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Competitive vs. Cooperative Skills for AI

Work innovators build balanced teams with competitive and cooperative AI skills. Applying these skills can take your team to the next level.

Competitive vs. Cooperative Skills for AI
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The ongoing emergence of new generative artificial intelligence (AI) applications signals a shift in the way work gets done. It's a change that's happening rapidly—and is embraced by some of the world's most innovative companies.

The innovators aren’t just limiting themselves to doing business as usual either. They’re embracing AI disruption and thriving through their use of new technology.

At Upwork, our 2023 Work Innovators report sheds light on how and why these companies—and their leaders—excel in times of change. While a number of factors play into these successes, embracing new systems and hiring for specific skills is a big part of the process.

You too can think (and hire) like a work innovator who's ready to embrace AI as part of a digital transformation. Here's how.

Establish a system of innovation

When conducting research for the Work Innovators report, we weren't merely looking for companies using generative AI.

Staying in line with the broader mission of the Upwork Research Institute, we sought to understand the fundamental practices driving innovative companies forward—independent of the technology they used.

Interestingly, our findings revealed that many of the companies we spoke to lacked a formal generative AI strategy. Those that did have a strategy in place, though, were more likely to be a work innovator.

Work innovators are 2.9 times more likely to have an AI strategy in place.

This finding makes sense: work innovators typically exhibit a systems mindset.

Traditional business models often rely on a linear mindset. This way of thinking looks at inputs and outputs, and in order to make change, you typically need to isolate parts of processes. This isn’t bad—but it isn’t always the most effective way to work, especially within a large organization.

A systems mindset, on the other hand, allows business leaders to look at interconnected relationships within said system—in this case, a company. With this mindset, work innovators can look at how new relationships form as connections evolve. It becomes easier to see how connections are central to business operations, too, as it’s harder to isolate single parts of an organization when you have a systems mindset.

By taking this big-picture view of their organization as a system, work innovators can better recognize their team members' skills and abilities. They can also evaluate the capabilities of the technology their teams use.

Embrace a systems mindset to enhance AI innovation

When we apply this thinking to AI, it becomes easier to determine which parts of a system are appropriate for a machine to handle, and which parts need a human touch.

Because work innovators are more likely to use a systems mindset, it makes sense that they're excited by the use of AI in business—they can see exactly how it fits into their company, and what benefits AI can bring.

47% of the leadership of high-performing businesses are actively incorporating generative AI into their daily operations.

Work innovators with a systems mindset can also see where connections are made between work done by a person and work done by a machine. This, in turn, helps them hire the right skill sets to support innovation.

Identify important skills for AI innovation

Innovators typically need to source two types of skills for success when working with AI models: competitive and cooperative.

Balancing these two skill sets in the organization makes it easier for leaders to plan hiring needs, build agile teams, and continue advancing work faster than non-innovator competitors.

What are competitive skills?

Competitive skills are human-centric—they can't be easily replicated by a machine. Such skills can include:

  • Emotional intelligence: The capacity to understand and regulate human emotions through self-awareness, empathy, and clear communication
  • Strategic thinking: The ability to analyze a current state and develop the steps necessary to reach a goal state—including an awareness of risks and potential
  • Creative problem solving: The ability to think outside the box and develop unique solutions that move innovation forward while working within any fixed limitations, such as budgets
  • Critical thinking: The ability to see all sides of an issue, evaluate the validity of arguments without bias, and dissect complex problems into discrete parts
  • Ethical decision-making: The process of choosing steps, alternatives, and solutions based on moral implications, consequences, and ethical considerations

What are cooperative skills?

Cooperative skills, on the other hand, are those that humans use to leverage the ability of a machine or algorithm.

These skills include:

  • AI literacy: An in-depth understanding of how algorithms, machine learning models, and neural networks work—along with their impact on real-world human productivity
  • AI fluency: An ability to plan, strategize, and work with AI systems in ways that will bring the organization and its stakeholders closer to meeting key goals
  • Algorithmic communication: The ability to communicate human needs to machine algorithms, such as through prompt engineering
  • Data analysis: The ability to understand algorithmic outputs and data in order to make decisions and advance work

Build a team with competitive and cooperative skills

To use AI like a work innovator, you'll need to first take a step back and make sure that you know why you want to use AI. What's the business problem you want to solve?

From there, taking a system-wide view is key. You know what your problems are—now find out where they’re happening. Are you dealing with a human problem? A machine problem? Or is there a breakdown happening when humans and machines interact?

This will help you decide whether you need to improve your technology, source new team members with competitive skills, or focus on strengthening the cooperative skills in your workforce.

Improve your tech stack

If you aren't already using AI—or you find system breakdowns happening when AI is supposed to carry out specific tasks—then it's time to upgrade your technology.

You can integrate AI into your workflows in countless ways, from hiring AI developers to build custom applications to using AI tools with a dedicated purpose (such as generating social media content).

42% of work innovators already have large language models in place, compared with just 19% of their peers.

Upskill existing team members

If you find that you need more competitive skills in your company, you may be able to enhance your existing team through training and development.

Find the people in your organization with great emotional intelligence, strong decision-making skills, and creativity. Think about where and how you can best use their competitive skills within your own system—and seek out training tools to help them continue to strengthen these skills.

Add skills with independent talent

You can also add select skills to your team as needed by embracing flexible talent.

A flexible talent model allows you to bring in independent talent with specific experience—great when you need a key cooperative skill.

Leaders who create an environment where flexible talent models thrive are 111% more likely to believe their teams have the right skills mix to meet goals effectively.

This unlocks tremendous flexibility for a changing workforce and allows innovators to always have the best AI talent available to them.

Transform into a work innovator

Staying at the forefront of innovation involves understanding your system, embracing AI technology, and leveraging the power of flexible talent.

But these aren't the only points of focus for the most innovative companies operating today. To learn more about how work innovators function—and take steps to work like an innovator throughout your organization—read the complete Work Innovators report.

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Author Spotlight

Competitive vs. Cooperative Skills for AI
Kelly Monahan
Managing Director, Upwork Research Institute

Dr. Kelly Monahan is Managing Director of the Upwork Research Institute, leading our future of work research program. Her research has been recognized and published in both applied and academic journals, including MIT Sloan Management Review and the Journal of Strategic Management. In 2018, Kelly released her first book, “How Behavioral Economics Influences Management Decision-Making: A New Paradigm” (Academic Press/Elsevier Publishers). In 2019, Kelly gave her first TedX talk on the future of work. Kelly is frequently quoted in the media on talent decision-making and the future of work. She also has written over a dozen publications and is a sought-after speaker on how to apply new management and talent models in knowledge-based organizations. Kelly holds a B.S. from Rochester Institute of Technology, an M.S. from Roberts Wesleyan College and a Ph.D. in Organizational Leadership from Regent University.

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