Artificial intelligence has maintained a steady graph of growth in the past few years. But the pandemic led to a rapid digital transformation, which further prompted rapid innovation in the realm. As per McKinsey’s State of AI survey published in November 2020, half of the survey respondents had stated their companies had adopted AI in at least one function.
Experts well versed in the AI domain predict that it’ll continue to experience vast expansion and development in meaningful ways in 2021 and beyond. 2021 is expected to present many promising developments and may turn out to be the golden year of AI implementation.
Let’s mull over some of the developments in the domain of AI that you can expect.
- Automated governance will control AI applications
New age businesses are wary of Rogue AI. In 2021, enterprises will enhance AI governance across their organisations by implementing strong model assurance within their machine learning operational workflows. This will be crucial for ensuring that AI apps perform their intended functions appropriately. At the same time, the apps will steer clear of privacy violations, demographic biases, and other negative algorithmic outcomes.
Vendors of AI governance systems will expand their capacity to deploy and manage a steady flow of assured models all the way to edge devices.
- AIOps is the future
The complexity of IT systems has increased remarkably in the past several years. An AIOps solution allows IT operations and other teams to upgrade the essential processes, tasks, and decision-making through nuanced analysis of the volumes and categories of data coming it’s way. It was reported that vendors have come up with platform solutions that merge multiple monitoring disciplines like application, infrastructure, and networking.
In such circumstances, IT leaders must rely on AIOps providers who can empower cross-team collaboration through data correlation. Such providers also offer end-to-end digital experience and integrate smoothly into IT operations management tools.
- Facial recognition as a dominant AI-based contactless authentication technology
In 2021, enterprises will integrate advanced facial recognition for solid authentication within a range of internal and consumer-centric applications. At the same time, businesses will avoid using the technology to inference identity, gender, race, and other factors that might be sensitive from a bias, privacy, or surveillance standpoint.
If businesses incorporate facial recognition in image/video auto-tagging, query-by-image, and other such applications, it’ll require extensive review by legal teams. The sensitivity of this technology and the legal risks involved will only grow in the foreseeable future.
- AI structures unstructured data
In the coming year, organisations will leverage machine vision and natural language processing (NLP) to simplify the structuring of unstructured data like images or emails. The objective of it is to process data that robotic process automation (RPA) technology can use to automate transactional activity in the organisation.
“RPA is said to be the fastest-growing area of software adoption. But RPA comes with its set of limitations”, states Jared Mason, an SAP assignment help expert. For instance, it can only process structured data. Using AI to accomplish the complex task of deciphering unstructured data and then offer a defined output like a consumer’s intention will allow RPA to complete the action.
- Edge-based AI will break neural networks down to their essence
In 2021, AI developers will reduce all their models’ neural network architectures, hyperparameters, and other features to suit the hardware constraints of edge platforms. AI-model compilers are automating the tuning and compression of AI models for efficient execution across multiple edge endpoints.
In the near future, we’ll witness more AI developers use neural architecture search techniques to look for the most compact, efficient structure of a neural net for a particular task of AI inference. Compressing AI algorithms down to their predictive essence will quicken the movement of most AI workloads to function on the microcontrollers embedded in edge devices.
- The amalgamation of AI and IoT
AIoT isn’t anything new, but we’ll finally notice the seamless merger between AI and IoT. The trend already has found its way into the industry and is a part of many valuable use cases. Adding AI into the equation will allow AIoT systems to take actions, carry out tasks and learn automatically based on the data without human involvement, like in redirecting traffic, locking doors, turning off lights, etc.
AIoT will also have a prominent presence in smart buildings, cities and retail environments, where data will be leveraged to provide optimum security, enhanced sustainability practices, smooth customer experience, real-time offer optimisation, etc.
It’ll undoubtedly influence almost every industry verticals, including aviation, automotive, finance, manufacturing, healthcare and supply chain.
- Emphasis on the total of AI ownership
Until some years ago, only the distinguished companies like Google, Amazon and Facebook could develop AI-based solutions. Today, technology has become more accessible to the vast majority of organisations.
The number of Artificial Intelligence-based solutions and projects powered by Machine Learning is growing exponentially. This has resulted in the development of various and affordable ML frameworks and libraries.
Intrigued by the promises and perks of investing in AI, businesses are eager to implement Artificial Intelligence technologies to automate their operations. More recently, the focus of different organisations has shifted from only seeing the benefits to the cost in total to develop and maintain an advanced AI-solution.
- The emergence of AI as a service
AI as a Service mixes the AI services with the SaaS business model, which helps bring Artificial Intelligence to the masses without a hefty price tag. It’s not only because AI promotes efficiency and optimisation to processes, but also because the future of digital transformation itself rests on the democratisation of the new technologies.
The most prominent advantage of AI as a Service is that it lets businesses use AI’s power even without the expertise to manage it when there’s a shortage of AI experts.
All in all, 2021 will witness the launch of many AI applications, offering efficiency, insights and cost-effectiveness in the digital era. And while it’ll continue impacting all aspects of businesses, mentioned here are some aspects where AI is predicted to have the biggest impact this year.
Author bio: Ema Lee is asoftware developer for an esteemed corporate organisation in Australia. She holds a vast knowledge of AI and IoT and dabbles into blogging as well. She’s also an academic expert who provides software engineering assignment help service to students.