The Fourth Industrial Revolution, Future of Work and the Rise of Content IQ Skills

According to the World Economic Forum, we are currently in the midst of the Fourth Industrial Revolution, where technology is merging the physical, digital and biological worlds, and creating great promise and peril simultaneously. It brings fresh challenges for identifying job fit and matching individuals to opportunities, and is requiring large-scale changes to job and skill demand. In fact, by 2022, the core skills required to perform most roles will change by 42 percent — greatly impacting the future of work.

Automation and artificial intelligence (AI) are key drivers in the future of work. Over the next 10 to 15 years, the adoption of automation and AI technologies will transform the workplace as people increasingly interact with smarter machines. Research by the Mckinsey Global Institute states automation is accelerating the new digital workplace and shifting workforce skills to mandate both basic digital skills and advanced technological skills such as programming. Workers in all corporate functions are expected to improve their digital literacy over the next three years, especially employees in functions including sourcing, procurement, and supply chain management.

Yet, the research found there is still demand for social and emotional skills such as leadership and managing others – skills machines aren’t able to master. Demand for higher cognitive skills will also grow, especially creativity. In aggregate, between 2016 and 2030, demand for these social and emotional skills will grow across all industries by 26 percent in the United States and by 22 percent in Europe.

Amazon Alexa-like skills for the enterprise

As automation, AI and work converge in the enterprise, new technologies are emerging that address the shifting skillset of enterprise workers and how they are consuming technology. We’ve learned from advances in consumer technology the need to make technology easier to consume. One of the most applicable to the enterprise is the concept of “skills”; for example, introducing new skills to Amazon Alexa.

Alexa provides a set of built-in capabilities, referred to as skills. For example, Alexa’s abilities include playing music from multiple providers, answering questions, providing weather forecasts, and querying Wikipedia. The Alexa Skills Kit lets you teach Alexa new skills. Alexa skills are apps that give Alexa even more abilities, letting it speak to more devices and websites. Customers can access these new abilities by asking Alexa questions or making requests. You can build skills that provide users with many different types of abilities, and there is now a whole world of third-party skills that can make Alexa even more useful. In fact, there are currently more than 70,000 skills.

Within the enterprise, this same concept of skills is being applied to understanding and processing content. The volume and complexity of content continues to grow exponentially. Organizations contain valuable information within CRMs, BPM, ERPs and other process management systems waiting to be more useful. To leverage the value in that information, businesses need to automatically extract and understand all relevant data and integrate that information into every aspect of their business. Robotic process automation (RPA), a fast-growing technology, is great for automating tasks and delivering information into systems. It’s why the RPA market has skyrocketed: Statista believes that the RPA industry will be worth $3.1 billion this year and $4.9 billion by 2020. However, it has limitations to being able to identify and process content.

The opportunities and challenges associated with RPA have led to organizations establishing Centers of Excellence, where business and IT take ownership of their AI strategy. And, this is where intelligent capture has become a key part of a successful RPA strategy. RPA is being used with intelligent capture, machine learning, and other AI technologies to automate a wide array of repetitive tasks along with the handling and accessing of both structured and unstructured content. It can be rapidly deployed, the bots are easy to configure, and once in place, they perform work just like humans. Because of this, RPA is a fresh alternative to big IT projects that take months or even years to implement. When applied to the right use cases, it provides a quick return on investment and provides an agile environment for businesses to reduce costs, meet compliance mandates and automate work in a wide variety of tasks. By using these technologies together, organizations can connect multiple systems and data sources to understand content, and in effect, enable it to be more useful to the organization.

However, RPA bots need skills to easily drive intelligence from capture technologies.

The rise of content IQ skills

Intelligent capture is shifting how organizations use and consume data. It has evolved from back office scanning to connecting new digital technologies such as RPA and AI. This evolution and how the technology is being consumed within the context of automation tools has led to content IQ.

Content IQ is defined as a class of enabling technologies that help digital workforces, or RPA robots, understand and create meaning from enterprise content. Content IQ provides the ability to automatically extract all relevant information from documents and breaks down processing of content into easy-to-use-and-consume technology that can be leveraged directly within an automation solution like RPA, targeting activities and skills required by the digital worker to solve specific business problems.

