Blog categorized as AI Strategy

Human optimism fuels effort, learning, and change. But technological optimism—the kind that dismisses friction and treats governance as obstruction—creates systems that drift toward the logic of their incentives. When a system never bears the consequence of error, someone else inevitably will.

AI is changing markets, expectations, and operating rhythms. But the principles of adaptive leadership haven’t changed, they’ve simply become non-negotiable.

What makes AI more reliable in practice, not in demos? The answer is better context design.

Progress belongs to those who build environments that learn faster than their models. Cultivating intelligence also means cultivating platform skill—knowing your soil.

In AI adoption, design is no longer about polish—it’s about judgment. Here’s how strategists and designers can embed reflection and reasoning into their systems.

How intelligent decision environments can make organizations learn faster, adapt better, and lead with greater.

How the democratization of AI is reshaping innovation, quality, and leadership inside modern enterprises.

How to navigate AI transformation without falling into the hype trap.

In this article, we'll dive into the key findings of the 2024 AI Index Report, focusing on benchmarks for truthfulness, reasoning, and agent-based systems, and explore their implications for businesses.

The 2024 HAI AI Index Report reveals a rapidly evolving AI landscape characterized by rising training costs, potential data constraints, the dominance of foundation models, and a shift towards open-source AI.

How do you create a generative AI strategy?

How do you create a generative AI strategy?

A new study has shown that transformers can be expressed in a simple logic formalism. This finding challenges the perception that transformers are inscrutable black boxes and suggests avenues for interpreting how they work.

When designing BloombergGPT, a new large language model optimized for financial data, the researchers at Bloomberg made an important decision around tokenization.

When designing BloombergGPT, a new large language model optimized for financial data, the researchers at Bloomberg made an important decision around tokenization.