Marketers are increasingly pessimistic about the economy, with sentiment reaching its lowest level since the pandemic in 2020. In response—and facing organizational pressures for returns—marketing activities are contracting, lowering spending and prioritizing existing customers over expansion opportunities.

At the same time, companies are accelerating adoption of artificial intelligence, projecting that AI will account for more than half of all marketing activities within three years. Yet this rapid technological progress is outpacing organizational readiness, with no marketing technology activity currently delivering at its full potential. These are among the findings of the 35th edition of The CMO Survey, directed by Professor Christine Moorman of Duke University’s Fuqua School of Business and co-sponsored by Deloitte and the American Marketing Association.

The survey was conducted from January 7 to January 29, 2026. It polled 308 marketing leaders at for-profit U.S. companies, 97% of whom are VP-level or higher.

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Professor Christine Moorman on why keeping marketing secrets may cost more than letting them go

Companies spend billions safeguarding their marketing secrets—from customer insights to pricing algorithms—assuming these secrets are key to competitive advantage. The global data loss prevention market is valued at an estimated $1.5 to $2 billion annually and continues to grow. But does locking down knowledge undermine performance rather than protect it?

In this episode of Duke Fuqua Insights, Professor Christine Moorman of Duke University’s Fuqua School of Business, a leading scholar of marketing strategy and the director of The CMO Survey, examines whether protecting marketing knowledge is worth the cost.

Drawing from in-depth interviews with senior executives across industries, Moorman and her co-authors explore how firms manage three types of marketing knowledge: customer and competitor insights, marketing plans, and marketing know-how, such as pricing algorithms. Their research challenges the conventional wisdom that tighter control always leads to stronger advantage.

The research found that efforts to prevent knowledge leakage often generate significant costs, while the external benefits may be overstated. Firms frequently rely on “leakage prevention strategies” that restrict who can access or share information. But Moorman finds these controls can create a set of “hidden costs” that can undermine decision quality, slow execution, and even weaken morale. Protection can also unintentionally block learning as well as leaks. “If you put up all of these barriers, those same barriers are going to also prevent information from coming to you,” she said.

On the benefit side, Moorman points out that these benefits may be overestimated. The reason is that even when information escapes, competitors must first notice it, interpret it correctly, and have the resources to act on it before any real harm occurs.

Moorman suggests that instead of obsessing over preventing leaks, companies should first weigh a careful assessment of these costs and benefits. Companies should also consider alternative knowledge protection strategies that do not have these costs. These include investing in harm prevention strategies, like refreshing their marketing knowledge faster than competitors can use it, and out-executing rivals even when information escapes. Competitive advantage may depend less on secrecy and more on speed.

Duke Fuqua Insights features digestible conversations with our faculty about the most impactful research from their careers, including studies they teach in Fuqua classes. New episodes every other week in season.

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Professor Anna Cieslak explains how central bank communication shapes financial markets, even when rates stay the same

When the Federal Reserve meets, markets obsess over one question: Will interest rates go up or down? But sometimes, market moves happen even when rates don’t change at all. In uncertain times, a subtle shift in tone can ripple across global financial markets.

In this episode of Duke Fuqua Insights Podcast, Professor Anna Cieslak of Duke University’s Fuqua School of Business explores how central bank communication shapes financial conditions beyond formal rate decisions.

Her research examines how the Fed uses “policy tilts”—signals about future intentions—to influence investor expectations and long-term interest rates.

Drawing on decades of data—including the late 1990s productivity boom and the post-COVID recovery—her research shows how policy tilts shift investor risk perceptions and long-term Treasury yields, with effects that can rival formal rate decisions.

She explains that the Fed follows a “risk management approach,” assessing not just the most likely forecast but also low-probability, high-cost scenarios. By signaling vigilance, policymakers reduce fears that they will fall behind inflation.

The stakes of getting communication right are high. In 2021, the Fed's 'lower for longer' messaging diverged from rising inflation concerns, tightening financial conditions even as rates held steady. As former Fed Chair Ben Bernanke observed, monetary policy is '98% talk and 2% action'—which means parsing Fed language is as important as watching the rate decision itself.

Duke Fuqua Insights features digestible conversations with our faculty about the most impactful research from their careers, including studies they teach in Fuqua classes. New episodes every other week in season.

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Professor Elia Ferracuti explains how activist investors reshape corporate research, and why it matters for long-term innovation.

