Arm-in-arm: How humans and machines will work together
- Posted on January 14, 2019
- Estimated reading time 4 minutes
This article was originally published in MoneyInc.
We’re in the year, if not the decade, of the algorithm, when data models can optimize virtually every aspect of a company’s operations. Model-driven companies weave design and data science into the fabric of their organizations to create more personalized products and services to better engage and retain their customers. It’s time to leverage these same practices to benefit your employees. One element of the future employee experience is about humans and machines working together. While that notion makes for nice headlines, how do you make it happen?
There are many organizations working to figure out how artificial intelligence will impact their business, and those leaders are often dealing with siloed organizational structures that make it difficult to leverage these new technologies. While there is lots of public debate on automation overtaking jobs, employees are enthusiastic about using digital technologies to get better outcomes at work. According to “Harnessing Revolution: Creating the Future Workforce“ by Accenture, 62% of workers believe artificial intelligence (AI) will have a positive impact on their jobs.
Let’s first look at digitally native companies as a showcase of this new way of working because they built it that way from the start. Stitch Fix is a great example of a model-driven company and how you can reimagine business processes for your employees with AI. Its main business is providing a personal shopping experience by picking out clothes and mailing them to you, all based on data you provide. You start by filling out a style survey, your basic body measurements, and then photos of styles you like.
Stitch Fix’s magic resides in its model-driven business, with algorithms running across every business unit and function, all supported by people. The clothing recommendation system is a combination of people and machines, where the structured data you provide is processed by the algorithm and then human stylists deal with everything else. They read the notes from customers about what they are looking for, they take inspiration from the style photos and then with the algorithm providing the recommendation, the full decision rests in the hands of the stylist who pulls it all together. It’s intelligence meeting design with the employee empowered with a new set of tools.
But most companies will not start out as model-driven and must adapt these new working experiences into an existing culture. That is not easy and at the core, there needs to be strong organizational change where employees are involved early and can design how they will eventually work. There are three core principles: preparing for the change with an AI strategy clearly defined, prioritizing the employee over the machine, and committing to scale up new skills for the employees to know how to work with the AI tools.
Let’s take a hypothetical example. A financial services company might be looking to empower their financial planners with enhanced research and relevant content for their customers. An AI-powered knowledge management system would enable the planners to find specific research across a variety of content and have the relevant points summarized by an AI system providing the specific information requested on financial products and policies. This would empower the planners with key information they need about their customer and allow them to find answers more quickly without having the machine help with the research. The company most likely has an existing process in place for the financial planners and to enable the success of the employees working with this new AI toolset, change management is required to support the rollout.
Going back to the core principles means:
- Preparing for the change: ensuring that the AI strategy is clearly defined and is aligned to the outcomes that the employees can achieve. How can this new knowledge exchange be used not just for financial planners but others across the organization?
- Prioritize the employee over the machine: involving the financial planners in the process for reimagining how they will work, and organizational leadership needs to understand how their work will be transformed by the tasks that the employee will perform vs. the machine.
- Skill development: identification of the new skills or tools that the financial planners will need to learn. Is the skill strategy in place for how the employees will need to work with the AI-powered system?
When you have humans and machines working together, it is imperative to apply organizational change principles and practices. The modern workplace experience is about how employees are enabled to reimagine their jobs of tomorrow. You can’t just jump into AI without thinking about the impact to your people. Empowering employees to work with machines opens the door for curiosity, creativity and the desire to make an impact on people’s lives.