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What AI Automation Can Bring to Your Organization

September 20, 2022 Digital Workplace
Siobhan Fagan
By Siobhan Fagan

While the technology is still evolving, AI is already being deployed across industries, with significant benefits to organizations that take the leap. The trend is moving at such speed, in fact, that the first steps in automating the development of AI models have been taken, which in turn is accelerating the creation of specialized AI models that can be applied to automate model development, training and deployment.

Gartner’s 2022 Hype Cycle for Emerging Technologies listed AI automation as one of the three emerging trends organizations should pay close attention to — alongside the enablement, evolution and expansion of immersive experiences, and the optimization of technologies delivery. 

The reason is simple according to Gartner: AI automation has the potential to be a real game-changer for business because it refocuses the role of humans in AI development, resulting in more accurate predictions and decisions as well as faster time to expected benefits.

What AI Automation Is

AI automation can be described as the ability to automate the process of making any software/hardware system more intelligent. Instead of the AI processes we see today, which involve a distinct series of steps and human development, AI automation looks at how the AI system as a whole operates, not just focusing on models making predictions but on automation of every aspect of the learning system, such that the system is continuous.

“In this respect, we are mirroring the human mind, which constantly learns from ongoing experience and not just one set of memories,” said Maya Mikhailov, co-founder and CEO of San Francisco-based machine learning platform provider SAVVI.

In a nutshell, AI automation is the automation of vastly complex and repetitive workflows lead by machine learning (ML) and AI. 

"Most important in AI automation is not how an intelligent system continues to auto-generate its own ML code and models but how it constantly selects and substitutes models as needed. This is done by architecting systems like those we have commonly associated with human intelligence. We define goals and controls but not the learning itself," she continued.

Mikhailov argues such a transition may require a mindset shift on the part of the organization. She notes it is a fundamentally different approach, moving from defining how learning will occur to defining desired outcomes and the regulatory, compliance and other requirements necessary for the organization in question.

Related Article: Gartner Identifies AI Automation as Key Enterprise Tech

What It Does

The promise of AI automation, said Mikhailov, is it will help organizations achieve their goals with AI and ML faster than before by minimizing the steps and time it takes for the system to learn and automatically adjust. It will also allow data science teams to play a more strategic role in designing for data outcomes rather than constantly tuning models.

According to Sheikh Fakhar Khalid, chief science officer at London-based digital twin technology company Sensat, successful AI automation means machines will not only be able to perform tasks more efficiently than humans, they also will have the ability to go beyond the limitation of human capabilities.

Various industries globally have already observed the benefits of AI automation, from increased productivity and efficiency in manufacturing, to rapid drug discovery and quality enhancement in healthcare, to increased accuracy of processes and confidence in the outputs of tasks such as fraud detection, said Khalid. Products and services powered by AI automation allow businesses to be more productive and adopt ML techniques that help improve processes and workflows with its continual use over time.

Construction companies have also recently started to use AI automation to track progress more efficiently and accurately. The technology enables them to optimize work schedules and improve workplace safety.

The biggest challenge for decision-makers in the civil infrastructure industry remains the holistic visibility and understanding of the management of large projects. Until now, this has been accomplished by experienced humans that have dedicated their careers in understanding the complexities of a successful construction project, but there is evidence that ML will eventually outclass any human knowledge in extracting patterns and detecting anomalies.

Related Article: Intelligent Process Automation Pushes the Boundaries of Business Process Automation

What AI Automation Means

Reasons for deploying AI automation are the same as the reasons for deploying AI, with the added advantage of quicker and more accurate AI model development.

AI is the most important component of intelligent automation, said Krzysztof Sopyła, head of machine learning and data engineering at python development company STX Next. Businesses can create a knowledge base and make predictions based on that data by analyzing organized and unstructured data using machine learning and sophisticated algorithms. Organizations can use AI automation to rapidly develop models that can analyze data to uncover trends and derive insights that will help them make better decisions. AI is already being used by businesses for security intrusion detection, process automation and even social media monitoring to assess brand perception.

From a business perspective, AI is often cited as the difference between getting ahead or falling behind in any given market. When used alongside appropriate technologies, such as intelligent automation, said Lou Bachenheimer, CTO of the Americas with Austin, Texas-based SS&C Blue Prism, a global developer of intelligent automation systems. AI can improve customer experience, help organizations adapt to rapidly changing market conditions, bring new products and services into effect more quickly and more efficiently, boost competitiveness and create a better working environment for employees.

The application of AI automation in the workplace is enabled through intelligent automation, Bachenheimer continued. By bringing together AI , ML, natural language processing (NLP), task mining and many more technologies under the domain of intelligent automation, businesses have all the critical elements needed to deliver transformative results within the workplace.

Related Article: Modeling Business With AI

How It's Evolving

AI has already begun transforming the digital workplace across industries, and it is expected that this process will accelerate in the near term. AI automation is one of the logical next steps in the evolution of AI, said Sopyła, and the impact will go beyond the inner workings of businesses to support economic growth and societal issues ranging from climate change to healthcare.

As one would expect, these technologies are also projected to change the nature of employment and the workplace. More human duties will be completed by machines, which will be able to undertake some tasks that are beyond the capabilities of humans. As a result, many professions will alter and thrive, while others will perish.

Because the widespread adoption of these technologies in the workplace relies on the ease of implementation as much as the advancement in the AI capabilities themselves, vendors working in these areas are working to ensure that businesses have the right technologies available to seamlessly connect people and digital workers and reengineer workplace processes for the benefit of employees and customers, all while being able to scale and orchestrate this technology across the business for maximum return, said Bachenheimer.

“Those organizations seizing this opportunity will possess an engine for sustainable growth, better customer service and competitive advantage,” he continued. “They’ll achieve this by working much faster, smarter and more efficiently while creating more opportunities and roles for human workers."

Related Article: Digital Transformation: What's Next?

A Better Tomorrow

Exponential technologies such as AI and automation help enable organizations re-engineer workflows, using vast amounts of proprietary data to create platform-centric business models that can help companies emerge as incumbent disruptors in their industries said Jonathan Wright, managing partner and service line leader at Armonk, New York-based IBM Consulting. Through real-time insights, scenario planning and market information, AI automation technologies help drive continuous improvement.

“Businesses that use intelligent automation to build these capabilities are poised to address today’s unforeseen workforce dislocation, supply chain challenges and customer service disruptions,” he said. In addition, automation can help retailers use data to optimize omni-channel fulfillment and logistics. That means reducing shipping times, carbon emissions and waste. With a more holistic approach, emerging technologies like AI and automation can be integrated to deliver greater efficiencies, enhanced resilience and new ways of working.


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