The 3 Tips You’ll Need to Succeed in the Age of AI Agents

The rise of AI agents in the workforce marks a major shift in what the future of work looks like. They’re performing increasingly intelligent tasks, like augmenting our decisions, generating entire strategies, interacting with customers, and soon, working alongside us in Slack. In fact, Slack’s most recent Workforce Index survey of more than 17,000 global desk workers found that 41% are excited for AI to handle tasks from their current job. The key question is, what skills do we need to sharpen to stay valuable as knowledge workers?

Slack’s Workforce Lab invited a group of leading AI academics for a candid conversation about preparing and hiring for the jobs of the future. These experts discussed how employers can foster a culture of experimentation, learning, and sharing, and can cultivate a growth mindset to effectively use AI. Watch the full discussion here or read on for their top tips and insights.

Tip 1: Learn the fundamentals of AI and agents to lead confidently in the agentic era

Our rapidly changing digital world requires everyone to develop the muscles to navigate change and boost technical literacy. Just as email, digital work platforms, and apps became commonplace in modern workplaces, AI and agents will follow suit as essential work tools.

Strengthening technical literacy skills isn’t about learning how to code or becoming a data scientist, said Gerald Kane, the head of the Management Information Systems Department at the University of Georgia. It’s about understanding the fundamentals of AI and agents, including their general capabilities and strengths.

“It’s about having a growth mindset,” Kane said. “Most of my time is spent convincing people that they can learn what they need to learn to participate in this next wave of the digital revolution. I go into some companies and they say, ‘Oh, we’re a legacy company, we can’t do that,’ or ‘I’m not a tech person.’ But I believe this learning is accessible to just about everyone if they are given the time and if they take the time to figure it out.”

Kane specializes in understanding how companies respond to major digital disruptions, like Covid-19. He is the lead author of The Technology Fallacy: How People Are the Real Key to Digital Transformation, and The Transformation Myth: Leading Your Organization Through Uncertain Times, both published by MIT Press.

Kane believes the digital adoption gap is one of the biggest challenges companies face in the agentic era. The adoption gap refers to the rate in which technology advances in comparison to how quickly it’s adopted by individuals, businesses, and public policy. More often than not, businesses and policy lag behind the pace of technological change.

Kane’s research found that a striking 30% of people were likely to leave their organization within a year if they were unhappy with its digital advancement. However, if employers provided development opportunities, these individuals were up to 15 times less likely to want to leave within a year. Notably, these weren’t entry-level employees; they were team leaders and executives.

Employees recognize the need to update their skills and will seek out employers that offer learning opportunities, including tools like AI, as they understand these capabilities will be essential for future competition.

Tip 2: Embrace experimentation and share what you learn

If you feel like you haven’t gotten the hang of using generative AI, Lilach Mollick, the Co-Director of the Generative AI Lab at the Wharton School of the University of Pennsylvania, offers reassurance.

“No one knows the best way to work with generative AI,” Mollick said. “There is no instruction manual. People are using it in radically different ways, depending on their areas of expertise. AI is not like coding, it’s more like teaching or managing.”

At the Wharton School, Mollick leads team-building applications to shape the future of AI in educational settings. She’s written several highly cited papers on the uses of AI for teaching and training, and the prompts she’s developed for educators and students are used throughout the world.

Mollick emphasizes the importance of sharing experiences and lessons learned when exploring AI. Leaders should encourage colleagues to openly share their expertise, use cases, successes, and failures. “Our organization is very open about sharing what works and what doesn’t work for us,” Mollick said. Creating roles specifically for individuals who focus on how AI can enhance productivity builds a path forward for teams to develop AI best practices that work for them.

There’s often fear associated with AI so it’s crucial to incentivize and encourage employees to share their experiences. For instance, organizing a demo day where employees can present how they used AI, how it benefited their team, and what they learned can promote a culture of sharing. If organizations don’t foster this sharing, individuals may use AI on their own, leading to missed opportunities for organizational learning and growth.

“Let’s invite AI to the table and explore what it can and cannot do,” Mollick said. “Let’s discover where it surprises us and where it might ‘hallucinate’ or make errors. It’s important not to wait for a consulting company to dictate the training you need; instead, develop your own in-house programs.”

Tip 3: Strengthen your cognitive and self-regulation skills

The skills that humans do best — like strategizing, creative thinking, collaboration, and reflection — are even more important in the agentic era, said Haoqi Zhang, an Associate Professor of Computer Science and Design at Northwestern University.

“In the future, all the problems that are going to be left to [humans to solve] will be research problems,” Zhang said. “Everything that is automatable, everything that is routine, everything that can be procedure-alized will be, and the AI will do those activities.”

At Northwestern University, Zhang works to advance the design of integrated socio-technical models that solve complex problems and advance human values at scale. He founded and directs the Design, Technology, and Research (DTR) program, which provides an original model for research training for over 100 graduate and undergraduate students.

To adapt to the AI revolution, Zhang believes that knowledge workers should focus on strengthening what he calls, “self-regulation skills.” Those are the critical skills for self-directing complex work, including:

• Problem-solving and planning
• People skills and collaboration
• Identifying risks
• Metacognition skills and the ability to self-assess knowledge on a subject
• Seeking help when needed
• Emotional regulation, like how to deal with failure and becoming more aware of our own fears and anxieties

Reasoning skills, especially concerning ethics, will continue to be especially important for knowledge workers. In practice, that looks like approaching a problem and knowing to ask questions, like:

• What are we trying to do here? 
• What’s the actual good in what we’re doing?
• What’s the goal we’re aiming for? 
• Why is that goal? 
• How do we make it more in line with the values that we have as an organization and as individuals?

Strategic thinking and interpersonal skills will continue to be crucial, now and in the future.

“Coming to see a problem differently — not just following procedures — is one of the most valuable skills of being a researcher,” Zhang said. “It’s the one irreplaceable thing that machines can’t do for us, and we wouldn’t want the machine to do for us anyway.”

Get started with Slack and Agentforce

Slack and Agentforce are here to give workers more time to focus on work that matters most. We’re building toward a future where humans and AI agents can work securely side by side, augmenting one another, so that you can focus on the work that matters most.

Talk to an expert to learn more about how Agentforce will work in Slack.