How AI Reinforces a Next Generation of Business Processes

Discover the enormous potential of AI to power digital transformation toward the next generation of business process technology.

Over the past several months, artificial intelligence (AI) has revealed its power and potential to the general public with the rise of generative AI tools like ChatGPT and Stable Diffusion. Writing poems and generating artwork have never been closer to what human creativity can come up with. At the same time, organizations are suffering from painful labor shortages as automation and efficiency emerge as crucial factors for the future of business.

Even though AI has powered our web search, smartphones, and social media and driven digital experiences for years, it all happened under the hood until ChatGPT came along. A larger public can now more directly interact with these AI tools fueling the imagination of how this technology can impact businesses and our society. In this blog, we’ll focus on how AI can help power digital transformation toward the next generation of process technology.

Business Processes and Digital Transformation

A business process is a collection of logically related activities or tasks performed by a combination of people and equipment to achieve a business goal. Business processes are everywhere, and we interact with or are affected by them when we withdraw money from an ATM, pay our taxes, buy goods online, are at work, and more. They’re the operational muscles of organizations, helping them realize their strategic and operational business goals. Ultimately, an organization’s success largely depends on its business processes’ productivity and efficiency.

Digital transformation refers to using and incorporating digital equipment (e.g., cloud computing) into business operations, products, and services. Businesses typically undergo digital transformation to improve the productivity and efficiency of their workforce and provide better customer service and experience.

Although the term digital transformation has gained significant traction over the last decade, it has positively impacted business processes since as far back as the 50s and 60s (based on the definition above). That was when the first commercial computers started supporting business operations and tasks in the insurance and military sector. Since the late 90s, business processes have undergone more transformative changes. With workflow and business process management systems powered by cloud and services computing, business process automation emerged as core technologies for supporting business operations.

These technologies successfully helped pave the way for the digital transformation of business processes, increase service quality, and improve service delivery. But their contribution, for the most part, gravitated less toward the actual automation of processes and focused more on computer-mediated operationalization.

Next Generation of Process Technology: Cognitively Augmented Business Processes

Cognitively augmented business processes are process technologies that leverage AI to power and enhance process participants’ cognitive abilities to improve the productivity and efficiency of organizational business processes. Cognitive augmentation within business processes can happen in many ways. For instance, it can involve virtual assistants that interact with end customers to provide support, automatic processing of (possibly hand-written) claims for an insurance company, fraud detection, and prevention in financial institutions, auto-marking of exams in educational processes, deciding on the next best action to take within a workflow, etc.

The unprecedented recent breakthroughs in AI (computer vision, natural language processing, speech recognition, etc.) now make state-of-the-art cognitive augmentation possible. These areas are akin to human abilities that previously required a manual effort.

What drives cognitively augmented business processes?

AI’s growing capabilities include cognitive tasks that previously required a human presence. Its unprecedented and fast-paced improvement in performance is the principal driver of cognitively augmented business processes. Such tasks include text summarization, automatic email replies, customer support via virtual assistants, automation of tasks and workflows, real-time support, and information retrieval for assisting knowledge workers.

Another key driver of cognitively augmented business processes is the ever-increasing amount and variety of the so-called cognitive services available in the Amazon Web Services (AWS), Azure, and Google marketplaces. These advanced AI-powered services are readily available through APIs and can integrate into an organization’s business process and workflow management systems. Examples include Azure’s cognitive services for speech (speech-to-text, speaker recognition), language (entity recognition, sentiment analysis), decision (anomaly detection, content safety), and vision (image recognition, optical character recognition (OCR)).

Figure 1. The ecosystem of cognitively-augmented business processes (extended from Barukh et al. 2021)

What are the benefits of cognitively augmented business processes?

The ultimate aim of cognitively augmented business processes is to combine the best of human and machine abilities to help organizations unlock new opportunities, improve their operations, and achieve competitive advantage. Other key benefits for organizations include:

• Improved productivity and efficiency: Cognitive technologies can help boost worker productivity by enhancing their performance in tedious, repetitive, and lengthy tasks. Tasks can sometimes be fully automated, allowing workers to focus on higher-value activities.
• Higher responsiveness: With the ability of cognitive technologies to partly or fully automate tasks, critical process tasks can result in faster response times, thus reducing end-to-end process turnaround time.
• Scalability and adaptability: Cognitive services can handle large volumes of data and events that need processing within organizational workflows. Cloud computing technologies can quickly scale and adapt based on demand, benefiting workflows that must adapt swiftly and (re-)scale throughout their lifespan.
• Enhanced decision-making: Cognitively augmented business processes can help boost the performance of knowledge workers by allowing them to make faster and more accurate decisions that lead to improved and competitive business outcomes.

Thus, cognitive augmentation of business processes harnesses the power of AI and human intelligence to put it to work and goes a long way toward improving and optimizing business operations in an increasingly competitive digital transformation landscape.

What are the challenges of cognitively augmented business processes?

New technologies bring together new challenges. Many of the challenges listed below in the context of cognitively augmented business processes also apply to digital transformation in general. Here are some of these challenges:

• Limited in-house expertise: This refers to a lack of the necessary skills, knowledge, and ability to assess, design, engineer, implement, and integrate cognitive technologies into an organization’s process tech stack. Cognitive technologies typically require skills in AI, machine learning, data science, and related fields.
• Low digital culture: Like any other digital transformation initiative, cognitive augmentation of business processes is more likely to thrive in environments with well-established digital cultures. These environments are typically more prone to embracing innovation, lowering entry barriers for new digital tech.
• Poor management support: Often stems from an insufficient understanding of the technology and its implications for the organization in highly competitive markets. Symptoms include a need for the necessary guidance, resources, and assistance for the teams that champion and drive these initiatives.
• Immature organizational culture about AI tech: AI tech remained largely obscure and unknown to the general public until recently. Therefore, we often need better awareness of this technology and how it can help businesses. In some cases, people have also developed a fear of job displacement.
• Regulatory and legislative changes: Just like other technologies that deal with data (personal, organizational, governmental), cognitive technologies can be subject to current and future regulations. In particular, there are concerns regarding using personal information for training the AI models that operate behind cognitive services.

Future Expectations

Similar to previous waves, such as workflow automation and services computing, organizations have realized the value of this technology and the competitive advantages of effectively and responsibly integrating it into their process tech stack.

AI-powered and cognitively-augmented business processes are the next big wave in process technology. And, as opposed to past promises of “automating everything” in previous waves, we remain optimistic that this new approach of deeply partnering human intelligence with technology in a symbiotic relationship will lead to a fundamentally better digital transformation of organizations.

Original post here.

Authored by Carlos Rodríguez:

Carlos Rodríguez is a project leader and collaborator in the data space with over 15 years of experience applying data science research and innovation across multiple domains in the software industry. He’s applied this work to business process management systems, compliance, crowdsourcing, service-oriented computing, software security vulnerability management, and EdTech, among other domains.