It’s been twenty-five years since Peter Drucker outlined what he called the greatest challenge facing management in the twenty-first century: improving the productivity of knowledge work. What did he predict would prove hardest, and what did he never imagine?

Management’s roots are in the industrial age, with its focus on cranking out known solutions with ever greater efficiency. Now that organizational survival demands more creative breakthroughs, how do methods and frameworks have to change?

Knowledge workers are decision-makers. But as organizations and economies become more knowledge-intensive, are the people in them getting better at making good choices? How could we help them build that strength? And in an age of increasingly smart machines, should we bother?

If business history teaches anything, it’s that large organizations struggle to spot and seize on the exciting new opportunities emerging all around them.  Is it a problem of who gets hired to work in them—or what the organization does to them once they’re onboard? What can we learn from places where entrepreneurial flames burn bright?

Looking for inspiration on how to apply the hottest AI tools in your operations? Here, the focus is on real-world deployments that yielded impressive gains—from R&D and autonomous maintenance to advertising and staffing management. What were the keys to their success? What might be the unintended consequences?

Everyone concerned with talent development agrees that changing conditions require new capabilities in the workforce. But that’s where the agreement ends. Given limited resources and an unpredictable future, which new capacities are most important—and exactly how should they be built? Talent development experts offer competing answers.

Recent developments on the global political landscape are sending seismic shocks through commercial ecosystems. Will future historians look back on this moment as a catastrophic end of an era, or the turning point toward accelerated progress and prosperity? What key moves by powerful policymakers—and energized citizens—could make all the difference?

If your job is to take teams of people to greater heights of achievement, you should be learning all you can about what makes them tick. 

Recent years have seen a surge of social justice activism by organizations—not always perceived as sincere, not universally appreciated. Meanwhile, have employers made progress in their first responsibility, treating their own people with fairness and respect?

Certain ideas about how to run organizations have been thoroughly contested and disproven, only to rise again and continue wreaking their havoc. In this lively session, management observers who have seen this movie before call out the undead notions that should finally be stopped in their tracks.

The global pandemic unleashed in 2020 forced workplaces into unplanned experiments with remote and hybrid working models—and now, many are dialing back those arrangements. What did we learn in the process about the conditions people need to do their best work? How does an organization decide what is right for its own workforce?

We hear that new tools, processes, and organizational structures have deliveredn explosion of knowledge worker productivity—but is it true? How do we know one way or the other?

When talented people combine their strengths, amazing things can happen. But that takes skilled project management, structuring

Some component of any worker’s labor is “uncontracted”—exerted at their own discretion, according to how much they care about the success of the enterprise. For contractors, consultants, and other knowledge workers who work at arm’s length from your organization, that is a very large component indeed. What inspires them to contribute best efforts?

Organizations do not succeed in isolation any more than individual people do—they are densely connected in webs of mutual dependence and cooperation. Learning to lead beyond the walls of a single enterprise is a next-level capability, but increasingly demanded of today’s managers.

The conventional wisdom about the rise of artificial intelligence is that it will disrupt knowledge work in the way that industrial technologies of the past disrupted manual labor. Not everyone believes it’s true.