Artificial Intelligence and Big Data Technologies Drive Business Innovation in 2018

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Software and web development companies these days, especially those in Australia, bring technology and innovation to customers wherever they may be located in the world. The two most popular technology innovations these days are Big Data and AI.  Service providers make use of these hottest technology trends to keep pace with the tough competition and to provide clients only with highly effective and dynamic solutions.

At the intersection of smart technology and analytics, companies are beginning to realize the long-awaited benefits of Artificial Intelligence. After years of promise and hope, this year may be the year when AI gains meaningful traction within Fortune 1000 organizations. An overwhelming 97.2 percent of executives report that their organizations are investing in creating or launching big data and AI initiatives. Among the executives surveyed, a rising consensus is emerging that big data and artificial intelligence initiatives are getting closely intertwined, with 76.5 percent of executives indicate that the greater availability of data and proliferation is empowering AI and cognitive initiatives within their enterprises.

Now, executives see a direct correlation between AI initiatives and big data capabilities. For the first time, huge corporations report that they have direct access to meaningful sources and volumes of data, which could feed AI algorithms to understand behaviors and detect patterns. Not dependent on data subsets to do analyses, these organizations combine big data, computing power and AI algorithms to produce an array of business benefits form real-time consumer credit approval to new product offerings. Organizations like Morgan Stanley and American Express publicly shared their success stories within the past year.

Driving Innovation Through Big Data

In the big data world, where growing volumes of information, from a bigger variety of sources are created at ever growing velocities, the unenviable challenge to those collating information is to fully appreciate the bigger application of the sets of data they hold. Truly, the reality is that those making or collating data are not all the time bet-places in determining its widest apps.

It is perhaps not surprising that the marketing and sales director of BMW revealed to the North American International Auto Show that not only had the company received a considerable number of requests to use the collated data by its vehicle, but that these requests were declined ordinarily. This looks to have been prompted by privacy concerns and possible unintended consequences of making accessible customer data to third parties, where it could be vulnerable to unwanted exposure.

While privacy no doubt is an important consideration for large data analysis, any wholesale rejection to make data more available on the grounds of privacy risks, ignoring the intrinsic value for innovators. Of course, it should be remembered that privacy issues only arise to an extent that personal information is involved. Business must focus on the quality and nature of the data captured. Assessment should be made at the outset as to whether it’s strictly necessary for data that has a personal quality to it to be collated.

Driving Innovation Through Artificial Intelligence

Executives indicate that investments in AI and big data are starting to yield meaningful results. Almost three-fourths of surveyed executives report that their organizations now achieve measurable results from robots artificial intelligence and big data investments. Executives particularly report notable successes in initiatives to boost decision-making, via advanced analytics, with a 69 percent success rate and via reduction in expense, with a 60.9 percent success rate.

Moreover, business organizations are using AI investments to accelerate time-to-market for new services and products and to boost customer service.  As mainstream organizations look to the future, there is a growing consensus that artificial intelligence holds the key. With 93 percent executives identifying AI as the disruptive technology that their company invests in for the future, there seems to be common agreement that organizations should leverage cognitive technologies to be able to stay ahead in an increasingly disruptive period. AI investment could be expected to increase as companies position to compete in the future.

Those organizations that prove to be adept in developing and executing initiatives using AI and big data capabilities likely would be the ones that are best positioned to deflect the threats of data-driven, agile competitors in the decade ahead.

Convergence of AI and Big Data

The convergence of AI and big data emerge as the single most important development that’s shaping the future of how companies drive business value form their data as well as analytics capabilities. The availability of greater sources and volumes of data is, for the first time, letting capabilities in AI and machine learning, which remained dormant for decades because of lack of available data, limited sample sizes and inability to analyze massive data amounts in milliseconds. Digital capabilities moved data from batch to real-time, always-available online access.

While a lot of AI technologies have been around for decades, it’s only now that they are able to take advantage of sufficient size for meaningful results and learning. The ability of accessing big data volumes with ready access and agility is leading to a fast evolution in the application of machine learning and AI apps. Big data lets an environment that encourages discovery of data via iteration. As a result, businesses could experiment more, move quickly and learn faster. To put it differently, big data allows organizations to fail fast and to learn faster.

Big data analytics solutions is moving to a new maturity stage. One that promises even much greater industry disruption and business impact in the coming decade. As big data initiatives mature, enterprises now are combining the agility of big data processes with AI capabilities scale to accelerate business value delivery.

Reliable software development companies bring peace of mind and reliability when it comes to harnessing big data and AI systems. Technology and software service providers in Australia in particular cater to clients across all industry verticals and various sizes to help them make the most of the huge amounts of data gathered each and every day and to make use of AI intelligent systems.

About the Author

Ritesh Mehta works as a senior Technical Account Manager in a software development company named TatvaSoft Australia based in Melbourne. He specializes in Agile Scrum methodology, Marketing Ops (MRM) application development, SAAS & SOA application development, Offshore & Vendor team management. Also, he is knowledgeable and well-experienced in conducting business analysis, product development, team management and client relationship management. 


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Speak Your Mind



  1. Every time AI does something innovative, it always seems like a magic. And Ritesh, very nice article btw.
    Keep writing.


  2. Hey Ritesh,

    Amazing article and very informative.
    You have provided great insights on the importance of the AI and Big Data. That is true the combination of these two advanced technologies is doing wonders, in fact, IoT is not behind.
    There are many IOT Companies who provide a combination of these advancements.

    Artificial intelligence is the technology that allows computers to do things that were once only the domain of humans. AI can be roughly divided into two disciplines. These are machine learning and deep learning. Machine learning involves the creation of computers and software that can learn from data, and then apply that knowledge to new data sets. Deep learning creates neural networks, designed to resemble the human brain. Deep learning is used to process data such is sounds and images.

    AI doesn’t work without data. It consumes data in order to learn. Big data refers to the massive sets of data that are now available for this purpose. These sets of data can be analyzed by machines. This can reveal patterns and trends, and facilitate making future predictions. These data sets come from a variety of sources.

    AI isn’t new. It’s existed both as a concept and in action for decades. Until recently though, the lack of data stymied the growth of AI. Today, things have changed. There is simply an enormous amount of data available of all types. This includes images, audio, and text data.

    Think about it. Every time you fill out a form or even make a decision that’s recorded by a computer that information is potentially added to a big data set. Data can also come from IOT, Internet-based transactions, and other sources.

  3. Hello Ritesh Mehta
    Thanks for publishing such a informative article about future business innovation technologies AI Bigdata

  4. Great Article Ritesh, very informative, Keep posting such kind of valuable information.