University of Kwazulu-Natal

Why Humans Matter Most In The Age Of Ai Jacob Taylor On Collaboration

Bonisiwe Shabane
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why humans matter most in the age of ai jacob taylor on collaboration

Jacob Taylor, Thomas Kehler, Sandy Pentland, Martin Reeves Janice C. Eberly, Molly Kinder, Dimitris Papanikolaou, Lawrence D. W. Schmidt, Jón Steinsson Rosanne Haggerty, Ruby Bolaria Shifrin, Jacob Taylor, Kershlin Krishna, Sara Bronin, Nick Cain, Xiomara Cisneros, Adam Ruege, Henri Hammond-Paul, Jamie Rife, Josh Humphries, Beth Noveck

Agur Jõgi, CTO of Pipedrive and expert in scaling technology and organizations. Experienced as an innovator, founder and C-level manager. Working well with others is a strategic advantage and will become even more so with greater digitization and AI use. In today’s business landscape, few organizations or individuals will succeed in isolation. Collaboration with and across teams, industry alliances and supply chains has always been essential, and making real human connections will remain core to successfully partnering and achieving great things. True collaboration begins with clarity.

When leaders articulate a clear vision, others can align with it. But clarity alone is not enough. Businesses need to build a culture where goals are shared, expertise is distributed and success is collective. Internal collaboration drives operational excellence. Cross-functional teams that work well together avoid duplication, solve problems faster and innovate more effectively. Collaboration must also span hierarchies.

Junior employees, senior leaders and everyone in between contribute perspectives that shape better outcomes. Diversity of opinion and experience, mediated by a shared culture, really kicks up the gears of innovation and productivity. Externally, few companies can retain every skill they need in-house. That’s why peer networks, strategic partnerships, vendors and consultants play a role. Open sharing, where appropriate, can improve benchmarking, refine KPIs and accelerate learning. Industry groups and lobbying bodies, meanwhile, extend influence where it matters most.

“If we’re faced with problems that are moving fast and require collective solutions, then collective intelligence becomes the toolkit we need to tackle them.” Jacob Taylor is a fellow in the Center for Sustainable Development at Brookings Institution, and a leader of its 17 Rooms initiative, which catalyzes global action for the Sustainable Development Goals. He was previously research fellow at the Asian Bureau of Economic Research and consulting scientist on a DARPA research program on team performance. He was a Rhodes scholar and represented Australia in Rugby 7s for a number of years. Reimagining Team Performance Through Collective Intelligence Using 17 Rooms to Break Down the SDGs Into Action

Building Rituals That Elevate Learning and Challenge Norms While many focus on the disruptive potential of artificial intelligence, Brookings Fellow Jacob Taylor asks, how can AI amplify human intelligence? In this Q&A, he discusses why collaboration, creativity, and human judgment remain key to solving global challenges. https://lnkd.in/eBCx5kQ8 AI AND THE FUTURE OF WORK: WHAT MATTERS NOW Artificial intelligence is fundamentally reshaping the global economy, initiating a paradigm shift in the very nature of work and human interaction. In this article, I advocate for a deep-seated belief that sustainable organizational transformation emerges from a conscious corporate culture.

This culture is organically nurtured through the consistent cultivation of individual habits. *** Our strategic imperative is not to resist the inevitable currents of technological change, but to consciously direct their flow, ensuring humanity retains its central, vital role in shaping progress. *** Read More: https://lnkd.in/gGZ84DVX #FutureOfWork #Consciousness Rivalry vs Resonance Competition fuels progress, until it doesn’t. Across industries, academia, and technology, we’ve watched rivalries sharpen minds and split ecosystems. When the goal becomes “winning the field” instead of expanding the field, collaboration slows.

Ideas that should connect stay siloed behind pride, policy, or protocol. At Inner Resonance™, we’re studying a different model, one where rivalry becomes resonance: a system of mutual calibration where difference generates discovery instead of division. Because the future isn’t built by isolated teams guarding breakthroughs; it’s built by networks that learn to synchronize signal, share data, and evolve together. Let’s replace competition that fractures with coherence that scales. #InnerResonance #Collaboration #Innovation #Leadership #AI #HumanCenteredTech Generative AI can act like a high-performing collaborator on team projects, propelling innovative thinking, says research by Harvard Business School's Fabrizio Dell'Acqua, Raffaella Sadun, and Karim Lakhani.

