, 30% of all AI security attacks will use training-data poisoning, AI model theft, or adversarial samples to attack AI-powered systems.

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