Eight Top artificial intelligence and analytics trends for 2019

Srinivasa Vegi Srinivasa Vegi
December 27, 2018 AI & Machine Learning

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Forward-looking organizations can’t afford to overlook the emerging trends in artificial intelligence and analytics in 2019.  8 Most Important AI and Analytics Trends for 2019 unpack the driving forces in AI for the New Year. 

Artificial intelligence will deliver approximately $2 trillion worth of business value worldwide over the next year through the use of advanced computing algorithms that identify and optimize business insights that humans cannot spot. Companies that fail to adopt AI will lose out. Some industries may even be wiped out.

Be on the look-out for these hot trends

1) AI and Analytics Merger

Applying AI algorithms to analytics will prove transformative but the complex merger requires a roadmap.

Analytics dashboarding and business intelligence already require a sophisticated command of information technology, mathematics and statistics. AI and machine learning algorithms can automate and optimize analytics processes, creating transformative business insights.

Applying AI algorithms to analytics insights from chatbots, ecommerce platforms and other sources can elevate the customer experience. Insights gleaned there can lay the groundwork for using AI and analytics across the business.

2) Decision Automation 

Greater AI and machine learning in enterprise resource planning will empower smarter process changes, minus the human intervention, to drive cost savings.

Enterprises use advanced applications for enterprise resource planning (ERP), customer relationship management (CRM) and other mission-critical functions. Updates to these platforms will fold in more AI and machine learning capability in 2019, built around the principle of decision automation.

3) Digital Twins

Digital replicas of physical processes, like production lines, let humans interact with IoT sensors automating asset management.

AI and analytics are crucial to the development of digital twins — computerized facsimiles of physical processes like a production line in a factory. The rise of digital twins in 2019 means more companies will generate predictive insights that allow them to anticipate problems and fix them before breakdowns send costs spiraling.

4) Edge Computing

Data center AI and analytics will deliver more real-time intelligence, anticipating problems and implementing fixes before costly breakdowns.

As more digital twins enable real-time modeling of production environments in 2019, organizations in remote areas will need high-powered processors nearby. A coal mine operator, for instance, can use a digital twin to detect a buildup of gases and avoid a catastrophic explosion. But if the mine’s IT operation relies on remote servers hundreds of miles away, a small data lag could be a major disaster. The solution lies in edge computing — deploying powerful data center technologies closer to end users.

5) Mixed Reality

The combination of elements of virtual and augmented reality with data analytics will grow in 2019 but will accelerate even faster over the next two or three years.

Mixed reality combines elements of virtual- and augmented-reality technologies. It allows a furniture brand, for example, to show people what a new sofa looks like in their home — no showroom required. And, of course, all of these technologies provide massive reams of data for analytics and AI.

6) Blockchain Boom 

Blockchain uses a shared digital ledger that’s impossible for hackers to breach, making it one of the most-watched technologies of 2019.

Blockchain relies on a shared digital ledger that’s functionally impossible for hackers to break into, making it attractive for organizations that protect sensitive data. The core challenge is that blockchain’s ledger requires complex interactions and processes that are time-consuming or labor-intensive. These complications create a strong incentive to deploy AI and analytics to accelerate blockchain operations.

7) Cloud Maturity

Thanks to advances in security, more organizations will embrace the cloud generating huge new datasets to inform advanced machine learning.

Organizations with rigid compliance rules like HIPAA can implement hybrid clouds. Storing apps, workloads and data in the cloud generates vast datasets that are the prerequisite for advanced machine language functions.

8) Full-Stack Engineers

Companies will scramble to hire full-stack engineers with AI and analytics skills making this one of the hottest careers of 2019!

Merging AI and analytics puts data science at the forefront of IT operations. In years past, experts in data ETL (extraction, transformation and loading) worked in a separate department. In 2019, IT departments will face more pressure to integrate data ETL into their AI and analytics operations.

Organizations looking to embrace AI and analytics trends in 2019 should start with a well-thought-out roadmap. There’s no need to adopt a big-bang approach.

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