The must-reads MIT SMR editors are reading this week, including: potential pitfalls of the agile workspace, influencers’ influence on marketing, and gender bias in unlikely places.

The must-reads MIT SMR editors are reading this week, including: How working couples are hacking inequality at home, the future of work won’t be utopian, and why you should kill your favorite meeting.

The must-reads MIT SMR editors are most excited about this week, including: Why emotion is a key ingredient for getting customer experiences to stick, what we can learn from Germany’s platform economy, the best leader for your digital transformation effort might not be the obvious candidate, and more.

China is shaking off its reputation for “copycatting” and establishing itself as a digital leader. One of the key areas where it’s moving ahead of the U.S. and Europe is transportation. China has made strides in electronic and autonomous vehicles as well as high-speed rail in recent years — and its most important development has been to transform itself into an innovation-focused, entrepreneurial hub of technical prowess.

All bubbles are different. Bubbles occur when the market value of assets decouple from their intrinsic value and expectations of rising valuations generate investor demand. Many ambitious infrastructure projects that produced canals, railways, and telecom networks were fueled by bubbles. Unlike the housing bubble, the effects of a bursting AI bubble wouldn’t cause great harm.

The most valuable companies in the world have harnessed platforms’ power to achieve rapid growth and market dominance. But as these platforms have grown in size and scale, the opportunity for abuse has become very real — while profitability isn’t coming easily even for successful platforms. In an interview with MIT SMR, the authors of The Business of Platforms bust the myths and outline the pitfalls of platform strategy.

Each month, the MIT SMR Strategy Forum poses a single question to our panel of experts in the fields of business, economics, and management. This month’s question asks our panel whether, in the next five years, blockchain technology will have a transformative effect on emerging markets in the global economy.

As AI develops better decision-making skills, leaders may feel threatened and push back, resisting the imperative to leave their biggest and most critical decisions to mechanical minds. And that might be a mistake, says psychologist Daniel Kahneman, given AI’s potential to reduce the bias in human thought processes.

While KPIs are widely used to track performance across most enterprises today, not all organizations are using those metrics effectively. New research finds greater KPI transparency and better alignment drive maximum business value.

Digital efforts may begin within a particular functional area, but they can also drive change across the entire organization.

AI provides access to unstructured information and enables organizations to learn faster and offer new services.

AI’s largest and most enduring contributions will be in non-technology sectors, and many of them will come from China. Buoyed by the country’s latest five-year plan and enabled by centralized data, Chinese companies are investing aggressively in AI and adapting their business models to make the most of AI’s potential, but unclear business cases and bottlenecks due to lacking technical capabilities hinder adoption.

Software continues to “eat the world,” but often at the cost of user privacy and trust. In order to grow responsibly, companies must move from a “can we” to a “should we” framework when bringing products to market.

The art of bian lian — or “face changing” — is integral to Sichuan opera: A main character changes masks to avoid capture by foes. The transformation is quick and surprising, the new face clearly different. In the theater of business, Chinese performers are undergoing a rapid transformation of their own as they seek to evolve from backroom producers to the world’s leading face of innovation.

Emerging technology and new business models have created new ways of serving customers and allowed digital leaders to disrupt traditional companies. Disruption rarely comes out of nowhere, however: There are common patterns to learn from and three major signals to recognize in evaluating the risk for your industry.

As digital disruption expands, many legacy businesses seek partnerships with tech companies to maintain competitiveness in the digital sphere. But instead of a centralized “hub” partnership, some companies find greater success through an adaptive ecosystem model, where partners develop significant projects or innovations together. This type of strategy requires imagination and flexibility.

Using industry examples and findings from the McKinsey Global Institute’s research, presenter Jacques Bughin describes the current state of AI and offers strategies for maximizing its potential.

Companies used to spend years clarifying business requirements before they would even think of launching new software. Today, cheaper cloud-based apps mean that implementation decisions are made on the fly — and there’s no going back.

Mature companies often lack the vision and the commitment to fully commit to new technologies — even when consumers are ready for them. This leads firms to develop watered down products with limited capabilities and leaves them exposed to upstart competitors.

For more than a century, economies of scale made the corporation an ideal engine of business. But now, a flurry of important new technologies, accelerated by artificial intelligence (AI), is turning economies of scale inside out. Business in the century ahead will be driven by economies of unscale, in which the traditional competitive advantages of size are turned on their head.