What’s AI-driven development? The third technology on Gartner’s 2019 strategic tech trends list automates time-consuming tasks for developers and more.
- Gartner’s Top 10 Strategic Technology Trends for 2019
- The Need for AI-Driven Development
- AI’s Impact on Application Development
- Stefanini’s AI Capabilities
In continuation of our series on Gartner’s top 10 tech trends for 2019, let’s talk about the third trend on Gartner’s list – AI-driven development. Following autonomous things and augmented analytics, investment in AI-driven development is expected to grow exponentially in the coming year.
What exactly is AI-driven development and why did it make Gartner’s list? Read on for the answer!
Gartner’s Top 10 Strategic Technology Trends for 2019
AI, smart spaces, and disruption, oh my! 2019’s trends are all about intelligent digital capabilities. To recap, Gartner has identified the following trends as having “substantial disruptive potential:”
1. Autonomous Things – Drones, robots, and autonomous vehicles are already using AI to automate functions that used to be performed by humans. Now, they can exploit AI to deliver advanced behaviors that interact more naturally with people and their surroundings.
2. Augmented Analytics – This specific area of augmented intelligence uses machine learning to transform how analytics content is developed, consumed, and shared. Augmented analytics automates the process of data preparation, insight generation, and insight visualization, eliminating the need for professional data scientists in many situations.
3. AI-Driven Development – Developers are getting a helping hand from AI. Details below!
4. Digital Twins – This digital representation of a real-world entity or system is expected to evolve over time, improving its ability to collect and visualize the right data, apply the right analytics and rules, and respond effectively to business objectives.
5. Empowered Edge – With this computing topology, information processing, and content collection and delivery are placed closer to endpoints. It tries to keep the traffic and processing local, with the goal being to reduce traffic and latency.
6. Immersive Edge – Virtual reality, augmented reality, and mixed reality are changing the ways people perceive and interact with the digital world. Companies should start thinking about providing their users with multichannel and multimodal experiences.
7. Blockchain – This type of distributed ledger provides transparency, enables trust, and reduces friction across business ecosystems by removing the need for central authorities in arbitrating transactions. It has the potential to lower costs, reduce transaction settlement times, and improve cash flow.
8. Smart Spaces – This trend refers to a physical or digital environment in which humans and technology-enabled systems interact in increasingly open, connected, coordinated, and intelligent ecosystems. In smart spaces, people, processes, services, and things come together to create a more immersive, interactive, and automated experience for a target set of people and industry scenarios.
9. Digital Ethics and Privacy – This trend is a huge concern for individuals, organizations, and governments. To get ahead, organizations in the public and private need to proactively address how they are using people’s personal information.
10. Quantum Computing – This term defines a type of nonclassical computing that operates on the quantum state of subatomic particles (for example, electrons and ions) that represent information as elements denoted as quantum bits (qubits). It can be applied to real-world business problems where a traditional algorithm would take too long to find a solution. Gartner predicts that industries like automotive, financial, insurance, pharmaceuticals, military and research organizations will benefit the most from advancements in QC.
The Need for AI-Driven Development
Today, the need for application developers to be able to operate AI-enhanced technologies independently is necessary. In order to do this, application developers and professional data scientists must work together to build AI-enhanced solutions that will allow the developer to leverage these technologies without prior expertise. According to Gartner, “this provides the developer with an ecosystem of AI algorithms and models, as well as development tools tailored to integrating AI capabilities and models into a solution.”
“Ultimately, highly advanced AI-powered development environments automating both functional and nonfunctional aspects of applications will give rise to a new age of the ‘citizen application developer’ where nonprofessionals will be able to use AI-driven tools to automatically generate new solutions,” said David Cearley, vice president and Gartner Fellow.
AI’s Impact on Application Development
As more companies strive to meet digital transformation initiatives, the pressure is on for application development teams to become even more productive. With AI and machine learning, AD teams can augment their work and increase their output.
By 2022, Gartner predicts that at least 40% of new AD projects will have an AI-powered ‘virtual developer’ on their team. With AI and ML automating time-consuming tasks within the realm of quality assurance and application testing, teams will find new ways of working in DevOps, mobile, and Internet of Things environments.
Called augmented software development, AI and ML will be leveraged to automate code preparation, validation, and generation, freeing up their human counterparts to focus on specialized problems that need human creativity and intuition. Of course, this approach comes with a learning curve as AI co-developers will need to correctly interpret software requirements and user stories expressed in the ambiguous ways that are a side effect of natural language. Therefore, human developers will need to translate conversations with end users and stakeholders into precise tests and logic their AI co-developers will comprehend. To do so effectively, Gartner recommends that developers and AD leaders advance and use their abilities in test-driven development (TDD) and behavior-driven development (BDD) techniques.
Stefanini’s AI Capabilities
At Stefanini, we have several technology trends mentioned by Gartner running in our Southfield Innovation Center, including AI-driven development. For instance, we are now showing the different faces of Sophie, our very own AI platform.
Sophie is integrated with Watson and machine learning, as well as the IoT platform. She interacts through voice with almost every experience in the Innovation Center, showing how she can go far beyond password reset.