Transforming Value Creation: How GenAI and Human-Machine Collaboration Are Redefining Efficiency

Value Creation is the use of imagination or original ideas to create something new.

Today, frontier technologies are forcing organizations to reassess ideas around what constitutes the creation of value. Augmentation is building human-machine collaboration by combining the strengths of both entities to enhance value creation in various domains. This collaboration leads to improved productivity, efficiency, and innovation. Also, the growing interest in ESG metrics and driving toward the common good means rethinking the role that business should play in society.

As is the case in problem-solving and decision-making, a focal point of value creation today is GenAI with algorithms capable of generating seemingly new, realistic content from training data. The most powerful generative AI algorithms are built on top of models trained on vast data to identify underlying patterns for a wide range of tasks.

GenAI is giving rise to an entire value proposition that includes building more efficient workflows for knowledge workers by automating and simplifying time-intensive processes through understanding and extracting insights from unstructured data. This is resulting in an entire business ecosystem, from hardware providers to application builders, that will help bring its potential for all classes of workers to fruition. Employees can enhance their performance in these higher-value domains with AI-powered virtual assistants while availing themselves of a human-AI co-creation framework that will maximize system flexibility and enhance creative outcomes. This branch of AI demonstrates a capacity not only to learn, predict, and infer, but also to create content that can be delivered in multiple modalities, including text, images, videos, and 3-D representations.

Some use cases are created by incorporating semantic search into basic chatbots and workflows, which can enable frontline teams to access information, create responses, and resolve requests much more quickly. Also, by automating repetitive or mundane aspects of coding and data engineering, GenAI is streamlining workflows and driving productivity for software and data engineers alike.

The employees who are closest to a process are the ones who can usually describe how it can be improved to add value. These workers can point to symptoms, which can help to map out the end-to-end improvement opportunities. Other subject matter experts can provide tools, education, support, and ongoing monitoring for everyone whose job is touched by new automation. Ultimately, the goal is to develop a system where automation manages the rote, repetitive, and rules-based aspects of the job, freeing the employee to do work that adds real value.

Steps to Realizing New Value

There are several diverse ways to augment the workforce and create new value in today’s organization, including shifting innovation to the edges of the organization to build ecosystems or networks that leverage digital technology for the benefit of the consumer and pave the way to multiple streams of revenue. Edges are powerful sources of value because they are places of potential and friction, where traditional products and practices are no longer adequate to address unmet needs or unexploited potential.
The organization then needs to test potential solutions for augmenting workers across multiple business units and use cases. This approach provides an opportunity to explore possible avenues for value creation by enabling the testing of different scenarios until the most impactful resolutions are identified. Along with worker augmentation, business leaders must strive to redesign their organizations for speed, accelerating productivity improvements, reshaping their portfolio, innovating new business models, and reallocating constrained resources.

Businesses using generative AI today are better placed to create new value by increasing productivity, institutionalizing knowledge, and pursuing novel avenues of research and development. As companies, employees, and customers become more familiar with applications based on this AI technology, a whole new level of applications will emerge. However, leaders will need to look beyond the technology to determine how it aligns with the overall business strategy and the company’s ability to implement it effectively. Although the wider adoption of AI is a source of value creation, it can become problematic when organizations don’t have appropriate governance structures in place.

It is also important to consider that employers will no longer hire for specific skills, which will constantly be evolving, instead, they will hire people for their ability to learn and potentially add value. Where technical skills remain in demand, human skills - like flexibility, adaptability, time management, and prioritization - are moving to the top of the value-added chain. Those who thrive in the future will be those with the ability to learn, unlearn, and adapt to digital world order. Automation and the rise of the augmented workforce are compelling executives to think differently about the value of their employees and the value those employees can contribute.