Donna Mitchell

expert panel

Healthcare organizations are under pressure from every direction. Consumers increasingly expect the same convenience, transparency and responsiveness they receive from retail, banking and hospitality brands. At the same time, providers and health systems face shrinking reimbursement rates, labor shortages, administrative burdens and rising operational costs. The tension is becoming impossible to ignore. According to a 2025 McKinsey analysis of the U.S. healthcare industry, financial pressures remain severe across hospitals and physician groups despite gradual margin stabilization. Meanwhile, a growing number of patients delay or avoid care because of cost concerns and confusion around billing and insurance coverage. Members of the Senior Executive Healthcare Think Tank argue that organizations cannot solve this challenge through cost-cutting alone. Instead, they believe healthcare leaders must rethink how care is delivered, coordinated and experienced. Below, Think Tank members share how healthcare leaders can reduce waste, improve patient trust and modernize care delivery while navigating the financial realities reshaping the industry.

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Artificial intelligence is rapidly reshaping healthcare, from predictive analytics to clinical decision support. Yet its promise comes with a critical caveat: AI systems are only as reliable and equitable as the data and decisions that shape them. Without intentional oversight, these tools risk reinforcing—rather than reducing—longstanding disparities in care delivery. Members of the Senior Executive Healthcare Think Tank bring deep expertise across technology, policy, patient experience and equity. They believe addressing bias in clinical AI is not just a technical challenge but a leadership responsibility. A recent analysis from Kaiser Family Foundation found that AI can exacerbate disparities when models are trained on biased or incomplete data, with studies linking AI use to longer wait times, underdiagnosis and poorer predictive performance for Black and Hispanic patients. At the same time, the research notes that AI could help reduce disparities if it is intentionally designed with representative data, transparency and ongoing oversight—reinforcing the dual reality leaders now face. Against this backdrop, healthcare leaders must rethink how AI is designed, validated and governed. The following insights from Think Tank members offer a roadmap for ensuring clinical AI improves outcomes for all patients—not just a subset.

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Artificial intelligence and blockchain are starting to converge within real business infrastructure. From AI agents that can autonomously execute transactions to decentralized marketplaces where data is bought, sold and verified, the two technologies’ complementary advantages could reshape how organizations operate, transact and stay accountable. Blockchain’s core strengths—immutability, transparency and decentralized trust—address some of AI’s most persistent weaknesses, including the challenge of explaining or auditing how decisions are made (aka the “black box” issue). At the same time, AI can bring intelligence and adaptability to blockchain networks that have historically required significant manual oversight.  However, the convergence also introduces risks. There’s the AI accountability gap—questions around liability, regulatory compliance and who’s accountable when an autonomous system makes a costly mistake don’t yet have clear answers. Business leaders who move fast without resolving those questions may find themselves exposed in ways they didn’t anticipate. As experts in blockchain, Web3, digital identity and distributed ledger technology, the members of the Senior Executive Blockchain Think Tank are keeping a close eye on the convergence of AI and blockchain. Below, two of them discuss functions and sectors where blending AI and blockchain makes the most sense, as well as the risks and governance gaps pioneering organizations can’t afford to ignore.

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As enterprises race to modernize supply chains and core operations, AI is muscling its way into the world of smart contracts. Business leaders are discovering that AI-enhanced smart contracts and analytics tools can unlock new efficiencies—but only if they’re deployed with the same rigor they promise to automate. AI-enhanced smart contracts do come with significant challenges. Without careful implementation, they can introduce new vulnerabilities, from biased or poor-quality data feeding automated decisions to opaque algorithms that complicate audits or dispute resolution. Yet when these systems are built on clean data, transparent governance and interoperable architecture, the upsides are substantial. Faster execution, real-time quality checks and predictive insights can streamline operations and generate measurable ROI, especially in complex supply chains where small efficiencies multiply quickly. Blockchain pioneers have a unique vantage point in this moment. They’ve spent years navigating immutable ledgers, decentralized architectures and cross-platform integrations—precisely the terrain where AI-enabled contracting now lives. Here, two members of the Senior Executive Blockchain Think Tank—experts in blockchain, distributed ledger technology, smart contracts and more—discuss why and how businesses should implement AI-enhanced smart contracts.

expert panel

As leading technology firms such as Google, Uber, Apple and Shopify move to explore stablecoin adoption, enterprise payments appear poised for transformation. The shift signals growing confidence in digital assets as a foundation for faster, lower-cost global transactions—and a potential turning point in how corporations manage cross-border operations. Recent research from McKinsey & Company suggests that tokenized cash and stablecoins could drive the next generation of payments, marking 2025 as a pivotal year for institutional adoption. The implications extend beyond operational efficiency to issues of compliance, volatility management and financial infrastructure readiness. The members of Senior Executive Blockchain Think Tank, a group of leaders with expertise spanning Web3, distributed ledger technology, digital identity and tokenization, bring deep insight into how this evolution may reshape enterprise operations. Here, two of them discuss what businesses need to do to prepare for this transition—underscoring that this shift is not merely a technological change but a strategic inflection point for enterprise finance.

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In July 2025, the U.S. Securities and Exchange Commission announced it was establishing formal regulatory frameworks for digital assets—including tokenized securities, DeFi platforms and disclosure standards—with the launch of Project Crypto. According to SEC Chairman Paul S. Atkins, the initiative seeks to “modernize the securities rules and regulations to enable America’s financial markets to move on-chain.” For blockchain leaders and innovators, this marks a welcome shift from ambiguity to actionable clarity—particularly around how tokenized assets will be classified, which DeFi activities will fall under securities oversight, and what disclosure standards will be required for institutional adoption. The critical question for C-suite leaders is no longer whether blockchain will be regulated, but how quickly disciplined adoption will become a differentiator for market leadership. Members of the Senior Executive Blockchain Think Tank, a curated group of blockchain innovators and executives, are carefully assessing the implications as the SEC moves forward. Below, two of them share how they interpret Project Crypto—and how business leaders should prepare to navigate the evolving legal landscape while remaining competitive.