How can we avoid being automated out of our jobs? When recommending areas for development, experts tend to focus on two broad classes of skills that distinguish people from machines: sociability and variability. But homing in on those areas can lead to burnout, leaving us even more vulnerable to obsolescence. Leisure can mitigate these effects. Beyond reducing burnout, leisure is a uniquely human activity that robots cannot perform, and it might actually make us better thinkers and workers.

Three impediments in particular work against agile adoption in most organizations. By addressing architectural rigidity, closing talent gaps, and adopting a product mindset, leaders and organizations can realize agile’s power in delivering business value.

High-skilled immigration is dramatically transforming the tech sector in the United States. U.S. tech workers over age 40 have good reasons to be concerned. In addition to competing with greater numbers of skilled foreign workers, older tech workers are now also more likely than younger workers to lose their jobs when technical work moves overseas.

The future of work will entail thinking not just analytically, but also algorithmically — so companies need to retrain workers for writing code, not formulas. Organizations that manage to make code the natural language for diffusing analysis across their organizations can often grow and innovate faster than their peers.

It can be easy to get caught up in all the uncertainty and speculation around the future of automation, but when we focus on the future, we may fail to see what’s happening right in front of us. In this audio interview, MIT SMR editor in chief Paul Michelman revisits the work of Accenture researchers Paul Daugherty and H. James Wilson to discuss what’s changed in the AI landscape and what leaders should be thinking about next.

Thoughtful adoption of intelligent technologies will be essential to survival for many companies. But simply implementing the latest technologies and automation tools won’t be enough. Success will depend on whether organizations use them to innovate in their operations and in their products and services—and whether they acquire and develop the human capital to do so.

Executives intent on exploiting AI to enhance processes or products tend to focus on having a strategy for AI. But creating strategy with AI can matter as much or even more. In a machine-learning era, enterprise strategy is defined by the KPIs that leaders choose to optimize —the measures organizations use to create value, accountability, and competitive advantage. AI can help determine what KPIs are measured, how they are measured, and how best to prioritize them.

Companies can turn AI hype into operational hay by developing their capacity for enterprise cognitive computing. This capacity entails five capabilities: data science competence, business domain proficiency, enterprise architecture expertise, an operational IT backbone, and digital inquisitiveness. The capabilities shape and are shaped by four practices: identifying use cases, managing application learning, cocreating applications, and thinking “cognitive.”

AI spares us from many mundane, time-consuming, nerve-wracking annoyances. The problem is, such annoyances play a key adaptive function by helping us learn to adjust our conduct in relation to the world around us. But AI designers can tackle that problem through system enhancements. By incorporating cognitive speed bumps, they can prompt users to engage in reflective thought rather than “outsourcing” cognitive, emotional, and ethical labor to software.

Renowned social psychologist Edgar Schein and his colleagues defined how we thought about organizations and leadership in the 1950s. But in the digital era, Schein — working with his son, Silicon Valley executive Peter Schein — has developed a new perspective, one that advocates combining culture, change, and leadership into an integrated process, rather than viewing them as three separate topics of importance.

For legacy companies, culture change is often the biggest challenge of digital transformation. How can they become more agile and innovative without alienating their best employees or wrecking their best existing practices? This article provides a framework for leaders in any industry. The process begins with understanding four key values of digital culture: impact, speed, openness, and autonomy. It then involves adopting or refining a set of digital-ready practices, grounded in these values.

While M&A deals and turnarounds are individually hard to pull off, combining the two can be even more challenging. Yet an analysis of roughly 1,400 M&A-based turnarounds between 2005 and 2018 shows that six management actions can help acquiring companies improve their odds of success. The rewards can be considerable. Successful buyers generate gains in both revenue growth and profit margins, and — most important — better returns.

The starting point for managing age diversity is to develop a basic understanding of cross-age differences in working style. The authors found that management style varied more with age than with any other characteristic in their survey. Younger managers prefer narrower approaches to management, while older ones tend to work through others and focus on the big picture. Being attuned to style differences can make it easier for individuals to navigate their working relationships effectively.

Leaders are increasingly strangers in the places where their organizations reside. With greater mobility and a disconnect from a physical office space, many leaders have identities that are not tied to one location. Yet leaders who lack a clear “passion for place” and well-established stakeholder connections might be putting their companies at a disadvantage during times of hardship.

Leisure time does two important jobs for us. Recharging is the obvious one. But it can also heighten our powers of creativity, given the cognitive benefits associated with letting our minds wander — and that gives us an edge over AI in the battle for jobs. Kellogg professor Adam Waytz makes this research-based argument in “Leisure Is Our Killer App,” the lead article in MIT SMR’s package on talent in a digital age. Check it out, along with the other pieces, in the fall issue of the magazine.

Technology may hold the answer to two of the knottiest problems faced by the U.S. economy — the shortage of farm labor and the excess of vehicle traffic. But there’s a flip side: It also enables surveillance so widespread and intrusive, companies can track even our heartbeats — and the data collected by these sensors is far from secure.

The Executive Briefings for the Summer 2019 issue of MIT SMR give a snapshot of the issue’s close look at the challenges, culture shifts, and opportunities that adopting AI will bring to businesses. Plus: How to make M&A successful; does management style change with age?