The State of Human–Machine Collaboration in the Workplace

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I currently work with a client who supervises two software robots that process financial data for her organization. A colleague in project management built a bot that now assists him with several personal workflows. I’m frequently asked about the status of human-AI collaboration, and I easily provide examples like these of the two cooperating. Both the humans and machines benefit as a result.

However, when I read reports and academic articles about the state of human interaction with machines, I often see a disconnect between them and what I encounter firsthand while working with businesses to implement and explore technologies like robotic process automation (RPA), chatbots, and cognitive computing. Here, I dive into my direct experience, not what the internet says is going on. I share these real-world scenarios in the hope they spur you to action, providing the confidence you need to start (or continue) your journey toward true human-machine collaboration.

Full Disclosure: Artificial intelligence co-wrote this post. I drafted the article, used an AI writing tool to polish it up, and then collaborated with an editor to make it ready for you, the reader.

The Technology Isn’t New, the Mindset Is

Chatbots aren’t new. RPA isn’t new. I hear people say, “We’ve been doing this stuff for years.” And it’s true. Companies have implemented chatbots and RPA tools as stand-alone technologies that work in silos. But this isn’t human-machine collaboration. It’s a machine working on its own.

Human-machine collaboration is where we are today, and it isn’t about technology. The technology has been available for years. This is about a mind shift in how businesses approach technological and human resources. Human and digital workers are better when they are designed to collaborate, passing a project back and forth. Play to each other’s strengths, cover each other’s weaknesses. That’s how you achieve synergy, a sum greater than its parts.

Here’s an example: Instead of a chatbot just answering questions, create an escalation workflow where the bot passes the baton to a human specialist, equipping the human with everything they need to provide a delightful customer experience. The chatbot prepares data for its human coworker, entering content into the customer service system, so when the human takes over, the conversation doesn’t have to restart. It continues naturally, seamlessly.

Related Article: BPA vs. RPA: How Are They Similar, How Are They Different?

You’re Not the Last to the Party

Our anxiety-prone brains tend to imagine deficit. Manufacturers think healthcare is ahead of manufacturing. Healthcare thinks manufacturing is leaving them in the dust. Every industry suspects it’s lagging behind the rest. Reality check: Relax, everyone is still figuring the future out.

I’m hearing and seeing firsthand individual companies progressing with experiments, but getting stuck in pilot projects. Hence, the barrage of marketing materials talking through how to move beyond the pilot and the conference session titles that are more focused on “what’s next” than “what I’ve done with the next-generation thing.”

You aren’t late yet, but you need to start moving now. If you do not, you will be late.

Related Article: AI in the Workplace: We’re Measuring the Wrong Things

Is the Technology Ready?

As always, the answer is yes and no.

Yes, the technology is ready, depending on your use case. If you go outside an approved use case, then no, the technology is not ready.

Successful implementation of human-machine collaboration requires intimate familiarity with the edges/limits of your tool’s capabilities. For example, I’m often asked if RPA can read documents. The answer: It depends on the document. The larger challenge here isn’t the limitation of the technology. It is the trust gap that is built when the technology implementer answers every question about what the technology can do with, “It depends.”

A team works when the team members trust each other to accomplish their tasks. If you ask your team member if they can do something and their answer is always, “Well, it depends,” your trust level isn’t going to be too high.

Humans need to trust their machine coworkers. To build this trust, leaders need to help grow an understanding of what these tools can and cannot do. Leaders need to show human employees their role in the human-machine team through clearly defining business processes and demonstrating how value is generated by the human plus machine team.

Related Article: AI Deployments Depend on Human Skills Too

Is the Business Ready?

This is where most human-machine collaboration challenges are found. Technology is thrown onto a business process without thinking through how humans and machines will work together. Instead, the technology is seen as “cost reducing” or “replacing the human.” This is the path to trouble.

Would you hire new humans without being able to show how they enable a business strategy? Any tech implementation should demand the same proof of concept. As natural language processing (NLP) grows, and machine capabilities and chatbots become an extension of your human team, you need to align the machine team members with your human team members and show how your whole, integrated team is driving business strategy.

Now is the perfect time to redesign your business processes so humans and machines collaborate to create the best experiences for your customers and employees. Customers expect immersive digital experiences and want to connect with humans through technology. Employees are demanding connected experiences powered by technology so they can focus on work that matters. In today’s economy, human-machine collaboration is a win-win. You need it to realize strategic business objectives, and your customers and employees are starting to expect it.

Is Your Business Ready for Collaboration?

Human and machine collaboration is at a fascinating moment right now in the Great Reshuffle of 2021. The workforce is changing drastically, and businesses are looking to automation for stability. Organizations feel the pressure to automate that comes with low unemployment rates, but they also see the strategic benefits of human-machine collaboration. As companies jump on the bandwagon to integrate, they are having difficulties making the leap because this isn’t just a tech integration. It is fundamentally changing how we think about and accomplish work. Leadership teams need to understand how this technology can make their business more effective and sustainable, not just cut costs or replace humans with robots.

The technology that enables humans and machines to collaborate is ready for business. Is your business ready for the technology?

Tim Kulp is the Chief Innovation Officer at Mind Over Machines and a member of the Forbes Tech Council. He’s trying to change the world.

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