They offer four recommendations for applying AI to teamwork. The research was conducted with Charles Ayoubi of ESSEC Business School, Dr. H /Hila Lifshitz (Hán, X也) of University of Warwick - Warwick Business School, Ethan Mollick and Lilach M. of The Wharton School, and a team from Procter & Gamble that includes Yi Han, Jeff Goldman, Hari Nair, and Stewart Taub. Read the findings: https://lnkd.in/ekaG5TUb If your team isn’t jumping on AI… it might be a sign they trust you.

When people care about the quality of their work, they hesitate with anything new. That’s not laziness - it’s integrity. So if your team is asking hard questions about AI? If they’re cautious? Thoughtful? Even skeptical?

Good. That’s what responsible adoption looks like. Pushback isn’t the problem. - silence is. When we treat curiosity as resistance, we shut down the very people we need to lead change. So if your people are poking holes, naming risks, asking “what about equity?”, don’t speed past that.

Pull up a chair and listen in. That’s not friction - that’s culture in motion! The “Age of AI” is not just about smarter machines; it’s critically going to be about smarter collaboration between people and technology. The Changing Nature of Teams and Leadership AI is rapidly automating many repetitive and analytical white-collar tasks, however human teams are still needed to focus on real creativity, strategy, empathy, and more complex decision-making. In this environment, successful teams will need to blend high technical literacy with the emotional intelligence that only humans can offer.

Teams will need to be well composed to deal with increasing change, risk and compelxity. Leaders, too, will evolve — shifting from old-school directive management styles to becoming facilitators of human and machine-driven insights for performance. In this mix good old-fashioned trust, and adaptability must not be lost. Virtual and hybrid work will continue to thrive, supported by increasingly intelligent systems that match skills, predict team dynamics, and even assist in decision-making. Yet, the ability to communicate effectively, embrace cognitive diversity, and manage interpersonal dynamics will remain uniquely human strengths, and still be best on an in-person basis whenever possible. Posted November 25, 2025 | Reviewed by Margaret Foley

For years, innovation has centered on speed. Faster processing. Faster decisions. Faster communication. But as artificial intelligence reshapes the modern workplace, a quieter truth is emerging from neuroscience and behavioral psychology: as technology accelerates, people are slowing down emotionally. Across industries, employees report rising cognitive fatigue, decreased trust, and a growing sense of isolation despite being more digitally connected than ever before.

The World Health Organization now recognizes burnout as an occupational phenomenon, and research firms are consistently finding that employees feel overwhelmed by the volume of digital tasks and communication rather than liberated by it. What’s becoming clear is that automation may increase efficiency, but it cannot replace the psychological conditions that allow humans to feel safe, understood, and ready to collaborate. In fact, research shows that human well-being rises most predictably when people experience meaningful interpersonal connection, not just more technological convenience. To explore this shift, I interviewed Sean Callagy—an entrepreneur, founder of Unblinded and ACTi, and a leading authority on modern business, leadership, and integrous human influence—to better understand why human connection is becoming the... It’s no new news that Artificial Intelligence is already here —built into the tools we use every day, from meetings to messaging. But one big message from Cisco’s WebexOne 2025 conference was clear:AI will only succeed when people stay involved.Technology alone won’t get us there.

(This post was inspired by insights shared in BizTech Magazine’s coverage of Cisco WebexOne 2025.) AI adoption starts — and sometimes stalls — with trust.If people don’t trust an AI system, they won’t rely on it. The takeaway: don’t treat AI like a black box.Transparency, guardrails, and human oversight are essential. Siobhan Hanna, SVP and General Manager, Welo Data. The transformative impact of AI on language translation, content creation and other areas is undeniable. However, behind every high-performing AI system lies a critical foundation that human annotators built.

These individuals meticulously label the raw data—images, text and audio clips—that feed AI models, allowing them to learn, process and perform at advanced levels. At the heart of every AI-driven breakthrough is high-quality data annotation. Human annotators provide the nuance and precision that AI systems need to operate at their best. Without this expertise, AI models would struggle to interpret complex information or offer reliable outcomes. As technology leaders, we must emphasize that data annotation is not just a technical process but a critical human-driven endeavor. As businesses race to implement AI, the demand for skilled data annotators has surged, especially with the rise of large language models (LLMs).

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