Top 10 Artificial Intelligence App Development Trends in 2019

Businesses around the world are exploring AI technologies to advance themselves. The year 2019 appears to be quite promising for businesses which are showing all positive signs to adopt this game-chancing technology and get trans-formative values out of it.

From tech buyers to vendors, to investors, to governments, to academia, now all are learning and educating themselves about the capabilities of AI. Although AI hasn’t suddenly emerged, however until recently, many of us have been expecting the technology to come out in the light of science fiction novels and movies. AI is here for all good reasons! Many experts believe that AI and its subsets, like ML, NLP, and DP will soon become a mainstay in the business world.

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Now, more and more businesses are professing their commitments to apply AI technology to different processes. No doubt, the technology has captured the huge attention of the business world. Many organizations are already deriving trans-formative businesses-value from AI technologies.

1. The growing interest in AI business applications

AI frameworks like ML and DL are already powering the plethora of projects in organizations, but it does not end here only. The evolution of the technology is going on at niche levels and at many places, customization for typical business applications are also in demand. The trend helps in rapidly pushing a solution with pre-packaged software when there is a limited time-to-market is available. This year and on, traditional AI services paradigm will migrate to unique app pitched to serve specific use-cases. Typical AI apps serving these use cases will be massively functional for the future growth of AI.

2. AI getting blended with Blockchain, cloud, and IoT

No surprise you will soon see the future AI App development being blended with other advanced technologies like AI, Blockchain, and IoT as well as running on the cloud. These exponential technologies will come together in a single project and be transformed into an advanced solution. The interface to interact with such AI solutions will be IoT devices. Voice-enabled virtual assistants like Google’s Home and Amazon’s Alexa will also augment customer experience and will finally become the business contact point for customers. AI frameworks like Speech Recognition (SR) and Natural Language Process (NLP) will be implemented as the translation layer sensors and deciphering technology. Blockchain will be implemented as the immutable database core to manage contracts, requests, and transaction between various parties. Based on these above mentioned technologies, the final AI software stack will be the pillar to fulfill huge computational requirement of resources.

3. AI’s business value to receive more attention than achieving cost efficiency through it

Majority of top level executives have already started or engaged in conversations around AI since the beginning of 2019. With year progressing further, AI will move freely from cost restraints or cost efficiency to churning out more business worth out of the technology. Businesses, this year, will understand that an AI implemented to reduce cost isn’t a justification with the technology. AI can be used to spot revenue loss, enhance customer experience, and simplify and reinvent several operations instead. This certainly can lead a business to generate more revenue, but AI cannot directly be implementation to bring in cost-efficiency to a business.

4. AI hardware and software infrastructure development

AI’s omnipresent availability will require the designing and development of hardware and software this year. We will see an explosion in the design, development, and optimization of hardware and software that run and drive artificial intelligence applications. We will also see a huge demand of special chipsets that can successfully run AI apps with minimum latency. This will happen due to increasing size and scale of data being used by AI applications to perform complex operations.

Smart assistants and wearables for end-customers will also get a massive demand in the market. No doubt, this disruption will continue to challenge typical software paradigms. With architectural components like edge computing becoming more common, latest AI application development projects will now be designed with having more locally available power.

5. Tools and technology for data being accessed by enterprises

The key reason why analytics and data-driven decision making received widespread adoption in past years was the development of such application that democratized the power of data. With these applications, data started to move free from remote silos and wasn’t accessible to the most sophistical techies only. These tools and technology frameworks put data into the mainstream, as a cornerstone, for how enterprise strategize and execute operations. So, by observing these patterns and as expected, data will not be limited to the limited people only. With the right tools and technology, anybody wishing to access data can access it. It will be new normal.

6. Formulation of policies fostering and governing AI

China announced its National Policy in 2017 and pushed others to take on policy level intervention for AI. This year many countries are expected to come forward with their versions of policies fostering and governing AI.

7. NLP to get revolutionized by Speech Recognition

Natural Language Understanding (NLU) and Natural Language Generation (NLG) have been making huge strides for last few years. NLP algorithms are now able to decode emotions, sarcasm, and figures of speech. Also, voice assistants will extract data from voice and blend it with the deep learning to relate the words spoken with emotions. This will help developers enrich the library processing speech and text.

8. The growth of explainable AI

With several decisions being powered by AI, we will see the growing demand of explainable AI too. The explainable AI helps executives get an explanation from AI that why it made certain recommendations. The need of the high level transparency and trust will lead the development of explainable AI. It will make AI decision making process free from biases.

9. Blending AI and analytics together

They year 2019 will exhibit a convergence of analytics and AI for uncovering and understanding insights from data. The AI algorithms are now fully capable of taking up tasks related to complex insight generation from multi-channel and huge data. This blend will help businesses in automation, improving decision making efficiency, and powering business planning and strategies.

10. AI to be implemented for cyber security

Last but not least, AI will be implemented for the transformation of cyber security paradigms. AI will provide a massive boost how secure to environments from threats. ML powered solutions can detect anomalies and reduce the time required to understand potential intrusions or attacks. AI, with the combination of ML, will give cyber security a huge boost by decentralized and traceable databases.

Author Bio. :- Sofia Coppol is is the technical writer of Rapidsoft technologies, a prominent mobile app development company which provides Android app development and iPhone app development services across the global. She loves to write on latest mobile trends, mobile technologies, startups and enterprises.

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