Innovative companies around the world are working on big problems, like treating cancer with mRNA vaccines and making autonomous cars safer. Addressing these complicated issues takes more than just an inventor or two with good ideas and intentions. In fact, “90% of companies are confronting problems so complex that teams are essential to solving them.” Yet, collaboration is often limited by institutional inefficiencies, such as “poorly designed tasks, ineffective collaborative work practices, and inadequate information systems.”
As solving complex problems, from COVID-19 to climate change, becomes increasingly urgent, companies must find ways to overcome these inefficiencies. Is an AI teammate part of the answer?
Benefits of an AI Teammate
Artificial intelligence is good at tasks that humans don’t always do well; missteps, especially in data collection, are called “human error” for a reason. When teams delegate detail-oriented, time-consuming tasks to AI, human team members have more time to focus on tasks that AI can’t do well.
When AI is the one gathering data and searching for insights, humans have more—and more accurate—information they can use to make decisions. While AI can make autonomous decisions based on available data, human judgment is difficult, if not impossible, to replicate with current technology. This symbiotic relationship allows for faster, better decisions at all levels of business.
AI can also serve as a go-between. The right tools help teams store, share, and communicate essential details. IP.com’s AI-powered IQ Ideas Plus™ provides feedback on novelty to engineers and streamlines the innovation disclosure process, enhancing collaboration between an organization’s R&D and IP teams.
Barriers to Working with AI
Adding an AI partner to your current workflows is not enough to realize the benefits of artificial intelligence. The first barrier to working seamlessly with AI is a failure to integrate it completely into your business. This requires big changes—organizational, procedural, and cultural—that are not completely risk-free. Adding to this challenge is the unavoidable fact that AI is not always a perfect solution from day one. Machine learning is an evolving process that takes human input and oversight. Over time, AI and human teammates will learn how best to work together—not unlike adding a new human employee to a team.
Relying on AI as a member of the team is also challenging for the same reason organizations hesitate to rely on AI for any task: the “black box.” If AI can’t explain how it arrived at a specific solution, whether it be a decision on who to hire or what to patent, it may be a less valuable teammate.
If companies are, in fact, dedicated to solving the problems our society faces, they must explore all avenues for novel solutions. This likely includes AI, which likely offers substantial benefits if teams (and their employer as a whole) are willing to work through initial barriers to adoption.