There has been mind-boggling progress in Artificial Intelligence technology during recent years. It is not the esoteric technology that once was used in imaginary applications. Artificial Intelligence has revolutionized several industries in the modern world.
Especially after its emergence in mainstream business, it is expected to be a game changer that will open new avenues. Business organizations that adopt this innovative and useful technology are about to derive transformative, unprecedented business value.
The foray of Artificial Intelligence (AI) into mainstream business occurred quite long back, but it remained on the periphery. Now, with overall development on the technology front has ensured that this futuristic technology powers several of the contemporary industries. Web and mobile application development, for instance, is expected to advance in leaps and bounds.
Capability and awareness of AI have increased among various stakeholders such as technology entities, governments, academia, investors, and vendors. An increasing number of such stakeholders have begun to leverage AI technology within their specific organizations. It is clearly going to witness huge adoption in varied fields in the forthcoming years. It is worthwhile to take a close look at the potential trends in this transformative technology.
How and in What Ways Artificial Intelligence is Going to Revolutionize the World in Near Future?
1. Virtual Assistants and Chatbots
Voice recognition technology has reached unanticipated levels in the contemporary world. The ability to process natural language has become a demanded intelligence today. Natural language processing—in combination with speech recognition technology—will offer great help to businesses in the future. Solutions include simulating understanding as well as producing usable information, thus delivering immense business value.
Advanced Chatbots, now christened ‘Virtual Agents,’ are AI-powered. Provided with face and voice features, these will assist customers greatly by personifying a company. Customer service will improve and considerable business growth can be achieved. AI-enabled virtual agents are set to go beyond their present role of answering users’ queries, assisting in their shopping, and collecting feedback. In future, chatbots will act as personalized assistance and involve in engaging conversations with consumers. This will be made possible by the ability to learn consumer behavior and through leveraging AI-oriented machine learning.
2. The Confluence of AI, Cloud, and IoT
Exponential technologies such as Blockchain, IoT, and AI could be running on the cloud in the future. Such a software stack facilitating the coming together of such technologies will lead to great value creation. AI and IoT are expected to converge more at edge computing, most of the cloud-trained
models being placed at the edge layer.
In enterprises level, IoT will emerge as AI’s primary driver. Specially devised AI chips will have edge devices embedded. Industrial IoT applications will witness an increase in AI’s multifarious usage. Unlimited possibilities will be brought into light with the confluence of AI and IoT.
IoT devices will play the role of an interface using which various stakeholders including consumers will interact. AI-enabled devices will be catering to most of the future user requirements. They will make managing tasks such as health vitals monitoring more efficient.
3. Automated Machine Learning Will Become Prominent
Automated machine learning (AutoML) algorithms are set to bring about radical changes in machine learning. Developers will be able to solve complex problems without having to create specific models. AutoML will facilitate focusing on problems only, rather than considering the entire workflow and process.
Currently, although machine learning promises unlimited possibilities, the advanced expertise required for these is found to stifle them. AutoML, when applied properly, will empower developers and business analysts to evolve models of machine learning. This will enable skillfully handling of complex scenarios.
As issues are directly addressed and AutoML aligns seamlessly with custom ML platforms and cognitive APIs, time, as well as efforts, will be saved. The blending of portability and flexibility will become a reality.
4. DevOps Automation Through AIOps
Artificial Intelligence for IT Operations (AIOPs) is representative of the convergence of DevOps with AI. This convergence will become mainstream in the year 2019, providing considerable benefits to enterprises and vendors
Modern infrastructure with a huge number of applications generates quite a lot of data. This data needs to be indexed, filtered, and used for analytics. It has to be aggregated as well as correlated for finding patterns and insights. IT operations can be made proactive by adopting AI and machine learning models to these datasets and making them predictive.
By deploying AI, IT operations will be enabled to perform their tasks in a much shorter time, while getting to the root of the issue fast. AIOps will become operational in the recent future.
5. AI Will Play a Key Role in Cybersecurity
Use of AI and Machine Learning in cybersecurity will witness a huge upsurge. This will help businesses to transform their cyber defense, by revolutionizing both physical and cybersecurity paradigms. Advances in the field of machine learning-based anomaly identification will reduce the time needed for surfacing potential threats into safe environments.
Innovative approaches that make use of AI and machine learning will empower cybersecurity experts to meet the mounting security threats more efficiently. Potential security breaches will be thwarted. Even subtle indicators about abnormalities will be detected in real-time, nipping threats in the bud itself.
6. Neural Network Interoperability Will Become Key
In developing the models of AI-based neural networks, choosing the appropriate framework is an issue that needs to be overcome. Developers are faced with the difficulty of selecting one from a range of tools. Furthermore, when once a specific model has been chosen and trained, naturally it becomes tough to work on any other framework with another tool.
Interoperability—rather the lack of it—among the various neural network toolkits is a hindrance to AI adoption. Neural network technologies are expected to improve in 2019, enabling AI to become sophisticated. Enhanced network architectures and better training methods will be developed.
7. Open Source Frameworks
Open-source software has helped clear the barriers to AI adoption. Today, there are several open-source tools that mobile and web application developers may use efficiently.
With an increasing number of organizations seeking knowledge sharing and collaboration, an open source AI will be a dominant factor in the evolution and adoption of AI.
In the coming years, Artificial Intelligence and Machine learning will not be confined to core technology alone. They are about to make a big, positive impact on various businesses from several industries as well as on the society in general.
Future AI and ML models will transform business digitally in unprecedented ways. AI will certainly be in the middle of the myriad ongoing changes. It will intersect with society in a big way in 2019.