The human mind is unpredictable: decision-making patterns can only be assumed to a large extent due to neuroplasticity enabling us to adapt to personal and professional experiences resulting in evolving patterns of motives and expectations. As a leader in a people intensive business, I find myself spending a considerable amount of time in conversations with people of diverse generations, nationalities, and career stages—each with varied expectations, emotions, experiences, and interpretations of one’s organization culture. Amidst this I wonder—what is it that our employees really need?

We continually strive to excel at business performance, focusing on tangibles such as revenue, budgets, and asset health. To help boost performance and decision making across organizations, we see emerging technologies such as Artificial Intelligence (AI), machine learning and big data being used incrementally. These technologies have progressed to many organization’s journey by enhancing their productivity in systems, processes, and customer engagement. However, with the disruption of AI and new technologies impacting the future of work, do we ignore the needs and health of our most important assets—our people, because we think we can’t compute or predict them? The reality is that we can, yet very few organizations undertake to do so.

The concept of people profiling is not new—traditionally, behavioral science driven through experimentation on samples of human data has been leveraged to generalize segments of human behaviors – as an outcome of which human capital strategies were developed. However, due to human error, stereotyping and continuous evolution, it is a time consuming and static process which cannot possibly cope up with the diversity of the present workforce, leading to irrelevant human capital strategies – which may be fit-for-purpose but not fit-for-people.

The application of AI and Machine learning allows organizations to combine employee data with fast, iterative processing and intelligent algorithms, enabling the software to learn automatically.

An integral aspect of people and change services is creating human-centric talent strategies by leveraging AI to provide data-based insight, enabling us to address the question of how leaders can create strategies which are “fit-for-people”. A one-size-fits-all approach to human capital strategies have unlimited shelf life (indeed, they only look good on shelves!) and can leave leaders wondering why some high performers are resigning.

Employee’s happiness and well-being are one of the key contributors centric to an organization’s health equity. The use of machine learning has disrupted the common use of annual engagement surveys, focus group discussions and grievance channels to evaluate organizational health. Technology such as facial expression detection and NLP driven chatbots are enabling organizations to simply understand behavioral patterns, preferred workstyles, and track real-time employee sentiment on what does or does not ‘click’, to identify potential cases of employee satisfaction, burnout or loss of well-being. Organizations who leverage such information are able to proactively reshape and simplify communication through interactive virtual agents, build cultural and diversity intelligence, introduce flexible working models, and create personalized reward and recognition strategies – driving higher employee engagement, lower attrition rates and lower rehiring costs.

AI driven initiatives face formidable cultural and organizational barriers. With the increase in digitization, concerns amongst employees, including HR professionals, arise regarding jobs being replaced by AI. However, if used correctly, the augmentation of human minds with AI can help organizations to revitalize strategies, as well as pre-empt future skill needs. Analytics available today supported by “AI/human augmentation” enable the generation of real-time data on market supply and demand of skills, and the impact of automation on jobs in the future. This enables organizations to determine future core skills, driving their ability to reshape their corporate structures and make decisions concerning hiring or building skills internally. Talent and Learning leaders are hence able to build value-adding, relevant and non-replaceable skills–empowering organizations to work with employees to create version 2.0 of their jobs. Contrary to the belief that jobs will be replaced, this approach allows leaders to build trust and loyalty by customizing talent strategies to prepare employees for the future, instead of fostering an environment that foments apprehension of job loss, leading to disengagement and loss in productivity.

The most common use of AI in HR today is in recruitment, but emphasis remains on the automation of repetitive and administrative tasks. Few organizations have adapted its full potential by identifying suitable matches between individual career pathways, workstyles and business operating models, reducing the risk of individual and personal goals misalignment. The use of augmented and virtual reality coupled with AI also allows employers to simulate their work environments, allowing potential candidates and employers to test the waters, assess cultural and role alignment, further reducing hiring risks, recruitment costs and employee turnover.

The use cases of AI are evolving as it continuously learns, adapts, and senses changes to people and organization’s patterns. The key to sustainability thus becomes the continuous evolution of our approach to human capital to enhance employee experience and organization health. HR strategies that are built purely based on leading practices from competitors, and conversations with courageous high performers who speak up about what they need, may not be enough. Without adopting and embracing AI, your organization’s human capital strategy may lack employee centricity and remain obsolete.

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