How AI Can Make Human Intelligence More Valuable Than Ever

Paul Clark

Lately, there’s been a lot of discussion about the emerging role of artificial intelligence (AI), as well as its subsets, including machine learning, deep learning, and automation. Some people say that widespread acceptance of the technology will bring tremendous job loss that could be nearly impossible to regain. Meanwhile, others foresee a future where work is more meaningful and more people earn a livable wage.

No matter which side of the debate you’re on, there’s no telling what will happen with certainty. But Stephanie Stachura, senior manager in the human capital consulting practice at Deloitte, believes that organizations should start shaping the future to help ensure technology and humans can work together as one. She was recently on the “Next Wave of Tech at Work: Is Human-Centric AI Possible?” episode of SAP Radio’s “Coffee Break with Game Changers.” During the conversation, she said, “From the talent side of the business, [adoption of AI] is not necessarily about replacing people. It’s more about the elevation of certain skills.”

And Stachura is not alone with her perspective. In his podcast, “The Surreal Rise: Artificial Intelligence & Machine Learning,” Eric Kavanagh, CEO of The Bloor Group, noted, “AI and machine learning are going to affect just about every industry in various ways, shapes, and forms. I’m not as concerned, like some people are, about jobs being lost as much as I am about jobs being optimized and people doing more interesting things.”

Embedded artificial intelligence brings empowering human-centered experiences

With 84% of enterprises claiming that AI investments will lead to increased competitive advantage, most executives are looking to get beyond the hype surrounding the technology to uncover its vast potential. However, this is not as easy as just installing platforms that process large volumes of data in seconds, programming applications to follow specific business rules, or setting sensor-driven triggers that address operational anomalies.

HPE Pointnext suggests that businesses should prioritize real outcomes first when it comes to their AI initiatives. Tapping into advanced technologies and AI models and libraries, they can solve real business problems in three ways:

  • Simplify: Build and consume open, flexible solutions for secure data lakes, Big Data, and integrated analytics
  • Accelerate: Predict and automate outcomes and decisions from edge to core by applying AI
  • Innovate: Identify and apply emerging technologies and AI to industry-specific use cases

By embedding AI into every aspect of their internal operations and customer-facing interactions, businesses can take advantage of large volumes of data to repetitively and accurately process and refine AI models and predictions. In fact, this capability alone may be more valuable than any opportunity to use the technology to replace headcount.

According to Glyn Bowden, chief architect and lead of the AI and data science practice for Hewlett Packard Enterprise (HPE): “Human intellect has the unique property of being able to apply context to completely new stimuli in order to absorb that information into our analytical thought process. We make a cognitive decision on the value of the data provided by the new stimuli and its relationship to other data, and we generate context for it. This way we can make our decision tree exponentially more complex while continually refining it. It’s how humans learn.”

Learn more by accessing the “Next Wave of Tech at Work: Is Human-Centric AI Possible?” episode of SAP Radio’s “Coffee Break with Game Changers” hosted by Bonnie D. Graham.


About Paul Clark

Paul Clark is the Senior Director of Technology Partner Marketing at SAP. He is responsible for developing and executing partner marketing strategies, activities, and programs in joint go-to-market plans with global technology partners. The goal is to increase opportunities, pipeline, and revenue through demand generation via SAP's global and local partner ecosystems.