RPA vs content IQ

In the context of content IQ, organizations can apply intelligence to their content and connect it to their business processes. It brings several technologies together including OCR, machine learning, and other AI technology to create structured information from unstructured content using the metadata within text, images, documents and communications (e.g. email). AI synthesizes the content captured and applies real-time, work-level data, to generate more than just process statistics and operational analytics that measure the effectiveness of business processes. It allows the structure of the content and its data to be easily connected to the robotic process and adapt to the many variations of a document.

Most importantly, it provides a means for process improvement that can act as a transformative agent to provide businesses and processes with previously unimagined ways to enhance the work environment, customer interactions, and the way today’s companies do business.

Content IQ skills and the future of work

As the future of work evolves, we are seeing a shift in users of content IQ skills toward Centers of Excellence and business analysts rather than IT users. According to the Forrester report “Predictions 2019: Artificial Intelligence,” more than 40 percent of enterprises will create digital workers by combining AI with RPA. This adoption will accelerate the business analyst role, as they have the digital literacy to work alongside digital workers and the business acumen to know, understand and manage content IQ skills.

A major value proposition of content IQ skills is they enable enterprises to automate content-based processes without requiring users to be tech experts. It makes content-centric processes easier to set up and configure with out-of-the-box core skills and advanced cognitive skills that make robots smarter.

Content IQ skills are categorized into two levels that users can easily configure: core cognitive and advanced cognitive skills that work with many “host” automation platforms such as RPA, BPM, ECM, ERP and others. Core cognitive skills perform activities that include OCR, document classification and data extraction, while advanced cognitive skills leverage the core skills to perform specific tasks unique to a document type and business use case, such as processing supporting lending documents, an insurance claim or a bill of lading.

Content IQ skills work in four simple steps that are intuitive to business users and IT alike:

Design a skill: use out-of-the-box skills or build an advanced skill using activities.

Set up and train skills: train skills based on one or many document types and variations.

Publish and execute: publish skills to make them discoverable to an automation platform.

Continuous learning: build new cognitive learning models for classification and extraction.

The entire process can be completed within 30 minutes or less.

Benefits of content IQ

Many types of processes can benefit from content IQ.

Insurance:
The opportunities for applying content IQ are everywhere. For example, insurance companies can take in content as part of insurance claims. Documents are identified, and data is extracted, turned into meaningful information and connected into a robotic process for analysis and processing.

Banking:
Being able to understand content can also help banks deliver a seamless mobile customer experience as part of a lending process by capturing documents provided by the borrower – including pay stubs, utility bills, W-2, and other supporting documentation, be it structured or unstructured.

Transportation and logistics:
Content IQ can deliver a new set of digital workers with the right skills to identify and process shipping instructions, waybills, proof of delivery, and invoices associated with a load, providing transparency and awareness of when goods are delivered and accelerating the billing process.

Cross industry:
Content IQ can also help all businesses in streamlining their accounting functions by automating and evaluating purchase orders, receipt of delivery documentation, payables, invoicing and receivables. This ability can save corporations and government agencies both time and money when dealing with their back-office functions.

The future of the future of work

We can expect many fields to increasingly add AI technologies to automation and more people working alongside digital workers as more companies acknowledge their impact in the Fourth Industrial Revolution and the consequences to the future of work. It’s a reality more organizations are embracing – more than half of the companies surveyed by research firm Horses for Sources believe instituting an intelligent automation strategy, such as content IQ for the digital workforce, will lead to improved business operations.

However, we can rest assured that human employees will continue to be vital to businesses despite AI and automation replacing some aspects of their roles. The new skills AI delivers should be viewed as a job redistributor, one that will augment people’s career trajectories. Most U.S. workers want to delegate 48 percent of their tasks to AI anyway, and a majority of people are optimistic about AI’s impact on the workforce, while 65 percent of people believe technology like AI and RPA can increase the number of jobs available. Additionally, freeing employees from time-consuming work allows them to reclaim their time and strike a better life-work balance.

Content IQ skills are in a nascent stage and the number of skills currently available is expected to triple over the next two years as companies build more advanced cognitive skills. Automated systems and robotics will inevitably face bottlenecks and hiccups. Humans will need to be on-hand and have knowledge of these duties and the automated systems now performing them in order to keep business operations running smooth.