Why would a company famous for breakthrough discoveries suddenly pull back from bold research in favor of safer bets? Research shows shareholder pressure plays a role. The tension between short-term financial pressure and long-term scientific progress is at the heart of many hedge-fund-led activist campaigns and may explain why companies retreat from basic research, with effects across the broader innovation ecosystem.

In this episode, Professor Elia Ferracuti, an accounting scholar at Duke University’s Fuqua School of Business, discusses new research—co-authored by Fuqua’s Rahul Vashishtha and Kevin Standbridge of the University of Utah—on how hedge fund activism affects corporate science.

Drawing on large-scale data linking activist investor campaigns to corporate research outputs, Ferracuti and his coauthors examine what happens inside firms after activists push for operational and governance changes. Their analysis spans multiple industries, with particularly rich evidence from pharmaceuticals, where innovation choices are easier to observe and compare.

The research found that after firms are targeted by activist hedge funds, they produce significantly less scientific research. Measured through publications in academic journals, corporate science declines overall—and drops most sharply in top-tier journals. In pharmaceuticals, targeted firms also shift away from novel drugs toward more incremental “me-too” compounds that closely resemble existing treatments. “Activism pushes corporations away from risky activities with long gestation periods and large spillovers,” Ferracuti said.

Why does this happen? Hedge fund activists typically acquire minority stakes but exert outsized influence, pressing managers to boost near-term returns. According to Ferracuti, this pressure changes internal priorities: “Foundational scientific research may be among the first activities to go.” Because basic research is uncertain, slow to pay off, and often benefits society more than any single firm, it becomes vulnerable when managers face intense scrutiny to deliver quick results.

The effects don’t stop with targeted firms. Rival companies in the same industry also scale back research, likely because they fear becoming the next activist target.

Shareholder activism can improve efficiency—but it also carries hidden costs for innovation, economic growth, and social welfare.

Ferracuti cautions against “fiddling” with the functioning of capital markets, instead pointing to the growing importance of sustaining and incentivizing fundamental research, especially at universities, at a time when public support for science is under pressure.

Duke Fuqua Insights features digestible conversations with our faculty about the most impactful research from their careers, including studies they teach in Fuqua classes. New episodes every other week in season.

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Professor Simon Gervais explains how active managers can grow the economy, even when they don’t beat the market

Many investors are told that active funds rarely outperform passive index funds after fees. So why bother paying for them?

In this episode of Duke Fuqua Insights podcast, Professor Simon Gervais, a financial economist at Duke University’s Fuqua School of Business, challenges the narrow way we evaluate active money management. Drawing on his paper, “Money Management and Real Investment”, Gervais argues that focusing only on fund returns misses a critical role active managers play in the economy: improving how capital is allocated across firms and industries. Rather than acting as passive observers, active managers influence real corporate investment decisions through the information embedded in stock prices.

The central insight of Gervais’s research is that active money managers can create economic value even if their funds generate negative net returns after fees. By trading on information about industries, competition, and macroeconomic trends, active managers help direct capital toward more productive uses. The result is a “bigger economic pie,” even if investors receive a slightly smaller slice of it.

Active managers trade on information that corporate executives may not fully have, pushing stock prices up or down. Firms then learn from these price movements and adjust investment decisions accordingly. As Gervais puts it, if a firm announces a merger and its stock went down, maybe that is the signal that the merger was a bad idea.

For MBA students and business leaders, the takeaway is a broader view of value creation. Passive investors may benefit indirectly from better capital allocation, but unlike active managers, they don’t automatically adjust as the economy changes. The research calls into question how regulators, investors, and institutions evaluate asset managers. If active management improves productivity and risk allocation, then traditional performance metrics like alpha may be incomplete. As Gervais suggests, the real challenge is learning how to measure not just who captures value, but who creates it.

Duke Fuqua Insights features digestible conversations with our faculty about the most impactful research from their careers, including studies they teach in Fuqua classes. New episodes every other week in season.

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Artificial intelligence promises massive productivity gains, but not everyone can immediately jump in to reap its benefits. While some firms and countries race ahead with new tools, others deliberately stick with older technologies, a choice may be entirely rational.

In this episode of the Fuqua Insights podcast, Professor John Coleman of Duke University’s Fuqua School of Business joins host Sarah Kern to discuss how economies and businesses choose technologies based on the skills of their workforce. Drawing on his paper The World Technology Frontier, co-authored with Francesco Caselli of the London School of Economics, Coleman explores why countries with access to the same global technologies nonetheless adopt very different production methods and experience sharply different income levels.

