Divya Parekh

expert panel

As enterprise AI adoption accelerates, so too does the complexity of choosing the right foundation. Should companies invest in proprietary platforms like GPT-4 or Claude, or build on open-source models such as Meta’s Llama or Mistral? The answer increasingly lies not in technical specs alone, but in how each option aligns with an organization’s cost structure, data governance needs and long-term innovation strategy. Recent research from McKinsey & Company underscores the growing momentum behind open systems: Over 50% of enterprises already report using open-source AI tools across their technology stack, and 76% expect to increase usage in the coming years. At the same time, proprietary platforms offer speed, reliability and white-glove scalability—often the shortest path to business impact. The trade-offs are real and consequential. To help executive decision-makers navigate these choices, we turned to members of the Senior Executive AI Think Tank—a group of enterprise AI, machine learning and innovation leaders who are shaping the way organizations operationalize artificial intelligence. In the sections below, they break down the pros and cons of each approach and offer actionable guidance on when to build, when to buy and how to orchestrate the right AI model strategy for your organization’s evolving needs.

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The FDA’s new generative AI tool, Elsa, could signal the start of AI-native government operations—streamlining scientific reviews, increasing public transparency, and reshaping how trust is earned in digital-era governance. But as Elsa ushers in new efficiencies, AI leaders warn: Success depends on human oversight, ethical frameworks, and explainable systems.

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AI Think Tank members explore how OpenAI’s upcoming “super-assistants” could impact daily habits, reduce mental load and enhance productivity for consumers everywhere.

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AI Think Tank members weigh in on Meta's plan to fully automate ad creation by 2026—highlighting the efficiency gains, strategic risks, and human oversight required to stay competitive and authentic.

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As AI-generated content floods every platform, how can businesses preserve authenticity and build trust? Members of the Senior Executive AI Think Tank share how they’re staying human in a sea of automation.

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AI Think Tank members predict the future of business dashboards, where natural language, predictive analytics, and strategic recommendations replace static charts and siloed metrics.