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Navigating Uncertainty: AI Drives an Inflection Point for the Global Economy - Boyden
The ongoing maturity of private equity and venture capital is driving financial innovation and aligning business models to a geopolitical environment characterised by ‘controlled disorder’ and digital innovation. AI is spurring growth and value creation in private equity and portcos, revealing the truth about AI ‘bubble mania’ for business leaders, investors and high performance executives. Boyden’s Private Equity & Venture Capital Practice brings clarity to this complexity, examining how uncertainty is influencing investment strategies, portfolio performance, and leadership priorities across the sector. Each edition of the Navigating Uncertainty series explores a defining trend shaping the future of private equity and venture capital. Through the perspective of Boyden experts worldwide, the series delivers forward-looking analysis, actionable insights, and leadership intelligence to help investors and portfolio executives anticipate what’s next and lead with confidence. March 2026 ‘Controlled disorder’ sees private equity at the heart of economic evolution In the face of today’s multifaceted challenges, private equity leaders and investors remind us to keep calm, engineer solutions, diversify the investor base, hire with precision... and quietly take care of AI ‘bubble mania’. As business leaders strive to absorb tariff shocks, policy pressures and new market dynamics, we find ourselves at an inflection point: ‘the global economy is experiencing a transition, not a downturn,’ asserts Amundi Investor Solutions. Amundi’s Head of Investment Institute, Monica Defend, explains, “The economy is adapting to a new regime of ‘controlled disorder."1 In this environment, confidence among large corporate business leaders and finance professionals is unstable and patchy. PwC’s Annual Global CEO Survey reveals that 3 out of 5 CEOs (60%) think their company needs a major reinvention to survive the next decade2. According to ACCA, confidence among finance professionals remains at historically low levels, particularly in North America and Western Europe3. How does this compare with sentiment among private equity portco CEOs? Boyden poll data shows that 43% of portco CEOs agree or strongly agree that their organisation needs a major reinvention to survive the next decade; 13% disagree. Source: In February 2026 Boyden conducted a poll among the firm’s global private equity & venture capital experts, capturing sentiment and strategies among clients, GPs, LPs and com...
As AI Takes on Decision Making in Finance, the Risk Is No Longer Just ...
Artificial intelligence has long been used to analyse markets. Now, it is beginning to act within them.Across trading desks, asset managers and financial infrastructure providers, the role of AI is shifting from generating signals to influencing decisions. This transition from observation to action is quietly redefining how risk is understood in modern markets.For years, AI in finance has been framed around prediction, forecasting price movements, identifying patterns and optimising strategies. But as systems become more integrated into execution and workflow processes, the implications are becoming more complex.At the centre of this shift is a simple but critical question: what happens when an AI system is wrong?This issue was a focal point at the recent Agentic AI and Automation in Finance Summit in Atlanta, where discussions moved beyond model performance and toward system accountability. During a panel featuring Kaushal Sheth of GFT Technologies, alongside Juan Mendez of BlackRock, the conversation highlighted how AI’s expanding role is introducing a new category of operational risk.The challenge is no longer limited to whether a model can generate accurate outputs. It is whether those outputs, when embedded into decision making processes, can be trusted under real market conditions.Agentic AI systems designed to operate across multiple stages of financial workflows are accelerating this shift. These systems can analyse data, generate insights and in some cases trigger actions without direct human intervention. While this improves efficiency, it also compresses the margin for error.In traditional models, a flawed signal might be ignored or filtered. In autonomous systems, the same flaw can propagate into execution.That distinction is subtle, but significant.As Kaushal Sheth noted during the discussion, understanding how systems behave during abnormal market conditions is becoming more important than their performance during stable periods. Financial markets are defined by regime shifts, moments when correlations break, liquidity disappears and historical patterns lose relevance.These are precisely the environments where AI systems are most likely to be tested.Yet they are also the hardest to simulate.This creates a structural gap between development and deployment. While models can be trained on vast datasets, real world validation still depends on exposure to unpredictable market conditions. The feedback loop is slower, and the consequences of failure...
More Rational Than Us? How AI is Reshaping Financial Decision-Making
On the other hand, the risk of AI collusion that we mentioned earlier undermines competition and market efficiency. What role should human oversight play in financial decision-making as AI becomes more deeply embedded in investment processes? Human oversight remains central because getting AI right does not mean automating everything.
The 2026 AI Investment Supercycle: Navigating Geopolitical Turmoil and Economic Shifts
Complicating the outlook is the Iran war and its consequences, which threaten a global downturn from which AI may not be able to escape. Traders have already priced out rate cuts until December at the earliest, with potential knock-on effects for debt-funded AI capex. In this article, we look at where the AI sector may be headed in 2026, a year which already looks to be fraught with uncertainty.