Coleman’s central finding is that technology adoption is often an optimal choice, not a failure. Coleman distinguishes between skilled and unskilled labor, economic terms based primarily on formal education levels rather than the actual difficulty or value of work. In this framework, "skilled" workers have training that allows them to adapt to and leverage new technologies, while "unskilled" refers to workers with less formal education who may be highly capable but less equipped to use tools like AI.

Advanced economies tend to develop and use technologies that favor skilled labor, while less-developed economies rely on older, less skill-intensive tools because those technologies better match their labor force. As Coleman explains, a poorer country may “optimally choose to adopt what seems to an advanced economy to be a backward technology”, because using more advanced tools without the right skills can actually reduce productivity.

While technologies developed a long time ago are most suitable for labor that is mostly unskilled, newer technologies are designed for highly educated workers, Coleman notes. This framework applies directly to AI: “AI was developed by advanced economies that have the skilled labor that would benefit most from AI,” he says. Without that skill base, adopting AI may not pay off.

Business leaders should remember to align innovations with workforce capabilities. “Adopting AI without a well-developed plan to integrate it into your workforce would likely be a disaster,” Coleman warns. Globally, AI may widen gaps in the short run, but Coleman emphasizes that technology is not a zero-sum game. Over time, moving up the technology frontier can create opportunities for growth across economies.

Editor's Note: This episode was recorded prior to the extradition of Nicolás Maduro on January 3, 2026.

Duke Fuqua Insights features digestible conversations with our faculty about the most impactful research from their careers, including studies they teach in Fuqua classes. New episodes every other week in season.

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Professor David Brown explains how simple strategies can guide better decisions even when information is incomplete

New job postings appear daily. Real estate markets update constantly with fresh listings. In an environment where alternatives continuously multiply and options can seem endless, the hardest decision is knowing when to stop searching and commit.

In this episode, David Brown, the Snow Family Business Professor of Decision Sciences at Duke University’s Fuqua School of Business, discusses how people and organizations can make better decisions when information is scarce or costly.

Building on economist Martin Weitzman’s classic “Pandora’s Box Problem,” Brown and his co-author, Fuqua Ph.D. student Cagin Uru, found that straightforward search rules perform nearly as well as complex algorithms. Their research shows a surprisingly simple solution: commit upfront to search a specific number of alternatives based on search costs, then simply rank what you've seen and choose the best.

What makes their approach practical and appealing is its simplicity: it requires only the ability to rank alternatives you've seen and the discipline to stop searching at the right point, not probability calculations or complex data analysis. This applies broadly, from navigating job searches to booking flights to hiring contractors.

The conversation also explores when sophisticated algorithms are truly necessary. Their research shows that, across several search settings, their simple, transparent rules perform nearly as well as those based on more complex approaches (e.g., AI), raising questions about when algorithmic solutions are worth the investment.

Duke Fuqua Insights features digestible conversations with our faculty about the most impactful research from their careers, including studies they teach in Fuqua classes. New episodes every other week in season.

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A single decision improved by 1% might seem trivial. But make 300 small improvements over a year, and the compounding effect becomes transformative. A/B testing allows companies to systematically test different approaches and optimize performance, but research shows that the startups that could benefit most are the least likely to use it.

In this episode, Professor Sharique Hasan of Duke University’s Fuqua School of Business discusses his paper “Experimentation and Start-up Performance: Evidence from A/B Testing,” which focuses on how startups use A/B testing to drive performance. Based on data from more than 35,000 startups, Hasan and his coauthors found those that adopt A/B testing experience significantly higher performance over time—sometimes doubling outcomes after a year.

Hasan explains that while the impact is strongest for smaller and non–Silicon Valley startups, these firms often lack the resources to implement A/B testing effectively. For them, he introduces the concept of “experimental thinking” as a more accessible alternative: a mindset of comparing options rigorously, asking the right causal questions, and framing decisions with clear counterfactuals.

Drawing from both large-scale quantitative analysis and rich qualitative insights from tech practitioners, Hasan describes how small, compound decisions can lead to transformative outcomes.

Duke Fuqua Insights features digestible conversations with our faculty about the most impactful research from their careers, including studies they teach in Fuqua classes. New episodes every other week in season.

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