The long-awaited benefits of artificial intelligence and big data have become so elaborate, that now over 97.2 percent of executives in Australia report that their organizations have started plans to launch AI and big data projects.
Among the executives who volunteered in the survey, 76.5 percent agree that extensive availability of quality data is what has empowered AI and more so cognitive initiatives within their businesses.
Correlation Between AI and Big Data
Now, experts and managers alike see a serious connection between big data and AI capabilities. However, credit goes to technological advancement that has made possible easy access to meaningful volumes of data, with the potential to feed algorithms that can in return understand patterns and behaviors.
Data plays the biggest role in building intelligent systems, that’s why many AI projects remained halted for decades, only to blossom back to life in the 21st century when data became sufficient.
Nonetheless, not fully dependent on data subsets as the main tool for analysis, enterprises converge big data, AI algorithms and computing power to invent real-time consumer solutions, not to mention new product offering as well as consumer credit approval. In fact, American Express and Morgan Stanly made public their success stories in relation to this application.
Driving Innovation Through Big Data
Since the discovery, big data has always been seen to harbor great potential although initially, it was not clear in the areas it would affect. Those making or gathering data don’t always specifically bet-places in deciding the widest application.
There have also been unending contentions on how and who should be given access to big data reservoirs in companies. For instance, in the case of BMW, the company revealed that it has received countless requests to access and use collated data linked to their cars but the requests get blocked in the name of privacy concerns.
Okay, to some extent it makes sense to cancel data access requests but realistically, continuous rejection to make factually safe information available for analysis and scientific use tends to underrate the efforts of innovators.
Ideally, privacy issues should be capped but only up to where personal information like bank details and the likes is involved. Realistic assessment needs to be undertaken to allow necessary data be accessible to innovators because that’s a great need for the future world.
Driving Innovation Through AI
In survey reports, executives have collectively come out clear that their organizations now record tangible and serious results from AI-driven robots and big data investments. Managers to be particular claim they’ve seen positive progress in such initiatives, which has translated to fast and accurate decision making, through advanced targeted analytics, with close to 70% success rate in expense reduction and over 60% in overall success rate.
In particular, business organizations use AI tools to accelerate marketing speed for new products and services being introduced into the market, as well as enhance customer service (using chat agents.)
In wider perspective experts seem to agree that the mainstream organizations stand to benefit more with AI in future. With over 90% of executives admitting that AI is the irresistible disruptive tech that their firms invest for the ”now seem inevitable” future. And those enterprises that will prove successful implementation of AI and big data potentials will be key in deflecting data related fears.
AI Meets Big Data
The convergence of this two technologies, AI and big data, is now seen as a crucial step in the future of business analytics. Even for the level that we are in right now, it is the immense channels and volume of data that is permitting the interesting AI and big data projects we hear about.
In fact, some machine learning projects still existed a few decades ago but were unable to blossom due to data unavailability. Thanks to digital capabilities which came to avail data to real-time from the batch, now it’s available to any potential AI developers on tap.
Ideally, we expected to see big data analytic solutions accelerate to maturity faster with AI in the picture. At the same time, artificial intelligence capabilities and innovation are expected to accelerate business value delivery to newer speed rates.
In other words, this will also depend on hardware and software companies, that is they should focus on newer systems, to be particular AI and data-based systems, to ensure their customers don’t lag behind the oncoming inevitable AI revolution.