PWC Predicts Six AI Priorities for 2019

by Tech Mainstream Staff


March 6, 2019


PWC Predicts Six AI Priorities for 2019


PWC recently released a study determining "six AI priorities you can’t afford to ignore." Businesses should take heed to PWC's advice since it will most likely guarantee successful AI integration: "Those companies focusing their efforts in the following six key areas will be far ahead of other businesses this time next year." The study queried 1,000 US business executives at companies to assess their current AI integration status. 20% said their "organizations plan to implement AI enterprise-wide in 2019."

Why is AI integration so important for business success? It is estimated by 2030 that AI implementation will contribute $15.7 trillion to the global economy- not exactly a fact for companies to ignore. 

The first step for companies to excel in is "AI is Structure: Organize for ROI and momentum." Businesses want reusable AI building blocks to be used across organizations to simplify tasks and help increase ROI: "If done right, developing an AI model for one specific task can enhance an existing process or solve a well-defined business problem, while simultaneously creating the potential to scale to other parts of the enterprise." The right AI foundation is also critical for effective AI integration. It requires a team that includes individuals who have business, IT and specialized AI skills and are representive of all parts of your organization.

"Workforce: Teach AI citizens and specialists to work together" involves a workforce consisting of three levels of AI-savvy employees, citizen users, citizen developers, data scientists, and provides ways for all three to work together successfully. Identifying new job skills and roles is part of solving the AI equation.

"Trust: Make AI responsible in all its dimensions" is a idea that determines how AI affects privacy, cybersecurity, employment, inequality and the environment concerns. Therefore executives top priority for 2019 is if AI systems are considered trustworthy. There are six criteria for guaranteeing this goal: Fairness, Interpretability, Robustness and security, Governance and System ethics.

"Data: Locate and label to teach the machines," a fourth AI priority explains the importance of creating the data sets needed for training and the necessity of labeling the data . One of the top AI-related data priorities for 2019 is to combine AI and analytics systems to obtain business insights from data: "AI can be used with data and analytics to better manage risk, help employees make better decisions, automate customer operations and more." An AI CoE ensures creation of usable, labeled data sets for AI use: "For those data sets to help support AI across the enterprise (those consumers may interact with more than one business line), you’ll need standards for labeling them consistently."

"Reinvention: Monetize AI through personalization and higher quality," in a nutshell is that "the majority of AI’s economic impact will come from the consumption side, through higher-quality, more personalized and more data-driven products and services. Healthcare, retail and automotive could see the most immediate benefits, according to our analysis of more than 300 AI use cases."

"Convergence: Combine AI with analytics, the IoT and more," a top AI challenge for 2019, approximately 36% of the executives surveyed agreed: "Helping advanced, predictive and streaming analytics further evolve with AI is a common priority. This convergence can make new data-driven business models more powerful."

A useful PWC ai infographic is available for a pictorial ai explanation.

 

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Tech Definitions in the News

Augmented Reality is an enhanced version of reality where live direct or indirect views of physical real-world environments are augmented with superimposed computer-generated images over a user’s view of the real-world, thus enhancing one’s current perception of reality.

Source: https://www.realitytechnologies.com/ augmented-reality/

Chatbot is a piece of software that interacts with users in a conversational way.

Source: https://snatchbot.me/insight/250/ intelligent-chatbots


Deep Learning is a new area of Machine Learning research, which has been introduced with the objective of moving Machine Learning closer to one of its original goals: Artificial Intelligence.

Source: http://deeplearning.net/


DevOps is a set of software development practices that combines software development (Dev) and information technology operations (Ops) to shorten the systems development life cycle while delivering features, fixes, and updates frequently in close alignment with business objectives. Different disciplines collaborate, making quality everyone's job.

Source: https://en.wikipedia.org/wiki/DevOps


Docker is a tool designed to make it easier to create, deploy, and run applications by using containers. Containers allow a developer to package up an application with all of the parts it needs, such as libraries and other dependencies, and ship it all out as one package.

Source: https://opensource.com/resources/what-docker


Hybrid Cloud is a computing environment that combines a public cloud and a private cloud by allowing data and applications to be shared between them.

Source: https://azure.microsoft.com/en-us/overview/what-is-hybrid-cloud-computing/


Kubernetes (k8s) is an open-source system for automating deployment, scaling, and management of containerized applications.

Source: https://kubernetes.io/blog/



WWW2 and WWW3 (k8s) are hostnames or subdomains, typically used to identify a series of closely related websites within a domain, such as www.example.com, www2.example.com, and www3.example.com; the series may be continued with additional numbers: WWW4, WWW5, WWW6 etc. 

Source: https://en.wikipedia.org/wiki/WWW2


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