This Year’s Top 3 Predictions for AI, Big Data and Analytics

This Year’s Top 3 Predictions for AI, Big Data and Analytics

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Artificial intelligence, data and analytics are changing the world of business. Learning how they’re going to impact the future is critical for your career, no matter which industry you’re in.

So, what exactly does the future hold for your career? We spoke with two tech evangelists to find out.

Peter Vakkas is the Technology Lead for Accenture Australia & New Zealand. His role involves embedding modern technology and engineering practices into an enterprise. His career has been focused on technology architecture, and leveraging platforms like SAP & Oracle to help grow his clients’ businesses.

Pablo Quintero is a Business Analyst at AgriDigital. He is passionate about creating phenomenal customer experiences with technology. He works in product development in the Agritech space, and runs his own startup creating efficiencies in the sharing economy.

Vakkas and Quintero predict that three trends will gain traction in the next year:

Trend 1: A move towards verifiable, quality data

With business decisions (at tech startups in particular) becoming heavily data driven, the quality of data is paramount. One bad decision from inaccurate or unverified data could threaten the existence of an entire tech enterprise. Addressing this vulnerability is critical to success.

“Companies don’t need to accept the risks of poor data veracity,” suggests Vakkas. He advises managing this risk by building confidence in:

  1. Data provenance: Verifying the history of data throughout its life cycle
  2. Data context: Considering the circumstances around the data’s use
  3. Data integrity: Securing and maintaining data

Vakkas advises every business to build a data intelligence practice, drawing from existing data science and cybersecurity capabilities. By ensuring that only the right data is being used, while being vigilant about any potential manipulation by stakeholders, the sanctity of data can be protected.

This directive has the potential to present a lot of opportunities in the data quality assurance domain, so if you’re a current or future auditor or QA tester, your professional future looks bright!

Quintero reiterates the importance of quality and interpretability of data. According to him, “Everything begins with the data collected.” He believes companies will spend a lot of time cleaning and sorting data, while adopting simpler models to analyse and interpret it.

The key career insight Quintero offers is to be able to “close the gap between data science and management.” Being able to collect data is only half the battle; translating it into tangible insights is what makes you a truly valuable asset to your company.

Trend 2: The evolution of artificial intelligence and human/machine interaction

Vakkas believes that deploying AI is no longer just about programming it to perform a specific task. It’s now about “raising it to act as a responsible representative of the business and a contributing member of society.”

As AI is now being designed to collaborate with people and make their jobs easier, it’s essential that AI robots are able to explain their actions in a way that’s understandable to humans. Companies should also think about how to allocate responsibility and liability for the actions of their AI tech.

AI will take on a lot of the grunt work, allowing humans to focus on higher value and more creative work. Chatbots are a live example of this phenomenon, as they understand, interpret and respond to large volumes of customer enquiries, facilitating better and more efficient customer service.

Vakkas believes these advancements in human-machine interactions could see three new roles potentially emerging in the future: trainers, explainers and sustainers.

“Trainers could help computers learn to recognise faces, for instance. Explainers will interpret the results of algorithms to improve accountability for their decisions, helping strengthen the confidence of customers and workforces in AI powered processes. And sustainers will ensure intelligent systems stay true to their original goals, without crossing ethical lines or reinforcing bias,” says Vakkas.

His view is that the most important skills will be the ones that machines can’t perform, pointing to the necessity of human judgement to make decisions when AI-powered processes fail to act. This requires an understanding of the limitations of AI, and knowing when human intervention is needed.

Another important skill, according to Vakkas, is being able to train machines in specific processes while observing ethics and integrity. The ability to examine AI systems to derive insights from the data gathered will also be an immensely valuable human skill to possess in the future.

At AgriDigital, AI helps lead customers down specific pathways, depending on how they use the platform. Quintero knows that clearly presenting these pathways allows users to complete work quickly, leaving them more time for other activities.

Understanding possible human interactions and providing a computer-generated pathway in response to them will become an invaluable skill as AI tech continues to develop. Being able to imagine all possible scenarios will allow you to craft successful human-machine interactions.

Trend 3: Advances in the Internet of Things (IoT) and the Internet of Thinking

As those in the tech space already know, the Internet of Things (IoT) refers to the network of physical devices, vehicles, home appliances and other items embedded with software, sensors, actuators, and connectivity which enables them to connect and exchange data over the net. The future of IoT, to our experts at least, is bringing intelligent environments to life through dynamic immersive experiences.

Vakkas talks about the ‘internet of thinking’, which involves edge network computing. This allows data collected by IoT devices to be processed nearby in real time, rather than sending it to the cloud. This necessitates a more sophisticated interaction between hardware, software and internet solutions. He adds that “cloud processing remains appealing for high-value learning, predictions, AI-model generation and storage in situations that are not time critical. But for real-time intelligent action, data processing must happen at the edge of networks where the event is occurring.”

If you’re excited by creating amazing virtual and physical experiences for people, you’ll need to keep on top of trends in IoT devices, and understand their ability to create intelligent environments. With true understanding and ever-evolving tech comes limitless possibilities.

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