Six Skills Separating Intelligent AI from Basic Automation 

Shutterstock / Linda Bucklin

Managing the modern customer experience today means most businesses are implementing, or at least investigating, an automated, digital, workforce. Since coming to market almost a decade ago, RPA (robotic process automation) has become more than just the automation of repetitive tasks and legacy applications. An enterprise-level RPA platform supercharges digital transformation by acting as the processing constant between the changing modern and legacy application environment. It connects technologies of the past to those of the future.

What does this mean for IT teams? An effective enterprise RPA platform streamlines digital transformation by removing barriers to adoption, enabling swapping in and out of technologies and freeing up IT resources to focus on the highest priorities.

At the heart of implementing a good digital strategy is data – but the trouble is, it comes to the organization in varying formats. Also, many business processes are fragmented, handled by various call and service centers, leaving the knowledge and procedures required to form the backbone of digital strategy undocumented and manually executed. As systems and processes are transformed over time, the challenge of data accessibility and system sustainability is significant.

The latest and most advanced RPA solutions deliver a smarter, AI-powered robotic workforce. The selection of the correct solution is paramount to maintaining the necessary controls and security that IT teams require.

The following six skills are critical for ensuring that software robots, or digital workers, have “human-like” abilities necessary to work effectively alongside human counterparts — dramatically expanding horizons for autonomy, process scope, transaction speed, revenue gains and cost savings:

• Knowledge & Insight enables software robots to intelligently interpret information from different data sources (structured and unstructured) and deliver helpful insights using AI techniques, such as language translation, entity classification and sentiment analysis.

This means digital workers can communicate in the language specific to a business and can drive decisions based on complex data structures or external knowledge bases, in any language. Knowledge & insights can be leveraged to identify greater risk visibility by compiling risk data that is siloed in various systems across an enterprise in real-time to expose and allow stakeholders to take action on potential threats. It can also be used to quickly gather customer data and reduce customer request processing times and improve satisfaction levels.

• Visual Perception lets digital workers read, understand and contextualize information visually.

Digital workers can directly integrate with applications through a GUI as well as interact using computer vision (through surface automation) to read documents and understand content within images. This skill can be used to scan and understand the context of job lists online and smartly optimize labor hours. It can also identify the application fields that would qualify or disqualify someone for a loan — creating a more efficient application process.

• Planning & Sequencing is classified as one of the “executive functions” of the brain that helps with the formulation and selection of a sequence of actions to achieve a desired goal. A platform with this ability should cope with complex and secure orchestration with minimum human intervention.

This skill enables digital workers to identify optimal times to conduct tasks and schedule workloads accordingly. Digital workers can also auto-scale on-demand to achieve optimal productivity. All tasks are fully audited to adhere to enterprise security and compliance standards.

In real-world applications, planning & sequencing is used to coordinate payments and deposits for the finance team and to automatically scale digital workers to meet demand peaks and valleys.

• Collaboration is the ability of digital workers to complete tasks in collaboration with people and systems, enabling them to work within the modern ecosystem of digital channels.

With this skill, digital workers can communicate with staff, systems and each other using any modern communication platform without resorting to “digital duct tape” or RDA.

There are many applications for the collaboration skill: software robots can be deployed to communicate with customers and resolve their requests faster and with more engagement. It is also used to communicate data from one system to another.

• Problem Solving helps digital workers use both deterministic, rules-based workflow and probabilistic or predictive approaches via machine learning algorithms.

With this skill, digital workers can work within complex rules and leverage machine learning models to cope with non-rules-based decisions. Organizations can benefit from expanded automation scope, improved productivity levels and continuous process optimization.

• Learning provides intelligent automation platforms with the skills to take low confidence outcomes and optimize their machine learning algorithms.

Digital workers must be able to adapt to changes in data or patterns. Through advanced analytics and machine learning, they can be trained to cope with non-deterministic or predictive decisions to monitor compliance risk in robot-to-human conversations — even as they’re happening – to avoid potential risks in real time.

The future of the digitized workplace will involve a blending of human and digital labor, when a digital worker is just another team member interacting with customers, accepting tasks, moving work autonomously between human and digital workers. A digital workforce can learn from observing routine tasks and will give access to (and insight from) data across the IoT, modern and legacy systems of record. Far from a bleak, dystopian future where robots replace humans, it is one in which your business can grow organically and efficiently by connecting the IT fabric of your entire organization and empowering your workforce to trust and rely on digital colleagues by bringing to bear the skills required to augment and enhance human abilities.

Colin Redbond is head of technology strategy for Blue Prism.